A method, apparatus, and medium for predicting the remaining life of a gas cylinder under leakage fault conditions.

Abstract

This invention discloses a method, apparatus, and medium for predicting the remaining life of a gas cylinder under leakage fault conditions, relating to the field of rocket engine technology. It addresses the problem that existing methods cannot determine the remaining life of a gas cylinder in real time based solely on the measurement results of the cylinder's internal pressure. The method for predicting the remaining life of a gas cylinder under leakage fault conditions includes: acquiring the measured value of the cylinder's internal pressure and the cylinder's discrete state-space equation; estimating the cylinder's state based on the measured internal pressure value using an observer and the cylinder's discrete state-space equation, obtaining an estimated state value; iterating the cylinder's internal pressure and temperature in the lumped-parameter dynamics model based on the estimated state value and a preset iteration step size until the cylinder's internal pressure reaches a critical internal pressure value, obtaining the number of iterations; and calculating the remaining life of the gas cylinder based on the number of iterations and the preset iteration step size. The method for predicting the remaining life of a gas cylinder under leakage fault conditions provided by this invention improves the accuracy of the remaining life of the gas cylinder and is simple to implement.

Description

Technical Field

[0001] This invention relates to the field of rocket engine technology, and in particular to a method, device and medium for predicting the remaining life of a gas cylinder under leakage failure. Background Technology

[0002] Liquid rocket engines maintain or alter their operating parameters through valves, controlling transient processes and ensuring stable engine operation. These valves, driven by high-pressure gas, are pneumatic valves. The generator fuel valve, used to control the fuel supply to the gas generator and control engine shutdown, is one such pneumatic valve. When the engine receives a shutdown command, the solenoid valve activates, releasing the high-pressure gas loaded at the generator fuel valve control port. The generator fuel valve closes, cutting off the fuel supply to the gas generator, and the engine shuts down. Therefore, if the control gas cylinder leaks, and the pressure drops to the critical value required to keep the generator fuel valve open, the generator fuel valve automatically closes, and the engine shuts down uncontrolled. In multiple tests, leaks occurred in the pipeline supplying control gas to the generator fuel valve, causing depressurization of the control gas cylinder. In two tests, the cylinder pressure dropped below the generator fuel valve's critical pressure, resulting in automatic closure of the engine fuel valve and automatic engine shutdown. Therefore, it is necessary to treat generator fuel valve control gas cylinder leakage as a fault mode diagnosis, calculate the automatic closure time of the generator fuel valve, and provide support for the overall iterative guidance of the rocket.

[0003] Existing methods for predicting the remaining life of gas cylinders involve detecting acoustic emission mechanical waves inside the cylinder, counting and continuously analyzing these waves over a period of time to plot curves. However, this approach is problematic because leaks can cause unstable gas pressure, leading to errors in sensor measurements and inaccurate cylinder life predictions. Furthermore, various devices are needed to process the acoustic emission mechanical waves to obtain signals suitable for plotting curves, making the process complex and requiring additional sensors, thus presenting significant technical challenges. Finally, the vibrations and impacts experienced during engine operation cause the leakage area to change over time, making acoustic emission methods unsuitable for the leakage characteristics present in liquid rocket engines. Summary of the Invention

[0004] The purpose of this invention is to provide a method, device, and medium for predicting the remaining life of a gas cylinder under leakage fault conditions, in order to solve the problem that existing methods cannot determine the remaining life of a gas cylinder in real time based solely on the measurement results of the internal pressure of the gas cylinder.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] On one hand, the present invention provides a method for predicting the remaining life of a gas cylinder under leakage fault conditions, comprising:

[0007] Obtain the measured internal pressure of the gas cylinder and the discrete state-space equation of the gas cylinder;

[0008] Based on the measured internal pressure of the gas cylinder, the state of the gas cylinder is estimated by an observer and the discrete state space equation of the gas cylinder to obtain estimated state values; the estimated state values ​​include estimated gas cylinder temperature, estimated internal pressure, and estimated gas cylinder leakage area.

[0009] Based on the estimated state value and the preset iteration step size, the cylinder internal pressure and cylinder temperature in the cylinder lumped parameter dynamic model are iterated until the cylinder internal pressure reaches the critical internal pressure value, and the number of iterations is obtained.

[0010] The remaining lifespan of the gas cylinder is calculated based on the number of iterations and the preset iteration step size.

[0011] Compared with existing technologies, the method for predicting the remaining life of a gas cylinder under leakage faults provided by this invention effectively filters out system and measurement noise by estimating the cylinder state through an observer and a discrete state-space model of the cylinder, resulting in more accurate estimates of the cylinder's internal pressure, temperature, and leakage area. The lumped-parameter dynamic model of the cylinder enables the assessment of its dynamic characteristics under leakage conditions. Iterative methods are used to iterate the temperature and internal pressure, resulting in smaller data errors and higher accuracy. Furthermore, the cylinder leakage process is a complex physical process coupled with engine vibration, and the leakage area changes over time. This invention estimates the leakage area in real time and calculates the remaining life of the cylinder based on this estimated area, ensuring the accuracy of the calculation results. Additionally, this method can estimate the leakage area and remaining life of the cylinder in real time based solely on sensor measurement frequency, making it simple to operate.

[0012] Secondly, the present invention also provides a device for predicting the remaining life of a gas cylinder under leakage fault conditions, comprising:

[0013] The cylinder internal pressure value and cylinder discrete state space equation acquisition module is used to acquire the cylinder internal pressure measurement value and the cylinder discrete state space equation.

[0014] The cylinder state estimation module is used to estimate the state of the cylinder based on the measured internal pressure value of the cylinder, through an observer and the discrete state space equation of the cylinder, to obtain an estimated state value; the estimated state value includes an estimated cylinder temperature value, an estimated cylinder internal pressure value, and an estimated cylinder leakage area value.

[0015] The cylinder internal pressure and cylinder temperature iteration module is used to iterate the cylinder internal pressure and cylinder temperature in the cylinder lumped parameter dynamics model based on the estimated state value and the preset iteration step size until the cylinder internal pressure reaches the critical internal pressure value, and obtain the number of iterations.

[0016] The gas cylinder remaining life calculation module is used to calculate the remaining life of the gas cylinder based on the number of iterations and the preset iteration step size.

[0017] Compared with the prior art, the beneficial effects of the device for predicting the remaining life of a gas cylinder under leakage failure provided by the present invention are the same as the beneficial effects of the method for predicting the remaining life of a gas cylinder under leakage failure described in the above technical solution, and will not be repeated here.

[0018] Thirdly, the present invention also provides a computer-readable storage medium, comprising: instructions stored in the computer-readable storage medium, which, when executed, implement the above-mentioned method for predicting the remaining life of a gas cylinder under leakage fault. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0020] Figure 1 A schematic diagram of the control cylinder structure for a liquid rocket engine.

[0021] Figure 2 A flowchart of a method for predicting the remaining life of a gas cylinder under leakage fault provided by the present invention;

[0022] Figure 3 The remaining lifetime flowchart provided by the present invention;

[0023] Figure 4 This is a schematic diagram of the structure of a device for predicting the remaining life of a gas cylinder under leakage faults, provided by the present invention.

[0024] Figure label:

[0025] 1-Gas cylinder, 2-Valve, 3-Pressure sensor, 4-Control pipeline. Detailed Implementation

[0026] To facilitate a clear description of the technical solutions in the embodiments of the present invention, the terms "first" and "second" are used to distinguish identical or similar items with essentially the same function and effect. For example, the first threshold and the second threshold are merely used to distinguish different thresholds and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that the terms "first" and "second" are not necessarily different.

[0027] It should be noted that in this invention, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0028] In this invention, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, a combination of a and b, a combination of a and c, a combination of b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0029] Before introducing the embodiments of the present invention, the relevant terms involved in the embodiments of the present invention are first defined as follows:

[0030] EKF stands for Extended Kalman Filter, a highly efficient recursive filter (autoregressive filter). Kalman filtering is a type of highly efficient recursive filter, also known as an autoregressive filter, that can estimate the state of a dynamic system from a series of measurements that are not entirely free of noise.

[0031] Figure 1 This is a schematic diagram of the control gas cylinder structure for a liquid rocket engine, as shown below. Figure 1As shown, the system mainly includes a gas cylinder 1, a valve 2, and a pressure sensor 3 for measuring the internal pressure of gas cylinder 1. Gas cylinder 1 is a control cylinder, and it is connected to valve 2 via a control pipeline 4. The control medium in gas cylinder 1 is helium. Before a leak occurs, the internal pressure of gas cylinder 1 is approximately 20 MPa, and its volume is 22 L. When gas cylinder 1 is connected to the control port on the right side of valve 2, the pressure of gas cylinder 1 acts on the valve core, pushing it to the left. This pressure overcomes the spring force, and the friction between the valve core and the valve body causes the valve core to move to the left, opening valve 2 and unblocking the fuel path. The required gas pressure to open valve 2 varies depending on the type of valve. Assuming the required gas pressure to open valve 2 is 10 MPa, if a leak occurs in gas cylinder 1 or the control pipeline 4 between gas cylinder 1 and valve 2, and the internal pressure of gas cylinder 1 drops to 10 MPa, the gas pressure in gas cylinder 1 cannot overcome the spring force of the valve body, and valve 2 will automatically close. In this invention, the gas pressure required to open valve 2 is called the critical pressure. Before the pressure inside the gas cylinder drops to the critical pressure, valve 2 remains open. The time from the occurrence of a leakage fault to the closure of valve 2 or the pressure in gas cylinder 1 dropping to the critical pressure is the remaining service life of the gas cylinder.

[0032] Since the leakage process of the gas cylinder is a complex physical process coupled with engine vibration, the leakage area may change over time, requiring real-time estimation of the leakage area. Furthermore, since only the gas cylinder internal pressure information from the start of the test run to the current moment can be collected during the test, this invention provides a method, device, and medium for predicting the remaining life of a gas cylinder under leakage fault conditions. This method calculates the leakage area and estimates the remaining life by analyzing the changes in the gas cylinder internal pressure. The following is a detailed description of this method.

[0033] Figure 2 A flowchart illustrating a method for predicting the remaining life of a gas cylinder under leakage faults provided by this invention is shown below. Figure 2 As shown, the method for predicting the remaining life of a gas cylinder under this leakage fault includes the following steps:

[0034] Step 201: Obtain the measured internal pressure of the gas cylinder and the discrete state-space equation of the gas cylinder.

[0035] The internal pressure of the gas cylinder is measured in real time using a pressure sensor.

[0036] As an optional approach, the steps for establishing the discrete state-space equations of the gas cylinder are as follows:

[0037] A lumped parameter model of the gas cylinder is established based on the mass conservation equation, energy conservation equation, and gas equation.

[0038] Specifically, the mass conservation equation is shown in formula (1), the energy conservation equation is shown in formula (2), and the gas equation is shown in formula (3):

[0039]

[0040]

[0041] pV = mR g T (3)

[0042] Where m is the mass of the gas, t is time, and q is... m It is the leakage rate, c v It is the specific heat capacity at constant volume, c p It is the specific heat capacity at constant pressure, T is the gas temperature, p is the gas pressure, V is the gas cylinder volume, and R is the gas pressure. g It is the gas constant.

[0043] Based on formulas (1), (2), and (3), the lumped parameter model of the gas cylinder is derived, as shown in formulas (4) and (5):

[0044]

[0045]

[0046] Where, k g It is the specific heat ratio of the gas, k. g =c p / c v .

[0047] The flow rate equation for the leaked mass of the gas cylinder is calculated based on the equation of the throttling element.

[0048] Specifically, the equation for the throttling element is shown in formula (6):

[0049]

[0050] Where A is the leakage area of ​​the gas cylinder, k is the specific heat ratio of the gas, q(λ) is the leakage rate, and λ is the velocity coefficient.

[0051] The leakage area of ​​the gas cylinder is obtained by transforming formula (6) as shown in formula (7), and the leakage rate of the gas cylinder is shown in formula (8):

[0052]

[0053]

[0054] During gas cylinder leakage, due to the low external pressure, the sound velocity condition of formula (9) is always satisfied:

[0055]

[0056] Where, p b The pressure is atmospheric, and the flow velocity at the leak hole is equal to the speed of sound, λ = 1.

[0057] Substituting λ into formula (8), the leakage rate of the gas cylinder is obtained as shown in formula (10):

[0058] q(λ)=1 (10)

[0059] Substituting equations (7) and (10) into equation (6), the flow equation for the leaked mass of the gas cylinder is obtained as shown in equation (11):

[0060]

[0061] Substituting equation (11) into equations (4) and (5), we obtain the lumped parameter dynamic model of the gas cylinder with the leakage area as the geometric parameter, as shown in equations (12) and (13):

[0062]

[0063]

[0064] Based on the lumped parameter dynamic model of the gas cylinder, a continuous state-space equation for the gas cylinder is established with the internal pressure, temperature and leakage area of ​​the gas cylinder as state parameters.

[0065] The measurement noise and the process noise of the state parameters are added to the continuous state-space equation of the gas cylinder and discretized to obtain the discrete state-space equation of the gas cylinder.

[0066] Specifically, the continuous state-space equations with additive noise are shown in equations (14) and (15):

[0067]

[0068] y(t)=g(x(t))+v(t) (15)

[0069] in, Let be the rate of change of the state parameter, x be the state parameter, y be the system output parameter, f(·) and g(·) be the nonlinear mappings, w(t) be the Gaussian white noise of the process, v(t) be the Gaussian white noise of the measurement, the mean of w(t) is equal to 0, and the covariance is represented by Q.

[0070] The internal pressure of the gas cylinder, the temperature of the gas cylinder, and the leakage area of ​​the gas cylinder are taken as the state parameters of the system, as shown in formula (16):

[0071] x=[x1,x2,x3]=[p,T,A] (16)

[0072] The internal pressure of the gas cylinder is used as the system output parameter, as shown in formula (17):

[0073] y = [y1] = [p] (17)

[0074] According to formulas (12)-(17), the continuous state space equations of the gas cylinder can be obtained, as shown in formulas (18) and (19):

[0075]

[0076] [y1(t)]=[x1(t)]+[v1(t)] (19)

[0077] Where k is the specific heat ratio of the gas.

[0078] Discretizing equations (18) and (19) yields the discrete state-space equations of the gas cylinder, as shown in equations (20) and (21):

[0079] x k =Φ(x k-1 )+w k-1 (20)

[0080] y k =h(x k )+v k (twenty one)

[0081] Where Φ is the state transition matrix, and Φ(·) and h(·) are nonlinear mappings.

[0082] Step 202: Based on the measured internal pressure of the gas cylinder, the state of the gas cylinder is estimated by the observer and the discrete state space equation of the gas cylinder to obtain the estimated state value.

[0083] The estimated state values ​​include the estimated cylinder temperature, the estimated cylinder internal pressure, and the estimated cylinder leakage area.

[0084] Optionally, the observer can be a Kalman observer. The following explanation uses extended Kalman filtering as an example:

[0085] Based on the state equation in the discrete state space equation of the gas cylinder and the given initial state value of the gas cylinder, the mean and variance of the gas cylinder state parameters are predicted.

[0086] Based on the prediction results and the measured internal pressure of the gas cylinder, the mean and variance of the gas cylinder state parameters are updated to obtain the estimated state values.

[0087] Specifically, the prediction equations for the extended Kalman filter are shown in equations (22) and (23):

[0088]

[0089]

[0090] in, Let x be the prior value of the mean of the state parameter x at time k, and P be the variance of the state parameter. Let P be the prior variance of P at time k, based on P k The change in state estimation error over time can be observed; Φ is the state transition matrix, A k-1 Let be the Jacobian matrix of the process quantity at time k-1.

[0091] Update: The update equations for the extended Kalman filter are shown in equations (24), (25), and (26):

[0092]

[0093]

[0094]

[0095] Where I is the standard matrix, K k For Kalman gain, C k K is the Jacobian matrix of the system output parameters. k The bias of the system's prediction and measurement results when weighted summation is determined by K. k The smaller the value, the more the weighted sum is biased towards the system's prediction result. k The larger the size, the opposite is true.

[0096] Among them, A k-1 The calculation equation is shown in formula (27); C k The calculation equation is shown in formula (28):

[0097]

[0098]

[0099] Specifically, firstly, given initial state values ​​x1(0), x2(0), x3(0), the prior prediction results of the mean and variance of the state parameters when k=1 are obtained according to formulas (22) and (23); then, based on formulas (24), (25) and (26), the prior prediction results of k=1 are updated according to the measured value of the gas cylinder pressure to obtain the posterior results of the mean and variance of the state parameters when k=1, thus completing one prediction and update process; based on the posterior results when k=1, the prior prediction results of the mean and variance of the state parameters when k=2 are predicted; then, based on the measured value of the gas cylinder pressure when k=2, the prior prediction results of the mean and variance of the state parameters when k=2 are updated to obtain the posterior results of the mean and variance of the state parameters when k=2. By analogy, the estimated results of the mean and variance of the state parameters at any time can be obtained iteratively. Based on the estimated results of the mean and variance of the state parameters, the estimated state value can be obtained.

[0100] Step 203: Based on the estimated state value and the preset iteration step size, iterate the cylinder internal pressure and cylinder temperature in the cylinder lumped parameter dynamic model until the cylinder internal pressure reaches the critical internal pressure value, and obtain the number of iterations.

[0101] The lumped parameter dynamic model of the gas cylinder is an ordinary differential equation, which can be iteratively calculated using any ordinary differential equation solution method, such as the fourth-order Runge-Kutta method, the Runge-Kutta method, or the Euler method. Here, we are only using it as an example and not making specific limitations. The following will explain in detail the fourth-order Runge-Kutta method:

[0102] The preset iteration step size can be set as the time difference between two consecutive pressure measurements of the gas cylinder by the pressure sensor.

[0103] The iterative scheme of the fourth-order Runge-Kutta method is shown in formula (29):

[0104]

[0105] Where u = [p, T], h is the time step, which is the preset iteration step in this iterative method, n is the number of iterations, n = 1, 2, 3..., and K1 to K4 are the slope values ​​of each intermediate point within each preset iteration step, as shown in formula (30):

[0106]

[0107] The time t for the n+1 iterations n+1 As shown in formula (31):

[0108] t n+1 =t n +h (31)

[0109] The iteration process from the nth to the (n+1)th iteration is as follows:

[0110] First, based on the lumped parameter dynamic model of the gas cylinder, the first slope value of the gas cylinder temperature at each intermediate point within each preset iteration step and the second slope value of the gas cylinder internal pressure at each intermediate point within each preset iteration step are calculated by the fourth-order Runge-Kutta method.

[0111] Specifically, according to formulas (12), (13), and (30), the first slope value of the gas cylinder internal pressure p at time n and the second slope value of the gas cylinder temperature T at time n are calculated respectively, as shown in formula (32):

[0112]

[0113] Then, the cylinder temperature value at the next moment is calculated based on the first slope value, the estimated cylinder temperature value, and the estimated cylinder leakage area value; the cylinder internal pressure value at the next moment is calculated based on the second slope value, the estimated cylinder internal pressure value, and the estimated cylinder leakage area value, thus completing the first iteration;

[0114] Specifically, the cylinder temperature at the next moment is calculated according to formula (33):

[0115]

[0116] The temperature of the gas cylinder at the next moment is calculated according to formula (34):

[0117]

[0118] The above describes the implementation state (p). n ,T n ) to (p n+1 ,T n+1 Iteration of ).

[0119] Similarly, according to formulas (33) and (34), the next iteration is performed based on the first slope value at time k+1, the second slope value at time k+1, and the iteration result obtained from the previous iteration. In order to output the time of the gas cylinder leakage process, the iteration process does not set a specific number of iterations, but only sets the iteration stop condition: when the pressure value inside the gas cylinder drops to the critical pressure value, the iteration stops and the number of iterations is output.

[0120] Step 204: Calculate the remaining lifespan of the gas cylinder based on the number of iterations and the preset iteration step size.

[0121] Specifically, the product of the number of iterations and the iteration time step is the remaining life of the gas cylinder.

[0122] The specific implementation process can be combined with Figure 3Please provide an explanation, such as Figure 3 As shown, the method for predicting the remaining life of a gas cylinder under leakage faults provided by this invention consists of two parts: state estimation and life prediction. First, state estimation is performed based on the measurement results of the pressure sensor in the gas cylinder. Using an EKF observer and the discrete state-space equations of the gas cylinder, the internal pressure, temperature, and leakage area of ​​the gas cylinder can be estimated. If the estimated leakage area is greater than or equal to zero, the fault is eliminated; otherwise, the estimation result of the EKF observer is further used to predict the remaining life of the gas cylinder under leakage fault conditions. Then, the estimated results of the internal pressure and temperature at each discrete preset iteration step are used as initial conditions, and the estimated result of the gas cylinder leakage area is used as the geometric parameters of the lumped parameter dynamics model of the gas cylinder. The fourth-order Runge-Kutta method is used to iteratively calculate the lumped parameter dynamics model of the gas cylinder, which consists of ordinary differential equations. To obtain the remaining life of the gas cylinder, the iterative calculation continues until the pressure reaches the critical pressure. The estimated value of the remaining life is equal to the product of the number of iterations and the preset iteration step. At each discrete time step, the above calculation is repeated to obtain the remaining life of the gas cylinder at the corresponding time. Thus, based on the measurement frequency of the pressure sensor, the leakage area and the remaining life of the gas cylinder can be estimated in real time. It fills a gap in engineering applications.

[0123] Based on the aforementioned method and implementation process for predicting the remaining life of a gas cylinder under leakage faults, it can be seen that the method provided by this invention, which estimates the cylinder state using an observer and a discrete state-space model of the cylinder, can effectively filter out system and measurement noise, resulting in more accurate estimates of the cylinder's internal pressure, temperature, and leakage area. The lumped-parameter dynamic model of the cylinder can assess its dynamic characteristics under leakage conditions. Iterative methods are used to iterate the temperature and internal pressure, resulting in smaller data errors and higher accuracy. Furthermore, the cylinder leakage process is a complex physical process coupled with engine vibration, and the leakage area changes over time. This invention estimates the leakage area in real time and calculates the remaining life of the cylinder based on this estimated area, ensuring the accuracy of the calculation results. Additionally, this method can estimate the leakage area and the remaining life of the cylinder in real time based on the sensor measurement frequency.

[0124] The above mainly describes the solution provided by the embodiments of the present invention from the perspective of the interaction between various network elements. It is understood that, in order to achieve the above functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, the present invention can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0125] The embodiments of the present invention can divide functional modules according to the above method examples. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in the embodiments of the present invention is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0126] When dividing each function into modules according to its corresponding function. Figure 4 A schematic diagram of a device for predicting the remaining life of a gas cylinder under leakage fault conditions, provided in an embodiment of the present invention, is shown. Figure 4 As shown, the prediction device includes:

[0127] The cylinder internal pressure value and cylinder discrete state space equation acquisition module 401 is used to acquire the cylinder internal pressure measurement value and the cylinder discrete state space equation.

[0128] The cylinder state estimation module 402 is used to estimate the state of the cylinder based on the measured internal pressure value of the cylinder, through an observer and the discrete state space equation of the cylinder, to obtain an estimated state value; the estimated state value includes an estimated cylinder temperature value, an estimated cylinder internal pressure value, and an estimated cylinder leakage area value.

[0129] The cylinder internal pressure and cylinder temperature iteration module 403 is used to iterate the cylinder internal pressure and cylinder temperature in the cylinder lumped parameter dynamic model based on the estimated state value and the preset iteration step size until the cylinder internal pressure reaches the critical internal pressure value, and obtain the number of iterations.

[0130] The gas cylinder remaining life calculation module 404 is used to calculate the gas cylinder remaining life based on the number of iterations and the preset iteration step size.

[0131] Optionally, the gas cylinder state estimation module 402 can be specifically used for:

[0132] Using extended Kalman filtering, based on the state equation in the discrete state space equation of the gas cylinder and the given initial state value of the gas cylinder, the mean and variance of the gas cylinder state parameters are predicted.

[0133] Based on the prediction results and the measured internal pressure of the gas cylinder, the mean and variance of the gas cylinder state parameters are updated to obtain the estimated state values.

[0134] Optionally, the cylinder internal pressure and cylinder temperature iteration module 403 may include:

[0135] The first slope value and the second slope value calculation unit are used to calculate the first slope value of the gas cylinder temperature at each intermediate point within each preset iteration step and the second slope value of the gas cylinder internal pressure at each intermediate point within each preset iteration step based on the gas cylinder lumped parameter dynamic model and the fourth-order Runge-Kutta method.

[0136] The first iteration unit is used to calculate the cylinder temperature value at the next moment based on the first slope value, the estimated cylinder temperature value, and the estimated cylinder leakage area value; and to calculate the cylinder internal pressure value at the next moment based on the second slope value, the estimated cylinder internal pressure value, and the estimated cylinder leakage area value, thus completing the first iteration.

[0137] The iteration count output unit is used to perform the next iteration based on the first slope value, the second slope value, and the iteration result obtained from the previous iteration, until the internal pressure value of the gas cylinder reaches the critical pressure value, and obtain the iteration count.

[0138] Optionally, the prediction device may further include:

[0139] The lumped parameter model building module for gas cylinders is used to build lumped parameter models of gas cylinders based on the mass conservation equation, energy conservation equation, and gas equation.

[0140] The flow equation calculation module for gas cylinder leakage mass is used to calculate the flow equation for gas cylinder leakage mass based on the throttling element equation.

[0141] The cylinder lumped parameter dynamic model establishment module is used to substitute the flow equation into the lumped parameter model to obtain a cylinder lumped parameter dynamic model with leakage area as the geometric parameter.

[0142] Optionally, the prediction device may further include:

[0143] The cylinder continuous state space equation establishment module is used to establish the cylinder continuous state space equation with cylinder internal pressure, cylinder temperature and cylinder leakage area as state parameters based on the cylinder lumped parameter dynamic model.

[0144] The discrete state space equation establishment module for the gas cylinder is used to add the measurement noise and the process noise of the state parameters into the continuous state space equation of the gas cylinder and perform discretization processing to obtain the discrete state space equation of the gas cylinder.

[0145] Optionally, the cylinder internal pressure and cylinder temperature iteration module 403 can also be used for:

[0146] The internal pressure and temperature of the gas cylinder in the lumped dynamic model of the gas cylinder are iterated using the Euler method or the fourth-order Runge-Kutta method.

[0147] Optionally, the observer is a Kalman observer.

[0148] Optionally, the preset iteration step size is equal to the time difference between two consecutive measurements of the gas cylinder pressure by the pressure sensor.

[0149] On the one hand, a computer-readable storage medium is provided, which stores instructions that, when executed, are used to implement:

[0150] Obtain the measured internal pressure of the gas cylinder and the discrete state-space equation of the gas cylinder;

[0151] Based on the measured internal pressure of the gas cylinder, the state of the gas cylinder is estimated by an observer and the discrete state space equation of the gas cylinder to obtain estimated state values; the estimated state values ​​include estimated gas cylinder temperature, estimated internal pressure, and estimated gas cylinder leakage area.

[0152] Based on the estimated state value and the preset iteration step size, the cylinder internal pressure and cylinder temperature in the cylinder lumped parameter dynamic model are iterated until the cylinder internal pressure reaches the critical internal pressure value, and the number of iterations is obtained.

[0153] The remaining lifespan of the gas cylinder is calculated based on the number of iterations and the preset iteration step size.

[0154] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video disc (DVD); or it can be a semiconductor medium, such as a solid-state drive (SSD).

[0155] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings, the disclosure, and the appended claims in carrying out the claimed invention. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0156] Although the invention has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made therein without departing from the spirit and scope of the invention. Accordingly, this specification and drawings are merely exemplary descriptions of the invention as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its spirit and scope. Thus, if such modifications and modifications of the invention fall within the scope of the claims and their equivalents, the invention is also intended to include such modifications and modifications.

Claims

1. A method for predicting the remaining life of a gas cylinder under leakage fault conditions, characterized in that, include: Obtain the measured internal pressure of the gas cylinder and the discrete state-space equation of the gas cylinder; Based on the measured internal pressure of the gas cylinder, the state of the gas cylinder is estimated by an observer and the discrete state space equation of the gas cylinder to obtain estimated state values; the estimated state values ​​include estimated gas cylinder temperature, estimated internal pressure, and estimated gas cylinder leakage area. Based on the estimated state value and the preset iteration step size, the cylinder internal pressure and cylinder temperature in the cylinder lumped parameter dynamic model are iterated until the cylinder internal pressure reaches the critical internal pressure value, and the number of iterations is obtained. The remaining lifespan of the gas cylinder is calculated based on the number of iterations and the preset iteration step size. The process of estimating the state of the gas cylinder based on the measured internal pressure value using an observer and the discrete state-space equation of the gas cylinder to obtain the estimated state value includes: Using extended Kalman filtering, based on the state equation in the discrete state space equation of the gas cylinder and the given initial state value of the gas cylinder, the mean and variance of the gas cylinder state parameters are predicted. Based on the prediction results and the measured internal pressure of the gas cylinder, the mean and variance of the gas cylinder state parameters are updated to obtain the estimated state values. The process involves iterating the cylinder internal pressure and cylinder temperature in the lumped parameter dynamics model based on the estimated state value and a preset iteration step size until the cylinder internal pressure reaches a critical internal pressure value, thus obtaining the number of iterations, including: Based on the lumped parameter dynamic model of the gas cylinder, the first slope value of the gas cylinder temperature at each intermediate point within each preset iteration step and the second slope value of the gas cylinder internal pressure at each intermediate point within each preset iteration step are calculated by the fourth-order Runge-Kutta method. The cylinder temperature value at the next moment is calculated based on the first slope value, the estimated cylinder temperature value, and the estimated cylinder leakage area value; the cylinder internal pressure value at the next moment is calculated based on the second slope value, the estimated cylinder internal pressure value, and the estimated cylinder leakage area value, thus completing the first iteration; Based on the first slope value, the second slope value, and the iteration result obtained from the previous iteration, the next iteration is performed until the internal pressure of the gas cylinder reaches the critical pressure value, thus obtaining the number of iterations.

2. The method for predicting the remaining life of a gas cylinder under leakage faults according to claim 1, characterized in that, Prior to obtaining the measured internal pressure of the gas cylinder and the discrete state-space equation of the gas cylinder, the following steps were also included: A lumped parameter model of the gas cylinder is established based on the mass conservation equation, energy conservation equation, and gas equation. The flow rate equation for the leaked mass of the gas cylinder is calculated based on the equation of the throttling element. Substituting the flow equation into the lumped parameter model yields a lumped parameter dynamic model of the gas cylinder with the leakage area as the geometric parameter.

3. The method for predicting the remaining life of a gas cylinder under leakage faults according to claim 2, characterized in that, The process of substituting the flow equation into the lumped parameter model to obtain a lumped parameter dynamic model of the gas cylinder with the leakage area as the geometric parameter further includes: Based on the lumped parameter dynamic model of the gas cylinder, a continuous state-space equation for the gas cylinder is established with the internal pressure, temperature and leakage area of ​​the gas cylinder as state parameters. The measurement noise and the process noise of the state parameters are added to the continuous state-space equation of the gas cylinder and discretized to obtain the discrete state-space equation of the gas cylinder.

4. The method for predicting the remaining life of a gas cylinder under leakage faults according to claim 1, characterized in that, The process involves iterating over the cylinder internal pressure and cylinder temperature in the lumped parameter dynamics model based on the estimated state value and a preset iteration step size until the cylinder internal pressure reaches a critical internal pressure value. The iteration then stops, and the number of iterations is obtained, including: The internal pressure and temperature of the gas cylinder in the lumped dynamic model of the gas cylinder are iterated using the Euler method or the fourth-order Runge-Kutta method.

5. The method for predicting the remaining life of a gas cylinder under leakage faults according to claim 1, characterized in that, The observer is a Kalman observer.

6. The method for predicting the remaining life of a gas cylinder under leakage faults according to claim 1, characterized in that, The preset iteration step size is equal to the time difference between two consecutive measurements of the internal pressure of the gas cylinder by the pressure sensor.

7. A device for predicting the remaining life of a gas cylinder under leakage fault conditions, characterized in that, include: The cylinder internal pressure value and cylinder discrete state space equation acquisition module is used to acquire the cylinder internal pressure measurement value and the cylinder discrete state space equation. The cylinder state estimation module is used to estimate the state of the cylinder based on the measured internal pressure value of the cylinder, through an observer and the discrete state space equation of the cylinder, to obtain an estimated state value; the estimated state value includes an estimated cylinder temperature value, an estimated cylinder internal pressure value, and an estimated cylinder leakage area value. The cylinder internal pressure and cylinder temperature iteration module is used to iterate the cylinder internal pressure and cylinder temperature in the cylinder lumped parameter dynamics model based on the estimated state value and the preset iteration step size until the cylinder internal pressure reaches the critical internal pressure value, and obtain the number of iterations. The gas cylinder remaining life calculation module is used to calculate the gas cylinder remaining life based on the number of iterations and the preset iteration step size; The gas cylinder state estimation module is specifically used for: Using extended Kalman filtering, based on the state equation in the discrete state space equation of the gas cylinder and the given initial state value of the gas cylinder, the mean and variance of the gas cylinder state parameters are predicted. Based on the prediction results and the measured internal pressure of the gas cylinder, the mean and variance of the gas cylinder state parameters are updated. Obtain the estimated state value; The cylinder internal pressure and cylinder temperature iteration module includes: The first slope value and the second slope value calculation unit are used to calculate the first slope value of the gas cylinder temperature at each intermediate point within each preset iteration step and the second slope value of the gas cylinder internal pressure at each intermediate point within each preset iteration step based on the gas cylinder lumped parameter dynamic model and the fourth-order Runge-Kutta method. The first iteration unit is used to calculate the cylinder temperature value at the next moment based on the first slope value, the estimated cylinder temperature value, and the estimated cylinder leakage area value; and to calculate the cylinder internal pressure value at the next moment based on the second slope value, the estimated cylinder internal pressure value, and the estimated cylinder leakage area value, thus completing the first iteration. The iteration count output unit is used to perform the next iteration based on the first slope value, the second slope value, and the iteration result obtained from the previous iteration, until the internal pressure value of the gas cylinder reaches the critical pressure value, and obtain the iteration count.

8. A computer-readable storage medium, characterized in that, include: The computer-readable storage medium stores instructions that, when executed, implement the method for predicting the remaining life of a gas cylinder under a leakage fault as described in any one of claims 1-6.

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