Bearing fault diagnosis based on Gramian angular field and DenseNet

Yajing Zhou; Xinyu Long; Mingwei Sun; Zengqiang Chen; Yajing Zhou; Xinyu Long; Mingwei Sun; Zengqiang Chen

doi:10.3934/mbe.2022656

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 12: 14086-14101. doi: 10.3934/mbe.2022656

Previous Article Next Article

Research article Special Issues

Bearing fault diagnosis based on Gramian angular field and DenseNet

College of Artificial Intelligence, Nankai University, Tianjin 300350, China

Academic Editor: Hamid Reza Karimi

Received: 20 August 2022 Revised: 09 September 2022 Accepted: 20 September 2022 Published: 26 September 2022

Rolling bearings are the core components of mechanical and electrical systems. A practical fault diagnosis scheme is the key to ensure operational safety. There are excessive characteristic parameters with remarkable randomness and severe signal coupling in the rolling bearing operation, which makes the fault diagnosis to be challenging. To deal with this problem, the Gramian angular field (GAF) and DenseNet are combined to perform feature extraction and fault diagnosis. The GAF can convert 1-dimensional time series into an image, which can guarantee the completeness of feature information without temporal dependence. The GAF images are then trained by using the DenseNet to generate a data set network. In this process, the transfer learning (TL), which can solve the problem of insufficient samples, is integrated to the DenseNet to enhance its extensibility. The comparative simulations are carried out to illustrate the effectiveness of the proposed method.

Keywords:

Citation: Yajing Zhou, Xinyu Long, Mingwei Sun, Zengqiang Chen. Bearing fault diagnosis based on Gramian angular field and DenseNet[J]. Mathematical Biosciences and Engineering, 2022, 19(12): 14086-14101. doi: 10.3934/mbe.2022656

Related Papers:

[1]	Shuyue Ma, Jiawei Sun, Huimin Yu . Global existence and stability of temporal periodic solution to non-isentropic compressible Euler equations with a source term. Communications in Analysis and Mechanics, 2023, 15(2): 245-266. doi: 10.3934/cam.2023013
[2]	Zhigang Wang . Serrin-type blowup Criterion for the degenerate compressible Navier-Stokes equations. Communications in Analysis and Mechanics, 2025, 17(1): 145-158. doi: 10.3934/cam.2025007
[3]	Hongxia Lin, Sabana, Qing Sun, Ruiqi You, Xiaochuan Guo . The stability and decay of 2D incompressible Boussinesq equation with partial vertical dissipation. Communications in Analysis and Mechanics, 2025, 17(1): 100-127. doi: 10.3934/cam.2025005
[4]	Yang Liu, Xiao Long, Li Zhang . Long-time dynamics for a coupled system modeling the oscillations of suspension bridges. Communications in Analysis and Mechanics, 2025, 17(1): 15-40. doi: 10.3934/cam.2025002
[5]	Fangyuan Dong . Multiple positive solutions for the logarithmic Schrödinger equation with a Coulomb potential. Communications in Analysis and Mechanics, 2024, 16(3): 487-508. doi: 10.3934/cam.2024023
[6]	Zhen Wang, Luhan Sun . The Allen-Cahn equation with a time Caputo-Hadamard derivative: Mathematical and Numerical Analysis. Communications in Analysis and Mechanics, 2023, 15(4): 611-637. doi: 10.3934/cam.2023031
[7]	Rui Sun, Weihua Deng . A generalized time fractional Schrödinger equation with signed potential. Communications in Analysis and Mechanics, 2024, 16(2): 262-277. doi: 10.3934/cam.2024012
[8]	Chunyou Sun, Junyan Tan . Attractors for a Navier–Stokes–Allen–Cahn system with unmatched densities. Communications in Analysis and Mechanics, 2025, 17(1): 237-262. doi: 10.3934/cam.2025010
[9]	Yue Pang, Xiaotong Qiu, Runzhang Xu, Yanbing Yang . The Cauchy problem for general nonlinear wave equations with doubly dispersive. Communications in Analysis and Mechanics, 2024, 16(2): 416-430. doi: 10.3934/cam.2024019
[10]	Yang Liu . Global attractors for a nonlinear plate equation modeling the oscillations of suspension bridges. Communications in Analysis and Mechanics, 2023, 15(3): 436-456. doi: 10.3934/cam.2023021

Abstract

1. Introduction

In this paper, we study the 2D steady compressible Prandtl equations in $\left\{ x > 0, y > 0 \right\}$ :

$\begin{align} \left\{\begin{aligned} &u\partial_{x}u+v\partial_{y}u-\frac{1}{\rho}\partial^{2}_{y}u = -\frac{\partial_{x}P(\rho)}{\rho},\\ &\partial_{x}(\rho u)+\partial_{y}(\rho v) = 0,\\ & u|_{x = 0} = u_{0}(y), \quad\lim\limits_{y\to \infty}u = U(x),\\ &u|_{y = 0} = v|_{y = 0} = 0, \end{aligned}\right. \end{align}$

(1.1)

where $(u, v)$ is velocity field, $\rho(x)$ and $U(x)$ are the traces at the boundary $\left\{y = 0\right\}$ of the density and the tangential velocity of the outer Euler flow. The states $\rho, U$ satisfy the Bernoulli law

$\begin{align} U\partial_{x}U+\frac{\partial_{x}P(\rho)}{\rho} = 0. \end{align}$

(1.2)

The pressure $P(\rho)$ is a strictly increasing function of $\rho$ with $0 < \rho_{0}\leq\rho \leq \rho_{1}$ for some positive constants $\rho_{0}$ and $\rho_{1}$ .

In this paper, we assume that the pressure satisfies the favorable pressure gradient $\partial_{x}P\leq0$ , which implies that

$\partial_{x}\rho\leq0.$

The boundary layer is a very important branch in fluid mechanics. Ludwig Prandtl ^[14] first proposed the related theory of the boundary layer in 1904. Since then, many scholars have devoted themselves to studying the mathematical theory of the boundary layer ^{[1,7,8,9,11,12,17,18,19,21,22,23,24,26,27]}. For more complex fluids, such as compressible fluids, one can refer to ^[19,20,28] and the references therein for more details. Here, for our purposes, we only list some relevant works.

There are three very natural problems about the steady boundary layer: (ⅰ) Boundary layer separation, (ⅱ) whether Oleinik's solutions are smooth up to the boundary for any $x > 0$ and (ⅲ) vanishing viscosity limit of the steady Navier-Stokes system. Next, we will introduce the relevant research progress in these three aspects. The separation of the boundary layer is one of the very important research contents in the boundary layer theory. ^[17]. The earliest mathematical theory in this regard was proposed by Caffarelli and E in an unpublished paper ^[25]. Their results show that the existence time $x^{*}$ of the solutions to the steady Prandtl equations in the sense of Oleinik is finite under the adverse pressure gradient. Moreover, the family $u_{\mu}(x, y) = \mu^{-\frac{1}{2}}u(x^{*}-\mu x, \mu^{\frac{1}{4}}y)$ is compact in $C^{0}(\mathbb{R}_{+}^{2})$ . Later, Dalibard and Masmoudi ^[4] proved the solution behaves near the separation as $\partial_{y} u(x, 0)\sim(x^{*}-x)^{\frac{1}{2}}$ for $x < x^{*}$ . Shen, Wang and Zhang ^[18] found that the solution near the separation point behaves like $\partial_{y} u(x, y)\sim(x^{*}-x)^{\frac{1}{4}}$ for $x < x^{*}$ . The above work further illustrates that the boundary layer separation is a very complex phenomenon. Recently, there were also some results about the steady compressible boundary layer separation ^[28]. The authors found that if the heat transfer in the boundary layer disappeared, then the singularity would be the same as that in the incompressible case. There is still relatively little mathematical theory on the separation of unsteady boundary layers. This is because back-flow and separation no longer occur simultaneously. When the boundary layer back-flow occurs, the characteristics of the boundary layer will continue to maintain for a period of time. Therefore, it is very important to study the back-flow point for further research on separation. Recently, Wang and Zhu ^[21] studied the back-flow problem of the two-dimensional unsteady boundary layer, which is a important work. It is very interesting to further establish the mathematical theory of the unsteady boundary layer separation.

Due to degenerate near the boundary, the high regularity of the solution of the boundary layer equation is a very difficult and meaningful work. In a local time $0 < x < x^{*}\ll 1$ , Guo and Iyer ^[6] studied the high regularity of of the Prandtl equations. Oleinik and Samokhin ^[13] studied the existence of solutions of steady Prandtl equations and Wang and Zhang ^[23] proved that Oleinik's solutions are smooth up to the boundary $y = 0$ for any $x > 0$ . The goal of this paper is to prove the global $C^{\infty}$ regularity of the two-dimensional steady compressible Prandtl equations. Recently, Wang and Zhang ^[24] found the explicit decay for general initial data with exponential decay by using the maximum principle.

In addition, in order to better understand the relevant background knowledge, we will introduce some other related work. As the viscosity goes to zero, the solutions of the three-dimensional evolutionary Navier-Stokes equations to the solutions of the Euler equations are an interesting problem. Beirão da Veiga and Crispo ^[2] proved that in the presence of flat boundaries convergence holds uniformly in time with respect to the initial data's norm. For the non-stationary Navier-Stokes equations in the 2D power cusp domain, the formal asymptotic expansion of the solution near the singular point is constructed and the constructed asymptotic decomposition is justified in ^[15,16] by Pileckas and Raciene.

Before introducing the main theorem, we introduce some preliminary knowledge. To use the von Mises transformation, we set

$\begin{align*} \tilde{u}(x,y) = \rho(x) u(x,y),\quad \tilde{v}(x,y) = \rho(x) v(x,y),\quad \tilde{u}_{0}(y) = \rho(0)u_{0}(y), \end{align*}$

then we find that $(\tilde{u}, \tilde{v})$ satisfies:

$\begin{align} \left\{\begin{aligned} &\tilde{u}\partial_{x}\tilde{u}+\tilde{v}\partial_{y}\tilde{u}-\partial^{2}_{y}\tilde{u}-\frac{\partial_{x}\rho}{\rho}\tilde{u}^{2} = -\rho \partial_{x}P(\rho),\\ &\partial_{x}\tilde{u}+\partial_{y}\tilde{v} = 0,\\ &\tilde{u}|_{x = 0} = \tilde{u}_{0}(y),\quad\lim\limits_{y\to \infty}\tilde{u} = \rho(x)U(x),\\ &\tilde{u}|_{y = 0} = \tilde{v}|_{y = 0} = 0. \end{aligned}\right. \end{align}$

(1.3)

By the von Mises transformation

$\begin{align} x = x, \quad \psi(x,y) = \int_{0}^{y}\tilde{u}(x,z)dz,\quad w = \tilde{u}^{2}, \end{align}$

(1.4)

$\begin{align} \begin{aligned} \partial_{x}\tilde{u} = \frac{\partial_{x}\omega}{2\sqrt{\omega}}+\frac{\partial_{\psi}\omega\partial_{x}\psi}{2\sqrt{\omega}}, \quad \partial_{y}\tilde{u} = \frac{\partial_{\psi}\omega}{2}, \quad \partial_{y}^{2}\tilde{u} = \frac{\sqrt{\omega}\partial_{\psi}^{2}\omega}{2}, \end{aligned} \end{align}$

(1.5)

and (1.3)–(1.5), we know that $w(x, \psi)$ satisfies:

$\begin{align} \partial_{x}w-\sqrt{w}\partial_{\psi}^{2}w-2\frac{\partial_{x}\rho}{\rho}w = -2\rho\partial_{x}P(\rho), \end{align}$

(1.6)

with

$\begin{align} w(x,0) = 0,\quad w(0,\psi) = w_{0}(\psi),\quad \lim\limits_{\psi\to+\infty}w = (\rho(x)U(x))^{2}. \end{align}$

(1.7)

In addition, we have

$\begin{align} 2\partial_{y}\tilde{u} = \partial_{\psi}w,\qquad2\partial_{y}^{2}\tilde{u} = \sqrt{w}\partial_{\psi}^{2}w. \end{align}$

(1.8)

In ^[5], Gong, Guo and Wang studied the existence of the solutions of system (1.1) by using the von Mises transformation and the maximal principle proposed by Oleinik and Samokhin in ^[13]. Specifically, they proved that:

Theorem 1.1. If the initial data $u_{0}$ satisfies the following conditions:

$\begin{align} \begin{aligned} &u\in C^{2,\alpha}_{b}([0,+\infty))(\alpha > 0),\quad u(0) = 0,\quad\partial_{y}u(0) > 0,\quad\partial_{y}u(y)\geq0\quad\mathit{\text{for}}\quad y\in[0,+\infty), \\ &\lim\limits_{y\to+\infty}u(y) = U(0) > 0,\quad\rho^{-1}(0)\partial_{y}^{2}u(y)-\rho^{-1}(0)\partial_{x}P(0) = O(y^{2}) \end{aligned} \end{align}$

(1.9)

and $\rho\in C^{2}([0, X_{0}])$ , then there exists $0 < X\leq X_{0}$ such that system (1.1) admits a solution $u\in C^{1}([0, X)\times \mathbb{R}_{+})$ . The solution has the following properties:

$(i)$ $u$ is continuous and bounded in $[0, X]\times \mathbb{R}_{+}$ ; $\partial_{y}u, \partial_{y}^{2}u$ are continuous and bounded in $[0, X)\times \mathbb{R}_{+}$ ; $v, \partial _{y}v, \partial_{x}u$ are locally bounded in $[0, X)\times \mathbb{R}_{+}$ .

$(ii)$ $u(x, y) > 0$ in $[0, X)\times \mathbb{R}_{+}$ and for any $\bar{x} < X$ , there exists $y_{0}, m > 0$ such that for all $(x, y)\in[0, \bar{x}]\times[0, y_{0}]$ ,

$\partial_{y}u(x,y )\geq m > 0.$

$(iii)$ if $\partial_{x}P\leq0(\partial_{x}\rho\leq0)$ , then

$X = +\infty.$

Remarks 1.2. $u\in C^{2, \alpha}_{b}([0, +\infty))(\alpha > 0)$ means that $u$ is Hölder continuity and bounded.

This theorem shows that under the favorable pressure gradient, the solution is global-in- $x$ . However, if the pressure is an adverse pressure gradient, then boundary layer separation will occur. Xin and Zhang ^[26] studied the global existence of weak solutions of unsteady Prandtl equations under the favorable pressure gradient. For the unsteady compressible Prandtl equation, similar results are obtained in ^[3]. Recently, Xin, Zhang and Zhao ^[27] proposed a direct proof of the existence of global weak solutions of the Prandtl equation. The key content of this paper is that they have studied the uniqueness and regularity of weak solutions. This method can be applied to the compressible Prandtl equation.

Our main results are as follows:

Theorem 1.3. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Then, there exists a constant $C > 0$ depending only on $\varepsilon, X, u_{0}, P(\rho), k, m$ such that for any $(x, y)\in[\varepsilon, X]\times[0, +\infty),$

$\begin{align*} |\partial_{x}^{k}\partial_{y}^{m}u(x,y)|\leq C, \end{align*}$

where $X, \varepsilon$ are positive constants with $\varepsilon < X$ and $m, k$ are any positive integers.

Remarks 1.4. Our methods may be used to other related models. There are similar results for the magnetohydrodynamics boundary layer and the thermal boundary layer. This work will be more difficult due to the influence of temperature and the magnetic field.

Due to the degeneracy near the boundary $\psi = 0$ , the proof of the main result is divided into two parts, Theorem 1.5 and Theorem 1.6. This is similar to the result of the incompressible boundary layer, despite the fluid being compressible and the degeneracy near the boundary. Different from the incompressible case ^[23], we have no divergence-free conditions, which will bring new terms. It is one of the difficulties in this paper to deal with these terms. Now, we will briefly introduce our proof framework. First, we prove the following theorem in the domain $[\varepsilon, X]\times[0, Y_{1}]$ for a small $Y_{1}$ . The key ingredients of proof is that we employ interior priori estimates and the maximum principle developed by Krylov ^[10].

Theorem 1.5. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Then, there exists a small constant $Y_{1} > 0$ and a large constant $C > 0$ depending only on $\varepsilon, X, Y_{1}, u_{0}, P(\rho), k, m$ such that for any $(x, y)\in[\varepsilon, X]\times[0, Y_{1}],$

$\begin{align*} |\partial_{x}^{k}\partial_{y}^{m}u(x,y)|\leq C, \end{align*}$

where $X, \varepsilon$ are positive constants with $\varepsilon < X$ and $m, k$ are any positive integers.

Next, we prove the following theorem in the domain $[\varepsilon, X]\times[Y_{2}, +\infty)$ for a small positive constant $Y_{2}$ . The key of proof is that we prove (1.6) is a uniform parabolic equation in the domain $[\varepsilon, X]\times[Y_{2}, +\infty)$ in Section 4. Once we have (1.6) is a uniform parabolic equation, the global $C^{\infty}$ regularity of the solution is a direct result of interior Schauder estimates and classical parabolic regularity theory. The proof can be given similarly to the steady incompressible boundary layer. For the sake of simplicity of the paper, more details can be found in ^[23] and we omit it here.

Theorem 1.6. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Then, there exists a constant $Y_{0} > 0$ such that for any constant $Y_{2}\in(0, Y_{0})$ , there exists a constant $C > 0$ depending only on $\varepsilon, X, Y_{2}, u_{0}, P(\rho), k, m$ such that for any $(x, y)\in[\varepsilon, X]\times[Y_{2}, +\infty),$

$\begin{align*} |\partial_{x}^{k}\partial_{y}^{m}u(x,y)|\leq C, \end{align*}$

where $X, \varepsilon$ are positive constants with $\varepsilon < X$ and $m, k$ are any positive integers.

Therefore, Theorem 1.3 can be directly proven by combining Theorem 1.5 with Theorem 1.6.

The organization of this paper is as follows. In Section 2, we study lower order and higher order regularity estimates. In Section 3, we prove Theorem 1.5 in the domain near $y = 0$ by transforming back to the original coordinates $(x, y)$ . In Section 4, we prove (1.6) is a uniform parabolic equation by using the maximum principle and we also prove the Theorem 1.3.

2. Lower order and higher order regularity estimates

2.1. Lower order regularity estimates

In this subsection, we study the lower order regularity estimates using the standard interior a priori estimates developed by Krylov ^[10].

Lemma 2.1. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9)and the known function $\rho$ and $\partial_{x}P$ are smooth. Assume $0 < \varepsilon < X$ , then there exists some positive constants $\delta_{1} > 0$ and $C$ independent of $\psi$ such that for any $(x, \psi)\in[\varepsilon, X]\times[0, \delta_{1}],$

$\begin{align*} |\partial_{x}w(x,\psi)|\leq C\psi. \end{align*}$

Proof. Due to Lemma 2.1 in ^[5] (or Theorem 2.1.14 in ^[13]), there exists $\delta_{1} > 0$ for any $(x, \psi)\in[0, X]\times[0, \delta_{1}]$ , such that for some $\alpha\in(0, \frac{1}{2})$ and positive constants $m, M$ (we assume $\delta_{1} < 1$ ),

$\begin{align} |\partial_{x}w|\leq C\psi^{\frac{1}{2}+\alpha},\quad 0 < m < \partial_{\psi}w < M,\quad m\psi < w < M\psi. \end{align}$

(2.1)

By (1.6), we obtain

$\begin{align*} \partial_{x} \partial_{x} w-\sqrt{w} \partial_{\psi}^{2} \partial_{x} w = \frac{\left(\partial_{x} w\right)^{2}}{2 w}+2 \frac{\rho\partial_{x}P \partial_{x}w }{2 w}+\frac{\partial_{x}\rho}{\rho}\partial_{x}w+2\partial_{x}\left(\frac{\partial_{x}\rho}{\rho}\right)w-2 \partial_{x}[\rho\partial_{x}P]. \end{align*}$

Take a smooth cutoff function $0 \leq \phi(x) \leq 1$ in $[0, X]$ such that

$\begin{align*} \phi(x) = 1, x \in [\varepsilon,X],\quad \phi(x) = 0, x \in[0,\frac{\varepsilon}{2}], \end{align*}$

then

$\begin{align*} \begin{aligned} \partial_{x}\left[\partial_{x} w \phi(x)\right]&-\sqrt{w} \partial_{\psi}^{2}\left[\partial_{x} w \phi(x)\right]\\ & = \frac{\left(\partial_{x} w\right)^{2}}{2 w} \phi(x)+2 \frac{\rho\partial_{x}P \partial_{x}w }{2 w}\phi(x)+\frac{\partial_{x}\rho}{\rho}\partial_{x}w\phi(x)\\ &+2\partial_{x}\left(\frac{\partial_{x}\rho}{\rho}\right)w\phi(x) -2 \partial_{x}(\rho\partial_{x}P)\phi(x)+\partial_{x} w \partial_{x} \phi(x) : = \mathcal{W}. \end{aligned} \end{align*}$

Combining with (2.1), we know

$\begin{align} |\mathcal{W}| \leq C \psi^{2 \alpha}+C \psi^{\alpha-\frac{1}{2}}+C\psi^{\alpha+\frac{1}{2}}+C\psi+C \leq C \psi^{\alpha-\frac{1}{2}}. \end{align}$

(2.2)

We take $\varphi(\psi) = \mu_{1} \psi-\mu_{2} \psi^{1+\beta}$ with constants $\mu_{1}, \mu_{2}$ , then by (2.1) and (2.2), we get

$\begin{align*} \begin{aligned} \partial_{x}\left[\partial_{x} w \phi(x)-\varphi\right]-\sqrt{w} \partial_{\psi}^{2}\left[\partial_{x} w \phi(x)-\varphi\right] & \leq|\mathcal{W}|-\mu_{2} \sqrt{w} \beta(1+\beta) \psi^{\beta-1} \\ & \leq C \psi^{\alpha-\frac{1}{2}}-\mu_{2} \sqrt{m} \beta(1+\beta) \psi^{\beta-\frac{1}{2}}. \end{aligned} \end{align*}$

By taking $\mu_{2}$ sufficiently large and $\alpha = \beta$ , for $(x, \psi)\in(0, X] \times\left(0, \delta_{1}\right)$ , we have

$\begin{align*} \partial_{x}\left[\partial_{x} w \phi(x)-\varphi\right]-\sqrt{w} \partial_{\psi}^{2}\left[\partial_{x} w \phi(x)-\varphi\right] < 0. \end{align*}$

For any $\psi\in\left[0, \delta_{1}\right]$ , let $\mu_{1} \geq \mu_{2}$ , and we have

$\begin{align*} \left(\partial_{x} w \phi-\varphi\right)(0, \psi) \leq 0 , \end{align*}$

and take $\mu_{1}$ large enough depending on $M, \delta_{1}, \mu_{2}$ such that

$\begin{align*} \left(\partial_{x} w \phi-\varphi\right)\left(x, \delta_{1}\right)\leq M \delta_{1}^{\frac{1}{2}+\alpha}-\mu_{1} \delta_{1}+\mu_{2} \delta_{1}^{1+\beta} \leq 0 . \end{align*}$

Since $w(x, 0) = 0$ , we know that for any $x\in[0, X]$ ,

$\begin{align*} \left(\partial_{x} w \phi-\varphi\right)(x, 0) = 0. \end{align*}$

By the maximum principle, it holds in $[0, X] \times[0, \delta_{1}]$ that

$\begin{align*} \left(\partial_{x} w \phi-\varphi\right)(x, \psi) \leq 0. \end{align*}$

Let $\delta_{1}$ be chosen suitably small, for $(x, \psi)\in[\varepsilon, X] \times[0, \delta_{1}]$ , and we obtain

$\begin{align*} \partial_{x} w(x, \psi) \leq \mu_{1} \psi-\mu_{2} \psi^{1+\beta} \leq \frac{\mu_{1}}{2} \psi. \end{align*}$

Considering $-\partial_{x} w \phi-\varphi$ , the result $-\partial_{x} w \leq \frac{\mu_{1}}{2} \psi$ in $[\varepsilon, X] \times[0, \delta_{1}]$ can be proved similarly. This completes the proof of the lemma.

Lemma 2.2. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Assume $0 < \varepsilon < X$ , then there exists some positive constants $\delta_{2} > 0$ and $C$ independent of $\psi$ such that for any $(x, \psi)\in[\varepsilon, X]\times[0, \delta_{2}],$

$\begin{align*} |\partial_{\psi} \partial_{x} w(x, \psi)| \leq C, \quad|\partial_{x}^{2} w(x, \psi)| \leq C \psi^{-\frac{1}{2}}, \quad|\partial_{\psi}^{2} \partial_{x} w(x, \psi)| \leq C \psi^{-1}. \end{align*}$

Proof. From Lemma 2.1, there exists $\delta_{1} > 0$ such that for any $(x, \psi)\in[\frac{\varepsilon}{2}, X] \times[0, \delta_{1}],$

$\begin{align*} |\partial_{x} w(x, \psi)| \leq C \psi. \end{align*}$

Let $\Psi_{0} = \min \{\frac{2}{3} \delta_{1}, \frac{\varepsilon}{2}\}$ , for any $(x_{0}, \psi_{0}) \in[\varepsilon, X] \times(0, \Psi_{0}]$ , and we denote

$\begin{align*} \Omega = \bigl\{(x,\psi)|x_{0}-\psi_{0}^{\frac{3}{2}} \leq x \leq x_{0},\frac{1}{2} \psi_{0} \leq \psi \leq \frac{3}{2} \psi_{0}\bigr\}. \end{align*}$

By the definition of $\Psi_{0}$ , we know $\Omega\subseteq[\frac{\varepsilon}{2}, X] \times[0, \delta_{1}]$ , then it holds in $\Omega$ that

$\begin{align} |\partial_{x} w| \leq C \psi. \end{align}$

(2.3)

The following transformation $f$ is defined:

$\begin{align*} \begin{aligned} \Omega \rightarrow \widetilde{\Omega}: = [-1,0]_{\tilde{x}} \times[-\frac{1}{2}, \frac{1}{2}]_{\tilde{\psi}}, \quad (x, \psi) \mapsto(\tilde{x}, \tilde{\psi}), \end{aligned} \end{align*}$

where $x-x_{0} = \psi_{0}^{\frac{3}{2}} \tilde{x}, \psi-\psi_{0} = \psi_{0} \tilde{\psi}$ .

Since $\partial_{\tilde{x}} = \psi_{0}^{\frac{3}{2}}\partial_{x}, \partial_{\tilde{\psi}} = \psi_{0} \partial_{\psi}$ , it holds in $\Omega$ that

$\begin{align*} \partial_{\tilde{x}}\left(\psi_{0}^{-1} w\right)-\psi_{0}^{-\frac{1}{2}} \sqrt{w} \partial_{\tilde{\psi}}^{2}\left(\psi_{0}^{-1} w\right)-2\frac{\partial_{\tilde{x}}\rho}{\rho}(\psi_{0}^{-1}w) = -2 \rho\partial_{\tilde{x}}P \psi_{0}^{-1} . \end{align*}$

Combining with (2.1), we get $0 < c \leq\psi_{0}^{-\frac{1}{2}} \sqrt{w} \leq C, |\psi_{0}^{-1} w| \leq C$ , and for any $\widetilde{z}_{1}, \widetilde{z}_{2} \in \widetilde{\Omega}$ ,

$\begin{align*} \begin{aligned} |\psi_{0}^{-\frac{1}{2}} \sqrt{w}(\tilde{z}_{1})-\psi_{0}^{-\frac{1}{2}} \sqrt{w}(\tilde{z}_{2})| = \psi_{0}^{-\frac{1}{2}} \frac{\left|w\left(\tilde{z}_{1}\right)-w\left(\tilde{z}_{2}\right)\right|}{\sqrt{w}\left(\tilde{z}_{1}\right)+\sqrt{w}\left(\tilde{z}_{2}\right)} \leq C \frac{\psi_{0}\left|\tilde{z}_{1}-\tilde{z}_{2}\right|}{\psi_{0}} = C\left|\tilde{z}_{1}-\tilde{z}_{2}\right|. \end{aligned} \end{align*}$

This means that for any $\alpha \in(0, 1)$ , we have

$\begin{align*} |\psi_{0}^{-\frac{1}{2}}\sqrt{w}|_{\mathcal{C}^{\alpha}(\widetilde{\Omega})} \leq C. \end{align*}$

Since $P$ and $\rho$ are smooth, we have

$\begin{align*} |\rho^{-1}\partial_{\tilde{x}}\rho|_{\mathcal{C}^{0,1}([-1,0]_{\tilde{x}})}+|\rho\partial_{\tilde{x}}P\psi_{0}^{-1}|_{\mathcal{C}^{0,1}([-1,0]_{\tilde{x}})} \leq C . \end{align*}$

By standard interior priori estimates (see Theorem 8.11.1 in ^[10] or Proposition 2.3 in ^[23]), we have

$\begin{align} | w \psi_{0}^{-1}|_{\mathcal{C}^{\alpha}([-\frac{1}{2}, 0]_{\tilde{x}} \times[-\frac{1}{4}, \frac{1}{4}]_{\tilde{\psi}})}+|\partial_{\tilde{\psi}}^{2} w \psi_{0}^{-1}|_{\mathcal{C}^{\alpha}([-\frac{1}{2}, 0]_{\tilde{x}} \times[-\frac{1}{4}, \frac{1}{4}]_{\tilde{\psi}})} \leq C. \end{align}$

(2.4)

Let $f: = \partial_{x} w \psi_{0}^{-1}$ , which satisfies

$\begin{align*} \partial_{\tilde{x}} f-\frac{\sqrt{w}}{\psi_{0}^{\frac{1}{2}}} \partial_{\tilde{\psi}}^{2} f-\frac{\partial_{\tilde{\psi}}^{2} w}{2 \sqrt{w} \psi_{0}^{\frac{1}{2}}} f-2\frac{\partial_{\tilde{x}}\rho}{\rho}f = -2 \partial_{x}[\rho\partial_{\tilde{x}}P] \psi_{0}^{-1}+2\partial_{x}\left(\frac{\partial_{\tilde{x}}\rho}{\rho}\right)(\psi_{0}^{-1}w) . \end{align*}$

By (2.3), we have $|f| \leq C$ in $\widetilde{\Omega}$ . Due to

$\begin{align*} \big|\psi_{0}^{\frac{1}{2}}w^{-\frac{1}{2}}(\tilde{z}_{1})-\psi_{0}^{\frac{1}{2}}w^{-\frac{1}{2}}(\tilde{z}_{2})\big| = \psi_{0}^{\frac{1}{2}} \frac{\left|\frac{w(\tilde{z}_{1})-w(\tilde{z}_{2})}{w(\tilde{z}_{1}) w(\tilde{z}_{2})}\right|}{w^{-\frac{1}{2}}(\tilde{z}_{1})+w^{-\frac{1}{2}}(\tilde{z}_{2})} \leq C\left|\tilde{z}_{1}-\tilde{z}_{2}\right|, \end{align*}$

we have

$\begin{align} \big|\psi_{0}^{\frac{1}{2}}w^{-\frac{1}{2}}\big|_{\mathcal{C}^{\alpha}(\widetilde{\Omega})} \leq C. \end{align}$

(2.5)

Since

$\frac{\partial_{\tilde{\psi}}^{2} w}{2 \sqrt{w} \psi_{0}^{\frac{1}{2}}} = \partial_{\tilde{\psi}}^{2} w \psi_{0}^{-1} \frac{\psi_{0}^{\frac{1}{2}}}{2 \sqrt{w}},$

which along with (2.4) and (2.5) gives

$\begin{align*} \bigg|\frac{\partial_{\tilde{\psi}}^{2} w}{2 \sqrt{w} \psi_{0}^{\frac{1}{2}}}\bigg|_{\mathcal{C}^{\alpha}([-\frac{1}{2}, 0]_{\tilde{x}} \times[-\frac{1}{4}, \frac{1}{4}]_{\tilde{\psi}})} \leq C . \end{align*}$

As before, by (2.4) and the density $\rho$ and $P$ are smooth, via the standard interior a priori estimates, it yield that

$\begin{align*} |\partial_{\tilde{x}} f|_{L^{\infty}([-\frac{1}{4}, 0]_{\tilde{x}} \times[-\frac{1}{8}, \frac{1}{8}]_{\tilde{\psi}})}+|\partial_{\tilde{\psi}} f|_{L^{\infty}([-\frac{1}{4}, 0]_{\tilde{x}} \times[-\frac{1}{8}, \frac{1}{8}]_{\tilde{\psi}})}+|\partial_{\tilde{\psi}}^{2} f|_{L^{\infty}([-\frac{1}{4}, 0]_{\tilde{x}} \times[-\frac{1}{8}, \frac{1}{8}]_{\tilde{\psi}})} \leq C . \end{align*}$

Therefore, we obtain

$\begin{align*} |\partial_{x}^{2} w\left(x_{0}, \psi_{0}\right)| \leq C \psi_{0}^{-\frac{1}{2}}, \quad|\partial_{\psi} \partial_{x} w\left(x_{0}, \psi_{0}\right)| \leq C, \quad|\partial_{\psi}^{2} \partial_{x} w\left(x_{0}, \psi_{0}\right)| \leq C \psi_{0}^{-1}. \end{align*}$

This completes the proof of the lemma.

2.2. Higher order regularity estimates

In this subsection, we study the higher order regularity estimates using the maximum principle. The two main results of this subsection are Lemma 2.3 and Lemma 2.7.

Lemma 2.3. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Assume $0 < \varepsilon < X$ and $k \geq 2$ , then there exists some positive constants $\delta > 0$ and $C$ independent of $\psi$ such that for any $(x, \psi)\in[\varepsilon, X]\times[0, \delta],$

$\begin{align*} |\partial_{x}^{k} w| \leq C \psi, \quad|\partial_{\psi} \partial_{x}^{k} w| \leq C, \quad|\partial_{\psi}^{2} \partial_{x}^{k} w| \leq C \psi^{-1} . \end{align*}$

Proof. By Lemma 2.1 and Lemma 2.2, we may inductively assume that for $0 \leq j \leq k-1$ , there holds that in $\left[\frac{\varepsilon}{2}, X\right] \times\left[0, \delta_{3}\right]$ (assume $\delta_{3}\ll1$ ),

$\begin{align} |\partial_{\psi} \partial_{x}^{j} w| \leq C,\quad|\partial_{\psi}^{2} \partial_{x}^{j} w| \leq C \psi^{-1},\quad|\partial_{x}^{j} w| \leq C \psi,\quad|\partial_{x}^{j} \sqrt{w}| \leq C \psi^{\frac{1}{2}},\quad|\partial_{x}^{k} w| \leq C \psi^{-\frac{1}{2}}. \end{align}$

(2.6)

We will prove that there exists $\delta_{4} < \delta_{3}$ so that in $[\varepsilon, X] \times[0, \delta_{4}]$ ,

$\begin{align} |\partial_{\psi} \partial_{x}^{k} w| \leq C,\quad|\partial_{\psi}^{2} \partial_{x}^{k} w| \leq C \psi^{-1},\quad|\partial_{x}^{k} w| \leq C \psi,\quad|\partial_{x}^{k} \sqrt{w}| \leq C \psi^{\frac{1}{2}},\quad|\partial_{x}^{k+1} w| \leq C \psi^{-\frac{1}{2}}. \end{align}$

(2.7)

The above results are deduced from the following Lemma 2.4, Lemma 2.5 and Lemma 2.6.

Lemma 2.4. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Assume that (2.6) holds, then there is a positive constant $M_{1}$ for any $(x, \psi)\in\left[\frac{7 \varepsilon}{8}, X\right] \times\left[0, \delta_{3}\right]$ and $0 < \beta \ll 1$ ,

$\begin{align*} |\partial_{x}^{k} w| < M_{1} \psi^{1-\beta}, \quad|\partial_{x}^{k} \sqrt{w}| \leq M_{1} \psi^{\frac{1}{2}-\beta}. \end{align*}$

Proof. Take a smooth cutoff function $0 \leq \phi(x) \leq 1$ in $[0, X]$ such that

$\begin{align*} \phi(x) = 1, x \in [\frac{7\varepsilon}{8},X],\quad \phi(x) = 0, x \in[0,\frac{5\varepsilon}{8}]. \end{align*}$

As in ^[23], fix any $h < \frac{\varepsilon}{8}$ . Set

$\Omega = \left\{(x,\psi)|0 < x\leq X, 0 < \psi < \delta_{3}\right\},$

and let

(ⅰ) $f = \frac{\partial_{x}^{k-1} w(x-h, \psi)-\partial_{x}^{k-1} w(x, \psi)}{-h} \phi+M \psi \ln \psi,$ $(x, \psi)\in[\frac{5 \varepsilon}{8}, X]\times [0, +\infty)$ ,

(ⅱ) $f = M \psi \ln \psi,$ $(x, \psi)\in[0, \frac{5 \varepsilon}{8})\times[\psi, +\infty),$

so we get $f(x, 0) = 0$ , $f(0, \psi) \leq 0$ . We know

$f\left(x, \delta_{3}\right) \leq C\left(\delta_{3}\right)^{-\frac{1}{2}}+M \delta_{3} \ln \delta_{3} \leq 0,$

where $M$ is large enough. Then, by choosing the appropriate $M$ , we know that the positive maximum of $f$ cannot be achieved in the interior. Finally, the lemma can be proven by the arbitrariness of $h$ .

Assume that there exists a point

$p_{0} = (x_{0}, \psi_{0}) \in \Omega,$

such that

$f\left(p_{0}\right) = \max \limits_{\bar{\Omega}} f > 0.$

It is easy to know that

$x_{0} > \frac{5 \varepsilon}{8},\qquad \partial_{x}^{k-1} w(x_{0}-h, \psi_{0}) < \partial_{x}^{k-1} w(x_{0}, \psi_{0}).$

By (2.1), denote $\xi = \sqrt{m}$ , we have

$\begin{align} -\sqrt{w} \partial_{\psi}^{2}(M \psi \ln \psi) = -M \sqrt{w} \psi^{-1} \leq-\xi M \psi^{-\frac{1}{2}}. \end{align}$

(2.8)

By (1.6), a direct calculation gives

$\begin{align*} \begin{aligned} \partial_{x} \partial_{x}^{k-1} w-&\sqrt{w} \partial_{\psi}^{2} \partial_{x}^{k-1} w\\ & = -2 \partial_{x}^{k-1}(\rho\partial_{x}P)+\sum\limits_{m = 1}^{k-2} C_{k-1}^{m}\left(\partial_{x}^{k-1-m} \sqrt{w}\right) \partial_{\psi}^{2} \partial_{x}^{m} w+\left(\partial_{x}^{k-1} \sqrt{w}\right) \partial_{\psi}^{2} w \\ &\quad+2\sum\limits_{m = 0}^{k-1} C_{k-1}^{m}\partial_{x}^{k-1-m}\left(\frac{\partial_{x}\rho}{\rho}\right)\partial_{x}^{m}w\\ & = -2 \partial_{x}^{k-1}(\rho\partial_{x}P)+\sum\limits_{m = 1}^{k-2} C_{k-1}^{m}\left(\partial_{x}^{k-1-m} \sqrt{w}\right) \partial_{\psi}^{2} \partial_{x}^{m} w+\frac{\partial_{x}^{k-1} w}{2 \sqrt{w}} \frac{\partial_{x} w}{\sqrt{w}} \\ &\quad+\left(\frac{\partial_{x}^{k-1} w}{2 \sqrt{w}}\right) \frac{2\rho\partial_{x}P}{\sqrt{w}}-\left(\frac{\partial_{x}^{k-1} w}{2 \sqrt{w}}\right)\frac{2\frac{\partial_{x}\rho}{\rho}w}{\sqrt{w}}+2\sum\limits_{m = 0}^{k-1} C_{k-1}^{m}\partial_{x}^{k-1-m}\left(\frac{\partial_{x}\rho}{\rho}\right)\partial_{x}^{m}w\\ &\quad+ \sum\limits_{m = 0}^{k-2} C_{k-2}^{m} \partial_{\psi}^{2} w \partial_{x}^{m+1} w \partial_{x}^{k-2-m} \frac{1}{2 \sqrt{w}}\\ &: = \sum\limits_{i = 1}^{4}I_{i} \end{aligned} \end{align*}$

and

$\begin{align*} \begin{aligned} I_{1} & = -2 \partial_{x}^{k-1}(\rho\partial_{x}P)+\sum\limits_{m = 1}^{k-2} C_{k-1}^{m}\left(\partial_{x}^{k-1-m} \sqrt{w}\right) \partial_{\psi}^{2} \partial_{x}^{m} w+\frac{\partial_{x}^{k-1} w}{2 \sqrt{w}} \frac{\partial_{x} w}{\sqrt{w}}, \\ I_{2} & = \frac{\rho\partial_{x}P}{w}\partial_{x}^{k-1} w, \\ I_{3} & = -\frac{\partial_{x}\rho}{\rho}\partial_{x}^{k-1}w+2\sum\limits_{m = 0}^{k-1} C_{k-1}^{m}\partial_{x}^{k-1-m}\left(\frac{\partial_{x}\rho}{\rho}\right)\partial_{x}^{m}w,\\ I_{4}& = \sum\limits_{m = 0}^{k-2} C_{k-2}^{m} \partial_{\psi}^{2} w \partial_{x}^{m+1} w \partial_{x}^{k-2-m} \frac{1}{2 \sqrt{w}}. \end{aligned} \end{align*}$

For $x \geq \frac{5 \varepsilon}{8}$ , we consider the following equality

$\begin{align} \partial_{x} f_{1}-\sqrt{w\left(p_{1}\right)} \partial_{\psi}^{2} f_{1} = \frac{\sqrt{w(p_{1})}-\sqrt{w(p)}}{-h} \partial_{\psi}^{2} \partial_{x}^{k-1} w(p)+\sum\limits_{i = 1}^{4} \frac{1}{-h}\left(I_{i}\left(p_{1}\right)-I_{i}(p)\right), \end{align}$

(2.9)

where

$f_{1} = \frac{1}{-h}(\partial_{x}^{k-1} w\left(p_{1}\right)-\partial_{x}^{k-1} w(p)),$

with $p_{1} = (x-h, \psi), p = (x, \psi)$ .

For any $x \geq \frac{5 \varepsilon}{8}$ , by (2.6), it is easy to conclude that

$\begin{align} \begin{aligned} &\left|\frac{1}{-h}(\sqrt{w}(p_{1})-\sqrt{w}(p)) \partial_{\psi}^{2} \partial_{x}^{k-1} w(p)\right| \leq C \psi^{-\frac{1}{2}}, \\ &\left|\frac{1}{-h}(I_{1}(p_{1})-I_{1}(p))\right| \leq C \psi^{-\frac{1}{2}}, \\ &\left|\sum\limits_{i = 3}^{4}\frac{1}{-h}(I_{i}(p_{1})-I_{i }(p))\right| \leq C \psi^{-\frac{1}{2}}, \end{aligned} \end{align}$

(2.10)

where $C$ is dependent on the parameter $h$ .

Since

$\begin{align*} \frac{1}{-h}(I_{2}(p_{1})-I_{2}(p)) = f_{1} \cdot\big[\frac{\rho\partial_{x}P}{w} (p_{1})\big]+\partial_{x}^{k-1} w(p) \frac{1}{-h}\big[\frac{\rho\partial_{x}P}{w} (p_{1})-\frac{\rho\partial_{x}P}{w} (p)\big], \end{align*}$

combining with (2.6), $f_{1}(p_{0}) > 0$ and $\partial_{x}P\leq 0$ , it holds at $p = p_{0}$ that

$\begin{align} \frac{1}{-h}(I_{2}\left(p_{1}\right)-I_{2}(p_{0})) \leq C . \end{align}$

(2.11)

Summing up (2.10) and (2.11), we conclude that at $p = p_{0}$ ,

$\begin{align*} \partial_{x} f_{1}-\sqrt{w} \partial_{\psi}^{2} f_{1} \leq C_{0} \psi^{-\frac{1}{2}} . \end{align*}$

This along with (2.8) shows that for $x \geq \frac{5 \varepsilon}{8}$ , it holds at $p = p_{0}$ that

$\begin{align} \partial_{x} f-\sqrt{w} \partial_{\psi}^{2} f \leq C \psi^{-\frac{1}{2}}-\xi M \psi^{-\frac{1}{2}} . \end{align}$

(2.12)

By taking $M$ large enough, we have $\partial_{x} f\left(p_{0}\right)-\sqrt{w} \partial_{\psi}^{2} f\left(p_{0}\right) < 0$ . By the definition of $p_{0}$ , we obtain

$\begin{align*} \partial_{x} f\left(p_{0}\right)-\sqrt{w} \partial_{\psi}^{2} f\left(p_{0}\right) \geq 0, \end{align*}$

which leads to a contradiction. Therefore, for $M$ chosen as above and independent of $h$ , we have

$\max\limits _{\bar{\Omega}} f \leq 0.$

We can similarly prove that $\min _{\bar{\Omega}} f \geq 0$ by replacing $M \psi \ln \psi$ in $f$ with $-M \psi \ln \psi$ . By the arbitrariness of $h$ , for any $(x, \psi)\in(\frac{7\varepsilon}{8}, X] \times(0, \delta_{3}]$ we have

$\begin{align*} |\partial_{x}^{k} w| \leq-M \psi \ln \psi. \end{align*}$

Due to

$\begin{align} 2 \sqrt{w} \partial_{x}^{k} \sqrt{w}+\sum\limits_{m = 1}^{k-1} C_{k}^{m}(\partial_{x}^{m} \sqrt{w} \partial_{x}^{k-m} \sqrt{w}) = \partial_{x}^{k}(\sqrt{w} \sqrt{w}) = \partial_{x}^{k} w, \end{align}$

(2.13)

which along with (2.6) shows that in $(\frac{7}{8} \varepsilon, X] \times(0, \delta_{3}]$ ,

$\begin{align*} |\sqrt{w} \partial_{x}^{k} \sqrt{w}| \leq-C \psi \ln \psi . \end{align*}$

Lemma 2.5. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Assume that (2.6) holds, then for any $(x, \psi)\in[\frac{15}{16} \varepsilon, X] \times[0, \delta_{3}]$ ,

$\begin{align*} |\partial_{x}^{k} w| \leq C \psi, \quad|\partial_{x}^{k} \sqrt{w}| \leq C \psi^{\frac{1}{2}} . \end{align*}$

Proof. Take a smooth cutoff function $\phi(x)$ so that

$\begin{align*} \phi(x) = 1, x \in [\frac{15\varepsilon}{16},X],\quad \phi(x) = 0, x \in[0,\frac{7\varepsilon}{8}]. \end{align*}$

Set

$f = \partial_{x}^{k} w \phi-\mu_{1} \psi+\mu_{2} \psi^{\frac{3}{2}-\beta}$

with constants $\mu_{1}, \mu_{2}$ . Let $\beta$ be small enough in Lemma 2.4. Then it holds in $[\frac{7 \varepsilon}{8}, X] \times[0, \delta_{3}]$ that

$\begin{align} |\partial_{x}^{k} w| \leq C \psi^{1-\beta}, \quad|\partial_{x}^{k} \sqrt{w}| \leq C \psi^{\frac{1}{2}-\beta}. \end{align}$

(2.14)

We denote

$\Omega = \left\{(x,\psi)|0 < x\leq X ,0 < \psi < \delta_{3}\right\}.$

As in ^[23], we have $f(x, 0) = 0$ , $f(0, \psi) \leq 0$ and $f(x, \delta_{3}) \leq 0$ by taking $\mu_{1}$ large depending on $\mu_{2}$ . We claim that the maximum of $f$ cannot be achieved in the interior.

By (1.6), we have

$\begin{align*} \begin{aligned} \partial_{x} \partial_{x}^{k} w-&\sqrt{w} \partial_{\psi}^{2} \partial_{x}^{k} w\\ & = -2 \partial_{x}^{k}(\rho\partial_{x}P)+\sum\limits_{m = 0}^{k-1} C_{k}^{m}(\partial_{x}^{k-m} \sqrt{w}) \partial_{\psi}^{2} \partial_{x}^{m}w +2\sum\limits_{m = 0}^{k} C_{k}^{m}\partial_{x}^{k-m}\left(\frac{\partial_{x}\rho}{\rho}\right)\partial_{x}^{m}w, \end{aligned} \end{align*}$

and

$\begin{align*} \partial_{\psi}^{2} \partial_{x}^{m} w = \partial_{x}^{m} \partial_{\psi}^{2} w = \partial_{x}^{m}\left(\frac{\partial_{x} w}{\sqrt{w}}+\frac{2\rho\partial_{x}P}{\sqrt{w}}-\frac{2\partial_{x}\rho}{\rho}\sqrt{w} \right) . \end{align*}$

For any $x \geq \frac{7 \varepsilon}{8}$ , $0 \leq j \leq k-1$ and $0 \leq m \leq k-1$ , from (2.6) and (2.14), we get

$\begin{align*} |\partial_{x}^{j} w| \leq C \psi, \quad|\partial_{x}^{k} w| \leq C \psi^{1-\beta},\quad |\partial_{x}^{k-m} \sqrt{w}| \leq C \psi^{\frac{1}{2}-\beta}. \end{align*}$

Then let $\beta\ll\frac{1}{2}$ , for $0 \leq m \leq k-1$ and $x \geq \frac{7 \varepsilon}{8}$ , we obtain

$\begin{align*} |\partial_{\psi}^{2} \partial_{x}^{m} w| \leq C \psi^{\frac{1}{2}-\beta}+C \psi^{-\frac{1}{2}}+C \psi^{\frac{1}{2}-\beta}\leq C \psi^{-\frac{1}{2}}. \end{align*}$

Therefore, we conclude that for $x \geq \frac{7 \varepsilon}{8}$ ,

$\begin{align*} \partial_{x} \partial_{x}^{k} w-\sqrt{w} \partial_{\psi}^{2} \partial_{x}^{k} w \leq C+C \psi^{-\beta}+C\psi^{1-\beta}\leq C \psi^{-\beta}. \end{align*}$

By the above inequality and (2.1), it holds at $p = p_{0}$ that

$\begin{align*} \begin{aligned} \partial_{x} f-\sqrt{w} \partial_{\psi}^{2} f& = \partial_{x} \partial_{x}^{k} w-\sqrt{w} \partial_{\psi}^{2} \partial_{x}^{k} w+\partial_{x}^{k}w\partial_{x}\phi-\sqrt{w} \partial_{\psi}^{2}(-\mu_{1} \psi+\mu_{2} \psi^{\frac{3}{2}-\beta})\\& \leq C_{2} \psi^{-\beta}-\xi \mu_{2} \psi^{-\beta}, \end{aligned} \end{align*}$

where $\xi = \left(\frac{3}{2}-\beta\right)\left(\frac{1}{2}-\beta\right) \sqrt{m} > 0$ . Then we have $\partial_{x} f-\sqrt{w} \partial_{\psi}^{2} f < 0$ in $\Omega$ by taking $\mu_{2}$ large depending on $C_{2}$ . This means that the maximum of $f$ cannot be achieved in the interior. Therefore, we have

$\max \limits_{\bar{\Omega}} f \leq 0.$

In the same way, we can prove that

$\max\limits _{\bar{\Omega}}-\partial_{x}^{k} w \phi-\mu_{1} \psi+\mu_{2} \psi^{\frac{3}{2}-\beta} \leq 0.$

So, for any $(x, \psi)\in[\frac{15}{16} \varepsilon, X] \times[0, \delta_{3}]$ , we have

$\begin{align*} |\partial_{x}^{k} w| \leq \mu_{1} \psi-\mu_{2} \psi^{\frac{3}{2}-\beta} \leq \mu_{1} \psi. \end{align*}$

Combining with (2.6) and (2.13), it holds in $[\frac{15}{16} \varepsilon, X] \times[0, \delta_{3}]$ that

$\begin{align*} |\partial_{x}^{k} \sqrt{w}| \leq C \psi^{\frac{1}{2}}. \end{align*}$

This completes the proof of the lemma.

Lemma 2.6. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Assume that (2.6) holds, then for any $(x, \psi)\in[\varepsilon, X] \times[0, \delta_{4}]$ ,

$\begin{align*} |\partial_{\psi} \partial_{x}^{k} w| \leq C, \quad|\partial_{\psi}^{2} \partial_{x}^{k} w| \leq C \psi^{-1}, \quad|\partial_{x}^{k+1} w| \leq C \psi^{-\frac{1}{2}}. \end{align*}$

Proof. By Lemma 2.5 and (2.6), for any $(x, \psi)\in[\frac{15}{16} \varepsilon, X] \times[0, \delta_{3}]$ ,

$\begin{align} |\partial_{x}^{j} w| \leq C \psi, \quad|\partial_{x}^{j} \sqrt{w}| \leq C \psi^{\frac{1}{2}},\quad 0 \leq j \leq k. \end{align}$

(2.15)

Set $\Psi_{0} = \min \{\frac{2}{3} \delta_{3}, \frac{\varepsilon}{16}\}$ , for $(x_{0}, \psi_{0}) \in[\varepsilon, X] \times(0, \Psi_{0}]$ , we denote

$\begin{align*} \Omega = \bigl\{(x,\psi)|x_{0}-\psi_{0}^{\frac{3}{2}} \leq x \leq x_{0},\frac{1}{2} \psi_{0} \leq \psi \leq \frac{3}{2} \psi_{0}\bigr\}. \end{align*}$

A direct calculation gives

$\begin{align*} \begin{aligned} \partial_{x} \partial_{x}^{k} w-\sqrt{w} \partial_{\psi}^{2} \partial_{x}^{k} w = &-2 \partial_{x}^{k}(\rho\partial_{x}P)+\partial_{x}^{k} \sqrt{w} \partial_{\psi}^{2} w+\sum\limits_{m = 1}^{k-2} C_{k}^{m}\left(\partial_{x}^{k-m} \sqrt{w}\right) \partial_{\psi}^{2} \partial_{x}^{m} w \\ &+C_{k}^{k-1} \frac{\partial_{x} w}{2 \sqrt{w}} \partial_{\psi}^{2} \partial_{x}^{k-1} w+2\sum\limits_{m = 0}^{k} C_{k}^{m}\partial_{x}^{k-m}\left(\frac{\partial_{x}\rho}{\rho}\right)\partial_{x}^{m}w. \end{aligned} \end{align*}$

By (1.6), we obtain

$\begin{align*} \begin{aligned} \partial_{\psi}^{2} \partial_{x}^{m} w & = \partial_{x}^{m} \partial_{\psi}^{2} w\\ & = \partial_{x}^{m}\left(\frac{\partial_{x} w}{\sqrt{w}}+\frac{2\rho\partial_{x}P}{\sqrt{w}}-2\frac{\partial_{x}\rho}{\rho}\sqrt{w}\right) \\ & = \frac{\partial_{x}^{m+1} w}{\sqrt{w}}+\sum\limits_{l = 1}^{m} C_{m}^{l} \partial_{x}^{m-l+1} w \partial_{x}^{l} \frac{1}{\sqrt{w}}+\partial_{x}^{m}\left(\frac{2\rho\partial_{x}P}{\sqrt{w}}\right)-\partial_{x}^{m}\left(2\frac{\partial_{x}\rho}{\rho}\sqrt{w}\right), \end{aligned} \end{align*}$

and

$\begin{align*} \partial_{x}^{k} \sqrt{w} = \partial_{x}^{k-1} \frac{\partial_{x} w}{2 \sqrt{w}} = \frac{\partial_{x}^{k} w}{2 \sqrt{w}}+\sum\limits_{l = 1}^{k-1} C_{k-1}^{l} \partial_{x}^{k-1-l+1} w \partial_{x}^{l} \frac{1}{2 \sqrt{w}}, \end{align*}$

then

$\begin{align*} \begin{aligned} \partial_{x} \partial_{x}^{k} w-&\sqrt{w} \partial_{\psi}^{2} \partial_{x}^{k} w\\ = &-2 \partial_{x}^{k}(\rho\partial_{x}P)+\sum\limits_{m = 1}^{k-2} C_{k}^{m} (\partial_{x}^{k-m} \sqrt{w}) \partial_{\psi}^{2} \partial_{x}^{m} w \\ &+\frac{\partial_{x}^{k} w}{2 \sqrt{w}} \partial_{\psi}^{2} w+\sum\limits_{l = 1}^{k-1} C_{k-1}^{l} \partial_{x}^{k-1-l+1} w\partial_{x}^{l} \left(\frac{1}{2 \sqrt{w}}\right) \partial_{\psi}^{2} w \\ &+C_{k}^{k-1} \frac{\partial_{x} w \partial_{x}^{k} w}{2 w}+2\sum\limits_{m = 0}^{k} C_{k}^{m}\partial_{x}^{k-m}\left(\frac{\partial_{x}\rho}{\rho}\right)\partial_{x}^{m}w\\ &+C_{k}^{k-1} \frac{\partial_{x} w}{2 \sqrt{w}}\left[\sum\limits_{l = 1}^{k-1} C_{k-1}^{l} \partial_{x}^{k-l} w \partial_{x}^{l} \frac{1}{\sqrt{w}}+\partial_{x}^{k-1}\left(\frac{2\rho\partial_{x}P}{\sqrt{w}} \right)-\partial_{x}^{k-1}\left(2\frac{\partial_{x}\rho}{\rho}\sqrt{w}\right)\right]. \end{aligned} \end{align*}$

The following transformation $f$ is defined:

where $x-x_{0} = \psi_{0}^{\frac{3}{2}} \tilde{x}, \psi-\psi_{0} = \psi_{0} \tilde{\psi}$ .

Let $f = \partial_{x}^{k} w \psi_{0}^{-1}$ , we get

$\begin{align*} \begin{aligned} \partial_{\tilde{x}} f-&\frac{\sqrt{w}}{\psi_{0}^{\frac{1}{2}}} \partial_{\tilde{\psi}}^{2} f-\frac{1}{2 \sqrt{w}} \partial_{\psi}^{2} w \psi_{0}^{\frac{3}{2}}f-\frac{\partial_{x} w}{2 w} \psi_{0}^{\frac{3}{2}} f\\ & = -2\psi_{0}^{\frac{1}{2}} \partial_{x}^{k}(\rho\partial_{x}P)+\psi_{0}^{\frac{1}{2}}\sum\limits_{m = 1}^{k-2} C_{k}^{m} (\partial_{x}^{k-m} \sqrt{w}) \partial_{\psi}^{2} \partial_{x}^{m} w \\ &\quad+\psi_{0}^{\frac{1}{2}}\sum\limits_{l = 1}^{k-1} C_{k-1}^{l} \partial_{x}^{k-l} w\left(\partial_{x}^{l} \frac{1}{2 \sqrt{w}}\right) \partial_{\psi}^{2} w \\ &\quad+2\psi_{0}^{\frac{1}{2}}\sum\limits_{m = 0}^{k} C_{k}^{m}\partial_{x}^{k-m}\left(\frac{\partial_{x}\rho}{\rho}\right)\partial_{x}^{m}w\\ &\quad+\psi_{0}^{\frac{1}{2}}\frac{\partial_{x} w}{2 \sqrt{w}}\left[\sum\limits_{l = 1}^{k-1} C_{k-1}^{l} \partial_{x}^{k-l} w \partial_{x}^{l} \frac{1}{\sqrt{w}}+\partial_{x}^{k-1}\left(\frac{2\rho\partial_{x}P}{\sqrt{w}} \right)-\partial_{x}^{k-1}\left(2\frac{\partial_{x}\rho}{\rho}\sqrt{w}\right)\right]\\ &: = F. \end{aligned} \end{align*}$

From the proof of Lemma 2.2 and Lemma 2.6, we know that in $\widetilde{\Omega}$ for $\alpha \in(0, 1)$ ,

$\begin{align*} |f|\leq C, \quad 0 < c \leq \psi_{0}^{-\frac{1}{2}}\sqrt{w} \leq C, \quad|\psi_{0}^{-\frac{1}{2}}\sqrt{w}|_{\mathcal{C}^{\alpha}(\widetilde{\Omega})} \leq C . \end{align*}$

By (2.6), (2.15) and the equality

$\begin{align*} \begin{aligned} \partial_{\psi}\left(\partial_{\psi}^{2} \partial_{x}^{m} w\right) = & \frac{\partial_{\psi} \partial_{x}^{m+1} w}{\sqrt{w}}-\frac{\partial_{\psi} w \partial_{x}^{m+1} w}{2(\sqrt{w})^{3}}+\sum\limits_{l = 1}^{m} C_{m}^{l} \partial_{x}^{m-l+1} \partial_{\psi} w \partial_{x}^{l} \frac{1}{\sqrt{w}} \\ &+\sum\limits_{l = 1}^{m} C_{m}^{l} \partial_{x}^{m-l+1} w \partial_{x}^{l} \frac{\partial_{\psi} w}{-2(\sqrt{w})^{3}}+\partial_{x}^{m}\left(\frac{\rho\partial_{x}P\partial_{\psi} w}{-(\sqrt{w})^{3}} \right)-\partial_{x}^{m}\left(\frac{\partial_{x}\rho}{\rho}\frac{\partial_{\psi}w}{\sqrt{w}}\right), \end{aligned} \end{align*}$

we can conclude that for $j \leq k-1$ and $m \leq k-2$ ,

$\begin{align*} \big|\nabla_{\tilde{x}, \tilde{\psi}} \partial_{x}^{j} \sqrt{w}\big| \leq C \psi_{0}^{\frac{1}{2}}, \quad\big|\nabla_{\tilde{x}, \tilde{\psi}} \partial_{x}^{j}\big(\frac{1}{\sqrt{w}}\big)\big| \leq C \psi_{0}^{-\frac{1}{2}}, \quad\big|\nabla_{\tilde{x}, \tilde{\psi}} \partial_{\psi}^{2} \partial_{x}^{m} w\big | \leq C \psi_{0}^{-\frac{1}{2}}. \end{align*}$

Combining (2.4) with (2.5), we can obtain

$\begin{align*} |\frac{1}{2 \sqrt{w}} \partial_{\psi}^{2} w \psi_{0}^{\frac{3}{2}}+\frac{\partial_{x} w}{2 w} \psi_{0}^{\frac{3}{2}}|_{\mathcal{C}^{\alpha}(\widetilde{\Omega})}+|F|_{\mathcal{C}^{\alpha}(\widetilde{\Omega})} \leq C . \end{align*}$

By the standard interior priori estimates, we obtain

Therefore, this means that

$\begin{align*} |\partial_{x}^{k+1} w\left(x_{0}, \psi_{0}\right)| \leq C \psi_{0}^{-\frac{1}{2}}, \quad|\partial_{\psi} \partial_{x}^{k} w\left(x_{0}, \psi_{0}\right)| \leq C, \quad|\partial_{\psi}^{2} \partial_{x}^{k} w\left(x_{0}, \psi_{0}\right)| \leq C \psi_{0}^{-1} . \end{align*}$

Since $\left(x_{0}, \psi_{0}\right)$ is arbitrary, this completes the proof of the lemma.

Lemma 2.7. If $u$ is a solution for equation (1.1) in Theorem 1.1, assume $u_{0}$ satisfies the condition (1.9) and the known function $\rho$ and $\partial_{x}P$ are smooth. Assume $0 < \varepsilon < X$ and integer $m, k \geq 0$ , then there exists a positive constant $\delta > 0$ such that for any $(x, \psi)\in[\varepsilon, X]\times[0, \delta],$

$\begin{align} |\partial_{\psi}^{m} \partial_{x}^{k} w| \leq C \psi^{1-m}. \end{align}$

(2.16)

Proof. From Lemma 2.1, (2.1), Lemma 2.2 and Lemma 2.3, a direct calculation can prove that

$\begin{align*} \big|\partial_{x}^{k} \frac{1}{\sqrt{w}}\big| \leq C \psi^{-\frac{1}{2}}, \quad\big|\partial_{x}^{k} \partial_{\psi} \frac{1}{\sqrt{w}}\big| \leq C \psi^{-\frac{3}{2}}, \quad\big|\partial_{x}^{k} \partial_{\psi}^{2} \frac{1}{\sqrt{w}}\big| \leq C \psi^{-\frac{5}{2}} , \end{align*}$

and (2.16) holds for $m = 0, 1, 2$ . Then for $0 \leq m \leq j$ with $j \geq 1$ , we inductively assume that

$\begin{align} |\partial_{\psi}^{m} \partial_{x}^{k} w| \leq C \psi^{1-m},\quad \big|\partial_{x}^{k} \partial_{\psi}^{m} \frac{1}{\sqrt{w}}\big| \leq C \psi^{-\frac{1}{2}-m}. \end{align}$

(2.17)

In the next part, we will prove that (2.17) still holds for $m = j+1$ .

By (1.6), we obtain

$\begin{align*} \begin{aligned} \partial_{\psi}^{j+1} \partial_{x}^{k} w & = \partial_{\psi}^{j-1} \partial_{x}^{k} \partial_{\psi}^{2} w\\& = \partial_{x}^{k} \partial_{\psi}^{j-1}\left(\frac{\partial_{x} w}{\sqrt{w}}+\frac{2\rho\partial_{x}P}{\sqrt{w}} -2\frac{\partial_{x}\rho}{\rho}\frac{w}{\sqrt{w}}\right) \\ & = \partial_{x}^{k}\left(\sum\limits_{i = 0}^{j-1} C_{j-1}^{i} \partial_{\psi}^{j-1-i} \partial_{x} w \partial_{\psi}^{i} \frac{1}{\sqrt{w}}+2 \rho\partial_{x}P \partial_{\psi}^{j-1} \frac{1}{\sqrt{w}}-2\frac{\partial_{x}\rho}{\rho} \sum\limits_{i = 0}^{j-1} C_{j-1}^{i} \partial_{\psi}^{j-1-i} w \partial_{\psi}^{i} \frac{1}{\sqrt{w}}\right). \end{aligned} \end{align*}$

Combining with (2.17), we get

$\begin{align} |\partial_{\psi}^{j+1} \partial_{x}^{k} w| \leq C \psi^{\frac{3}{2}-j}+ C \psi^{\frac{1}{2}-j}+ C \psi^{\frac{3}{2}-j}\leq C \psi^{\frac{1}{2}-j} . \end{align}$

(2.18)

By straight calculations, we get

$\begin{align*} \begin{aligned} 0& = \partial_{x}^{k} \partial_{\psi}^{j+1}\bigg(\frac{1}{\sqrt{w}} \frac{1}{\sqrt{w}} w\bigg) \\ & = \partial_{x}^{k}\bigg[2 \sqrt{w} \partial_{\psi}^{j+1} \frac{1}{\sqrt{w}}+\sum\limits_{i = 1}^{j} \sum\limits_{l = 0}^{j+1-i} C_{j+1}^{i} C_{j+1-i}^{l}\left(\partial_{\psi}^{i} \frac{1}{\sqrt{w}}\right)\left(\partial_{\psi}^{l} \frac{1}{\sqrt{w}}\right) \partial_{\psi}^{j+1-l-i} w\\ &\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\quad +\sum\limits_{l = 0}^{j} C_{j+1}^{l} \frac{1}{\sqrt{w}}\left(\partial_{\psi}^{l} \frac{1}{\sqrt{w}}\right) \partial_{\psi}^{j+1-l} w\bigg]. \end{aligned} \end{align*}$

Combining the above equality with (2.17), we can conclude that

$\begin{align*} \big|\partial_{x}^{k} \partial_{\psi}^{j+1} \frac{1}{\sqrt{w}}\big| \leq C \psi^{-\frac{3}{2}-j}. \end{align*}$

This completes the proof of the lemma.

3. Proof of Theorem 1.5

In this section, we will prove the regularity of the solution $u$ in the domain

$\left\{(x,\psi)|\varepsilon\leq x\leq X, 0\leq y \leq Y_{1}\right\}.$

Proof of Theorem 1.5:

Proof. For the convenience of proof, we denote

$\begin{align*} (\tilde{x}, \psi) = \left(x, \int_{0}^{y} \tilde{u} d y\right) . \end{align*}$

A direct calculation gives (see P13 in ^[23])

$\begin{align*} \begin{aligned} \partial_{y} = \sqrt{w} \partial_{\psi}, \quad \partial_{x} = \partial_{\tilde{x}}+\partial_{x} \psi(x, y) \partial_{\psi}, \quad \partial_{x} \psi = \frac{1}{2} \sqrt{w} \int_{0}^{\psi} w^{-\frac{3}{2}} \partial_{\tilde{x}} w d \psi . \end{aligned} \end{align*}$

By (2.1) and Lemma 2.3, we have $|\partial_{x} \psi| \leq C \psi$ . Due to $\partial_{y} = \sqrt{w} \partial_{\psi}$ , we obtain

$\begin{align*} \begin{aligned} \partial_{x}^{k} 2 \partial_{y} \tilde{u} & = \left(\partial_{\tilde{x}}+\partial_{x} \psi \partial_{\psi}\right)^{k} \partial_{\psi} w, \\ \partial_{x}^{k} 2 \partial_{y}^{2} \tilde{u} & = \left(\partial_{\tilde{x}}+\partial_{x} \psi \partial_{\psi}\right)^{k}\left(\partial_{\tilde{x}} w+2 \rho\partial_{x}P-2\frac{\partial_{x}\rho}{\rho}w\right) \\ & = \left(\partial_{\tilde{x}}+\partial_{x} \psi \partial_{\psi}\right)^{k}\left(\partial_{\tilde{x}} w\right)+2 \partial_{\tilde{x}}^{k}(\rho\partial_{x}P)-2\left(\frac{\partial_{x}\rho}{\rho}\right)(\partial_{\tilde{x}}+\partial_{x} \psi \partial_{\psi})^{k}w-2\partial_{\tilde{x}}^{k}\left(\frac{\partial_{x}\rho}{\rho}\right)w. \end{aligned} \end{align*}$

By $|\partial_{x} \psi| \leq C \psi$ and Lemma 2.7, we obtain that Theorem 1.5 holds for $m = 0, 1, 2,$

$\begin{align} |\partial_{x}^{k} \partial_{y} \tilde{u}|+|\partial_{x}^{k} \partial_{y}^{2} \tilde{u}| \leq C . \end{align}$

(3.1)

We inductively assume that for any integer $k$ and $m \geq 1$ ,

$\begin{align} |\partial_{x}^{k} \partial_{y}^{j}\tilde{u}| \leq C, \quad j \leq m . \end{align}$

(3.2)

A direct calculation gives

$\begin{align*} \begin{aligned} &\partial_{x}^{k} \partial_{y}^{m+1} \tilde{u} \\ & = \partial_{x}^{k} \partial_{y}^{m-1} \partial_{y}^{2} \tilde{u}\\ & = \partial_{x}^{k} \partial_{y}^{m-1}\left(\tilde{u} \partial_{x} \tilde{u}-\partial_{y}\tilde{u} \int_{0}^{y}\partial_{x} \tilde{u}d y-\frac{\partial_{x}\rho}{\rho}\tilde{u}^{2}\right) \\ & = \partial_{x}^{k}\bigg(\sum\limits_{i = 0}^{m-1} C_{m-1}^{i} \partial_{y}^{m-1-i}\tilde{u}\partial_{y}^{i} \partial_{x} \tilde{u}-\sum\limits_{i = 0}^{m-2} C_{m-1}^{i+1} \partial_{y}^{m-1-i}\tilde{u} \partial_{y}^{i} \partial_{x} \tilde{u}-\partial_{y}^{m}\tilde{u} \int_{0}^{y}\partial_{x} \tilde{u}d y-\frac{\partial_{x}\rho}{\rho}\partial_{y}^{m-1}\tilde{u}^{2}\bigg), \end{aligned} \end{align*}$

and we can deduce from (3.1) and (3.2) that

$\begin{align*} |\partial_{x}^{k} \partial_{y}^{j} \tilde{u}| \leq C, \quad j \leq m+1 .\quad \Rightarrow \quad |\partial_{x}^{k} \partial_{y}^{j} u| \leq C, \quad j \leq m+1. \end{align*}$

This completes the proof of the theorem.

4. Proof of Theorem 1.3 and 1.6

In this section, we prove our main theorem. The key point is to prove that (1.6) is a uniform parabolic equation. The proof is based on the classical parabolic maximum principle. The specific proof details are as follows.

Proof. By (1.2) and $\partial_{x}P \leq 0$ , we obtain

$\begin{align*} C \geq U^{2}(x) = U^{2}(0)-2 \int_{0}^{x} \frac{\partial_{x}P(\rho)}{\rho} d x \geq U^{2}(0). \end{align*}$

By (1.7) and $w$ increasing in $\psi$ (see below), we know that there exists some positive constants $\Psi$ and $C_{0}$ such that for any $(x, \psi)\in[0, X] \times[\Psi, +\infty),$

$\begin{align} w \geq C_{0}U^{2}(0). \end{align}$

(4.1)

From Theorem 1.1, we know that there exists positive constants $y_{0}, M, m$ such that for any $(x, \psi)\in[0, X] \times[0, y_{0}]$ (we can take $y_{0}$ to be small enough),

$\begin{align} M \geq \partial_{y} \tilde{u}(x, y) \geq m . \end{align}$

(4.2)

The fact that $\psi\sim y^{2}$ is near the boundary $y = 0$ (see Remark 4.1 in ^[23]), for some small positive constant $0 < \kappa < 1$ , we get

$\begin{align} \frac{\kappa}{2} y_{0}^{2} \leq \psi \leq \kappa y_{0}^{2} \Rightarrow \sigma y_{0} \leq y \leq \frac{y_{0}}{2}, \end{align}$

(4.3)

for some constant $\sigma > 0$ depends on $\kappa, m, M$ .

We denote

$\begin{align*} \Omega = \bigl\{(x,\psi)|0\leq x\leq X,\frac{\kappa}{2} y_{0}^{2}\leq \psi\leq +\infty\bigr\}. \end{align*}$

By (4.2) and (4.3), we get $\tilde{u}(x, \sigma y_{0}) \geq m \sigma y_{0}$ , then for any $x\in[0, X]$ , we have

$\begin{align} w(x, \frac{\kappa}{2} y_{0}^{2}) \geq m^{2} \sigma^{2} y_{0}^{2}. \end{align}$

(4.4)

Since the initial data $u_{0}$ satisfies the condition (1.9) and $w = \tilde{u}^{2}$ , we know $w(0, \psi) > 0$ for $\psi > 0$ and there exists a positive constant $\zeta$ , such that for $\psi \in[\frac{\kappa}{2} y_{0}^{2}, \Psi]$ ,

$\begin{align} w(0, \psi) > \zeta. \end{align}$

(4.5)

Then, we only consider

$\begin{align*} \Omega_{1} = \bigl\{(x, \psi)|0\leq x\leq X, \frac{\kappa}{2} y_{0}^{2}\leq\psi\leq \Psi\bigr\}. \end{align*}$

We denote $H(x, \psi): = e^{-\lambda x}\partial_{\psi}w(x, \psi)$ , which satisfies the following system in the region $\Omega_{0} = \left\{(x, \psi)|0\leq x < X, 0 < \psi < +\infty\right\}$ :

$\begin{align} \left\{\begin{aligned} &\partial_{x}H-\frac{\partial_{\psi}w}{2\sqrt{w}}\partial_{\psi}H-\sqrt{w}\partial_{\psi}^{2}H+(\lambda-2\frac{\partial_{x}\rho}{\rho})H = 0,\\ &H|_{x = 0} = \partial_{\psi}w_{0}(\psi),\quad H|_{\psi = 0} = 2e^{-\lambda x}\partial_{y}\tilde{u}|_{y = 0},\quad H|_{\psi = +\infty} = 0. \end{aligned}\right. \end{align}$

(4.6)

Then, we choose $\lambda$ properly large such that $\lambda-2\frac{\partial_{x}\rho}{\rho}\geq 0$ . Due to

$\begin{align*} H|_{x = 0} = \partial_{\psi}w_{0}(\psi)\geq0,\quad H|_{\psi = 0} = 2e^{-\lambda x}\partial_{y}\tilde{u}|_{y = 0} > 0,\quad H|_{\psi = +\infty} = 0, \end{align*}$

it follows that

$\begin{align*} H(x,\psi) = e^{-\lambda x}F(x,\psi) = e^{-\lambda x}\partial_{\psi}w\geq0,\quad (x, \psi)\in[0,X^{*})\times\mathbb{R}_{+}, \end{align*}$

which means $\partial_{\psi}w\geq0$ in $[0, X)\times\mathbb{R}_{+}$ . Hence, $w$ is increasing in $\psi$ . Therefore, we know that there exists a positive constant $\lambda\geq m^{2} \sigma^{2} y_{0}^{2}$ such that for any $x\in[0, X],$

$\begin{align} w(x, \Psi) \geq \lambda. \end{align}$

(4.7)

By (1.6), for any $\varepsilon > 0$ , we know $W: = w+\varepsilon x$ satisfies the following system in $\Omega_{1}:$

$\begin{align*} \left\{\begin{aligned} &\partial_{x}W-\sqrt{w}\partial_{\psi}^{2}W-2\frac{\partial_{x}\rho}{\rho}W = \mathcal{F},\\ &W|_{x = 0} = W_{0} > \zeta,\quad W|_{\psi = \frac{\kappa}{2}y^{2}_{0}} = W_{1}\geq m^{2}\sigma^{2}y^{2}_{0},\quad W|_{\psi = \Psi} = W_{2}\geq \lambda, \end{aligned}\right. \end{align*}$

where

$\begin{align*} \mathcal{F} = -2\rho\partial_{x}P+\varepsilon-2\varepsilon x \frac{\partial_{x}\rho}{\rho}. \end{align*}$

Since $\partial_{x}P\leq0$ , we know the diffusive term $\mathcal{F} > 0.$ Therefore, the minimum cannot be reached inside $\Omega_{1}$ . Set

$\begin{align*} \eta_{0} = \min\left\{W_{0}, W_{1}, W_{2}\right\}, \end{align*}$

then by the maximum principle, we obtain $W = w+\varepsilon x\geq \eta_{0}$ . Let $\varepsilon \rightarrow 0$ , we have $w \geq \eta_{0}$ in $\Omega_{1}$ . Then we denote

$\begin{align*} \eta = \min\left\{\eta_{0}, C_{0}U^{2}(0)\right\} > 0, \end{align*}$

combining with (4.1), we have $w\geq\eta$ in $\Omega$ . Therefore, there exists some positive constant $c$ such that $c\leq w$ in $\Omega$ . From Theorem 1.1, we have $w \leq C$ in $\Omega$ . In sum, there exists positive constants $c, C$ such that $c \leq w \leq C$ in $\Omega$ . This further means that

$\begin{align} 0 < \sqrt{c}\leq\sqrt{w}\leq\sqrt{C}, \end{align}$

(4.8)

where $C$ depends on $X$ . Therefore, we prove (1.6) is a uniform parabolic equation. Furthermore, by Theorem 1.1, we know $\partial_{y}\tilde{u}, \partial_{y}^{2}\tilde{u}$ are continuous and bounded in $[0, X)\times \mathbb{R}_{+}$ . Combining $\rho$ , $\partial_{x}P$ are smooth, (4.8) with

$\begin{align*} 2\partial_{y}\tilde{u} = \partial_{\psi}w,\quad 2\partial_{y}^{2}\tilde{u} = \sqrt{w}\partial_{\psi}^{2}w = \partial_{x}w-2\frac{\partial_{x}\rho}{\rho}w+2\rho\partial_{x}P(\rho), \end{align*}$

we obtain

$\begin{align*} \|\sqrt{w}\|_{\mathcal{C}^{\alpha}(\Omega)}\leq C. \end{align*}$

Once we have the above conclusion, the proof of Theorem 1.6 can be given in a similar fashion to ^[23]. Here, we provide a brief explanation for the reader's convenience. More details can be found in ^[23].

Step 1: For any $(x_{1}, \psi_{1})\in[\varepsilon, X]\times[ \kappa y_{0}^{2}, +\infty)$ , we denote

$\begin{align*} \Omega_{x_{1}, \psi_{1}} = \bigl\{(x, \psi)|x_{1}-\frac{\varepsilon}{2}\leq x\leq x_{1}, \psi_{1}-\frac{\kappa}{2} y_{0}^{2}\leq\psi\leq \psi_{1}+\frac{\kappa}{2} y_{0}^{2}\bigr\}. \end{align*}$

Step 2: Note that the known function $\rho$ , $\partial_{x}P$ is smooth, we can repeat interior Schauder estimates in $\Omega_{x_{1}, \psi_{1}}$ to achieve uniform estimates independent of choice of $(x_{1}, \psi_{1})$ for any order derivatives of $w$ . Since the width and the length of $\Omega_{x_{1}, \psi_{1}}$ are constants and the estimates employed are independent of $(x_{1}, \psi_{1})$ , restricting the estimates to the point $(x_{1}, \psi_{1})$ , we can get for any $m < +\infty, |\nabla^{m}w(x_{1}, \psi)|\leq C_{X, m, y_{0}, \varepsilon}$ .

Step 3: Since $(x_{1}, \psi_{1})$ is arbitrary, we have for any $m < +\infty, |\nabla^{m}w(x_{1}, \psi)|\leq C_{X, m, y_{0}, \varepsilon}$ in $[\varepsilon, X]\times[ \kappa y_{0}^{2}, +\infty)$ . Then, as in Section 3, we can prove Theorem 1.6.

Finally, Theorem 1.3 is proven by combining Theorem 1.5 and Theorem 1.6.

Use of AI tools declaration

The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

Acknowledgments

The research of Zou was supported by the Fundamental Research Funds for the Central Universities (Grant No. 202261101).

Conflict of interest

The authors declare there is no conflict of interest.

References

[1]	Q. Ni, J. Ji, K. Feng, B. Halkon, A novel correntropy-based band selection method for the fault diagnosis of bearings under fault-irrelevant impulsive and cyclostationary interferences, Mech. Syst. Sig. Process., 153 (2021), 107498. https://doi.org/10.1016/j.ymssp.2020.107498 doi: 10.1016/j.ymssp.2020.107498
[2]	R. L. Larson, R. C. Searle, M. C. Kleinrock, H. Schouten, R. T. Bird, D. F. Naar, et al., Roller-bearing tectonic evolution of the Juan Fernandez microplate, Nature, 356 (1992), 571–576. https://doi.org/10.1038/356571a0 doi: 10.1038/356571a0
[3]	T. Wang, Z. Liu, G. Lu, J. Liu, Temporal-spatio graph based spectrum analysis for bearing fault detection and diagnosis, IEEE Trans. Ind. Electron., 68 (2021), 2598–2607. https://doi.org/10.1109/TIE.2020.2975499 doi: 10.1109/TIE.2020.2975499
[4]	A. Jardine, D. Lin, D. Banjevic, A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mech. Syst. Sig. Process., 20 (2006), 1483–1510. https://doi.org/10.1016/j.ymssp.2005.09.012 doi: 10.1016/j.ymssp.2005.09.012
[5]	Q. Ni, J. Ji, K. Feng, B. Halkon, A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis, Mech. Syst. Sig. Process., 164 (2022), 108216. https://doi.org/10.1016/j.ymssp.2021.108216 doi: 10.1016/j.ymssp.2021.108216
[6]	T. Wang, G. Lu, P. Yan, A novel statistical time-frequency analysis for rotating machine condition monitoring, IEEE Trans. Ind. Electron., 67 (2020), 531–541. https://doi.org/10.1109/TIE.2019.2896109 doi: 10.1109/TIE.2019.2896109
[7]	S. Yang, Z. Liu, G. Lu, Early change detection in dynamical bearing degradation process based on hierarchical graph model and adaptive inputs weighting fusion, IEEE Trans. Ind. Electron., 17 (2021), 3186–3196. https://doi.org/10.1109/TⅡ.2020.3007653 doi: 10.1109/TⅡ.2020.3007653
[8]	V. Sugumaran, V. Muralidharan, K. Ramachandran, Feature selection using decision tree and classification through proximal support vector machine for fault diagnostics of roller bearing, Mech. Syst. Sig. Process., 21 (2007), 930–942. https://doi.org/10.1016/j.ymssp.2006.05.004 doi: 10.1016/j.ymssp.2006.05.004
[9]	J. Wang, S. Liu, R. X. Gao, R. Yan, Current envelope analysis for defect identification and diagnosis in induction motors, J. Manuf. Syst., 31 (2012), 380–387. https://doi.org/10.1016/j.jmsy.2012.06.005 doi: 10.1016/j.jmsy.2012.06.005
[10]	N. K. Verma, V. K. Gupta, M. Sharma, R. K. Sevakula, Intelligent condition based monitoring of rotating machines using sparse auto-encoders, in 2013 IEEE Conference on Prognostics and Health Management (PHM), (2013), 1–7. https://doi.org/10.1109/ICPHM.2013.6621447
[11]	G. E. Hinton, R. R. Salakhutdinov, Reducing the dimensionality of data with neural networks, Science, 313 (2006), 504–507. https://doi.org/10.1126/science.1127647 doi: 10.1126/science.1127647
[12]	B. Buxton, D. Goldston, C. Doctorow, M. Waldrop, Big data: science in the petabyte era, Nature, 455 (2008). Available from: https://www.mendeley.com/catalogue/3c1a840c-af73-3ada-a109-ac33fdead72e/
[13]	Y. Lei, H. R. Karimi, X. Chen, A novel self-supervised deep LSTM network for industrial temperature prediction in aluminum processes application, Neurocomputing, 502 (2022), 177–185. https://doi.org/10.1016/j.neucom.2022.06.080 doi: 10.1016/j.neucom.2022.06.080
[14]	Q. Wang, B. Wu, P. Zhu, P. Li, W. Zuo, Q. Hu, ECA-Net: efficient channel attention for deep convolutional neural networks, in 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), (2020), 11531–11539. https://doi.org/10.1109/CVPR42600.2020.01155
[15]	H. Ahmed, M. Wong, A. Nandi, Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features, Mech. Syst. Sig. Process., 99 (2018), 459–477. https://doi.org/10.1016/j.ymssp.2017.06.027 doi: 10.1016/j.ymssp.2017.06.027
[16]	P. Jayaswal, S. Verma, A. Wadhwani, Development of EBP-artificial neural network expert system for rolling element bearing fault diagnosis, J. Vib. Control, 17 (2011), 1131–1148. https://doi.org/10.1177/1077546310361858 doi: 10.1177/1077546310361858
[17]	O. Janssens, V. Slavkovikj, B. Vervisch, K. Stockman, M. Loccufier, S. Verstockt, et al., Convolutional neural network based fault detection for rotating machinery, J. Sound Vib., 377 (2016), 331–345. https://doi.org/10.1016/j.jsv.2016.05.027 doi: 10.1016/j.jsv.2016.05.027
[18]	S. G. Kumbhar, E. Sudhagar, An integrated approach of adaptive neuro-fuzzy inference system and dimension theory for diagnosis of rolling element bearing, Measurement, 166 (2020), 108266. https://doi.org/10.1016/j.measurement.2020.108266 doi: 10.1016/j.measurement.2020.108266
[19]	A. Ajagekar, F. You, Quantum computing assisted deep learning for fault detection and diagnosis in industrial process systems, Comput. Chem. Eng., 143 (2020), 107119. https://doi.org/10.1016/j.compchemeng.2020.107119 doi: 10.1016/j.compchemeng.2020.107119
[20]	W. Mao, L. Ding, S. Tian, X. Liang, Online detection for bearing incipient fault based on deep transfer learning, Measurement, 152 (2020), 107278. https://doi.org/10.1016/j.measurement.2019.107278 doi: 10.1016/j.measurement.2019.107278
[21]	M. Zhao, M. Kang, B. Tang, M. Pecht, Deep residual networks with dynamically weighted wavelet coefficients for fault diagnosis of planetary gearboxes, IEEE Trans. Ind. Electron., 65 (2018), 4290–4300. https://doi.org/10.1109/TIE.2017.2762639 doi: 10.1109/TIE.2017.2762639
[22]	D. Wu, S. Zhang, H. Zhao, X. Yang, A novel fault diagnosis method based on integrating empirical wavelet transform and fuzzy entropy for motor bearing, IEEE Access, 6 (2018), 35042–35056. https://doi.org/10.1109/ACCESS.2018.2834540 doi: 10.1109/ACCESS.2018.2834540
[23]	W. Yu, C. Zhao, Robust monitoring and fault isolation of nonlinear industrial processes using denoising autoencoder and elastic net, IEEE Trans. Control Syst. Technol., 28 (2020), 1083–1091. https://doi.org/10.1109/TCST.2019.2897946 doi: 10.1109/TCST.2019.2897946
[24]	Z. Pu, C. Li, S. Zhang, Y. Bai, Fault diagnosis for wind turbine gearboxes by using deep enhanced fusion network, IEEE Trans. Instrum. Meas., 70 (2021), 2501811. https://doi.org/10.1109/TIM.2020.3024048 doi: 10.1109/TIM.2020.3024048
[25]	Y. Yang, H. Zheng, Y. Li, M. Xu, Y. Chen, A fault diagnosis scheme for rotating machinery using hierarchical symbolic analysis and convolutional neural network, ISA Trans., 91 (2019), 235–252. https://doi.org/10.1016/j.isatra.2019.01.018 doi: 10.1016/j.isatra.2019.01.018
[26]	V. Tran, B. Yang, F. Gu, A. Ball, Thermal image enhancement using bi-dimensional empirical mode decomposition in combination with relevance vector machine for rotating machinery fault diagnosis, Mech. Syst. Sig. Process., 38 (2013), 601–614. https://doi.org/10.1016/j.ymssp.2013.02.001 doi: 10.1016/j.ymssp.2013.02.001
[27]	G. Huang, Z. Liu, L. Maaten, K. Q. Weinberger, Densely connected convolutional networks, in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (2017), 4700–4708. https://doi.org/10.1109/CVPR.2017.243
[28]	S. J. Pan, Q. Yang, A survey on transfer learning, IEEE Trans. Knowl. Data Eng., 22 (2010), 1345–1359. https://doi.org/10.1109/TKDE.2009.191 doi: 10.1109/TKDE.2009.191
[29]	K. Weiss, T. M. Khoshgoftaar, D. Wang, A survey of transfer learning, J. Big Data, 3 (2016), 9. https://doi.org/10.1186/s40537-016-0043-6 doi: 10.1186/s40537-016-0043-6
[30]	G. Wilson, D. J. Cook, A survey of unsupervised deep domain adaptation, ACM Trans. Intell. Syst. Technol., 11 (2020), 1–46. https://doi.org/10.1145/3400066 doi: 10.1145/3400066
[31]	K. A. Loparo, Case western reserve university bearing data center, Bear. Vib. Data Sets, Case West. Reserve Univ., 2012 (2012), 22–28.
[32]	W. A. Smith, R. B. Randall, Rolling element bearing diagnostics using the Case Western Reserve University data: a benchmark study, Mech. Syst. Sig. Process., 64–65 (2015), 100–131. https://doi.org/10.1016/j.ymssp.2015.04.021 doi: 10.1016/j.ymssp.2015.04.021

This article has been cited by:

Yakui Wu, Qiong Wu, Yue Zhang, Time decay estimates of solutions to a two-phase flow model in the whole space, 2024, 13, 2191-950X, 10.1515/anona-2024-0037

Reader Comments

Your name:*

Email:*
© 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)