A health status detection system and method for hydrogen storage equipment in a hydrogen refueling station

Abstract

The present invention discloses a health status detection system for hydrogen storage equipment in a hydrogen refueling station, including a sensor module, a data acquisition and transmission module, a data processing and analysis module, and an alarm and display module; the sensor module is used to detect the hydrogen storage equipment in real time, and the data acquisition and transmission module is used to transmit the signal data sent by the sensor module to the data processing and analysis module; the data processing and analysis module is used to process the digital signal data and input it into a health assessment model, the health assessment model uses a machine learning algorithm to classify and evaluate the hydrogen storage equipment, and outputs the health assessment result to the alarm and display module; the alarm and display module is used to display the real-time status of the hydrogen storage equipment, and when the health assessment result output by the health assessment model reaches a preset alarm threshold, an alarm is triggered. This method can accurately detect internal micro-cracks, scratches, and micro-abnormalities. At the same time, by obtaining the data of the hydrogen storage equipment in the initial health state and using it as the benchmark data of the health assessment model; then when performing real-time detection, the health assessment model evaluates the real-time health status of the hydrogen storage equipment based on the real-time data and the benchmark data.

Description

Technical Field

[0001] The present invention relates to the field of hydrogen refueling stations, and in particular to a health status detection system and method for hydrogen storage equipment in hydrogen refueling stations. Background Art

[0002] With the rapid development of the hydrogen energy industry, the number of hydrogen refueling stations continues to increase. During the operation of hydrogen refueling stations, the safety of valve components and hydrogen storage tanks (bottles) is of vital importance. At present, traditional monitoring methods are mainly based on regular manual inspections and simple pressure and temperature monitoring. This method has incomplete monitoring and cannot monitor the overall health of valve components and hydrogen storage tanks under complex working conditions (such as frequent hydrogen charging and discharging, frequent startup, temperature changes, etc.). As a result, potential safety hazards cannot be discovered in time, which may cause serious accidents such as hydrogen leakage.

[0003] In order to solve the above problems, the patent application document with application number 202310005942.8 discloses a solid-state hydrogen storage tank with a leak detection function, which processes and analyzes the leakage sound detection signal of the solid-state hydrogen storage tank collected by the sound detector by using an artificial intelligence monitoring algorithm based on deep learning to detect whether the solid-state hydrogen storage tank is leaking, and uses the spatial characteristics between multiple sound detectors to optimize the expression of sound characteristics, thereby improving the accuracy of leakage sound detection, thereby improving the safety and fault warning capability of the solid-state hydrogen storage tank.

[0004] However, the above schemes still have shortcomings in the health monitoring methods for hydrogen storage tanks and valves, such as difficulty in accurately detecting internal micro cracks, scratches, and micro abnormalities. At the same time, the existing methods lack judgment criteria for the monitored defects of hydrogen storage tanks and valves.

[0005] Therefore, it is necessary for us to improve the above-mentioned prior art to overcome the above-mentioned defects. Summary of the invention

[0006] The purpose of the present invention is to provide a health status detection system and method for hydrogen storage equipment in a hydrogen refueling station to solve the problems existing in the prior art.

[0007] The above technical objectives of the present invention are achieved through the following technical solutions:

[0008] A health status detection system for hydrogen storage equipment in a hydrogen refueling station, comprising:

[0009] The sensor module is arranged on the hydrogen storage device of the hydrogen refueling station, and is used to detect the hydrogen storage device in real time, and send the detected analog signal data to the data acquisition and transmission module;

[0010] A data acquisition and transmission module, which is respectively connected to the sensor module and the data processing and analysis module for converting the analog signal data sent by the sensor module into digital signal data and sending the digital signal data to the data processing and analysis module;

[0011] A data processing and analysis module is used to receive and store digital signal data of hydrogen storage equipment. After the digital signal data is processed by signal processing and data analysis algorithms, it is input into a health assessment model. The health assessment model uses a machine learning algorithm to classify and evaluate the hydrogen storage equipment, and outputs the health assessment results to the alarm and display module;

[0012] The alarm and display module is used to display the real-time status of the hydrogen storage equipment. The display content includes the real-time curve of the sensor module data, the three-dimensional model of the hydrogen storage equipment and the health assessment results. When the health assessment results output by the health assessment model reach the preset alarm threshold, an alarm is triggered.

[0013] Furthermore, the sensor module includes

[0014] Ultrasonic sensors, which are installed in an array on the outer wall of the hydrogen storage device and detect cracks and delamination in the hydrogen storage device by transmitting and receiving ultrasonic signals;

[0015] A strain gauge sensor is arranged at a key position of the hydrogen storage device and is used to measure in real time the strain caused by pressure changes during the hydrogen storage device charging and discharging process;

[0016] Temperature sensors, which are distributed on the surface and inside of the hydrogen storage device and are used to monitor temperature changes of the hydrogen storage device during operation;

[0017] An acoustic sensor is arranged around the valve to collect sound signals during the valve opening and closing process. The sound signals are used to analyze the changes in sound frequency and amplitude and establish a normal acoustic characteristic model.

[0018] The torque sensor is arranged on the operating component of the valve and is used for real-time monitoring whether the valve operating torque exceeds the normal operating torque range.

[0019] Furthermore, the data acquisition and transmission module includes

[0020] A programmable controller, wherein the programmable controller is a PLC controller, which is used to control the analog input and output unit, the digital input and output unit and the communication unit;

[0021] An analog input and output unit, which is used to receive analog signal data sent by the sensor module;

[0022] A digital input and output unit, which is used to convert analog signal data into digital signal data;

[0023] The communication unit is used for communicating with the sensor module and the data processing and analysis module.

[0024] Furthermore, the data processing and analysis module includes

[0025] A data storage unit, which is used to store the collected sensor module data;

[0026] Data analysis algorithm: The collected data are processed using signal processing and data analysis algorithms. For ultrasonic sensor data, a defect recognition algorithm based on wavelet transform is used to extract defect features from ultrasonic reflection signals. For strain gauge sensor data, stress analysis is performed through finite element model combined with measured strain data to evaluate the stress condition of hydrogen storage equipment. For temperature sensor data, a heat conduction model is used to analyze the impact of temperature distribution on the structure of hydrogen storage equipment.

[0027] Health assessment model: The health assessment model is established based on multi-parameter fusion. It uses a machine learning algorithm to classify and evaluate the health status of the hydrogen storage equipment according to the analysis results of the ultrasonic sensor data, strain gauge sensor data and temperature sensor data by the data analysis algorithm.

[0028] Furthermore, the processing process of the ultrasonic sensor data is as follows:

[0029] For the ultrasonic reflection signal, its continuous wavelet transform CWT is defined as:

[0030]

[0031] Among them, a is the scale factor used to scale the wavelet function; b is the translation factor used to move the wavelet function, ψ(t) is the wavelet basis function, is its complex conjugate;

[0032] In practical applications, the ultrasonic reflection signal received by the ultrasonic sensor is subjected to wavelet transformation; the wavelet coefficients at different scales reflect the characteristics of the signal at different frequencies and time positions; defects are identified by analyzing the changes in these wavelet coefficients;

[0033] When the ultrasonic reflection signal encounters a defect, the frequency component and amplitude of the signal will change, and these changes will be reflected in the sudden change of the wavelet coefficients;

[0034] Set a threshold T, when the absolute value of the wavelet coefficient |W f The area where (a, b)|>T corresponds to the defect position or the abnormal signal part; combined with the known wavelet coefficient characteristics when there is no defect, comparative analysis is performed to determine the defect type and size.

[0035] Furthermore, the processing process of the strain gauge sensor data is as follows:

[0036] Firstly, a finite element model of the hydrogen storage device is established, and the mesh is divided according to the geometric shape, elastic modulus and Poisson's ratio of the device; assuming that the strain value measured by the strain gauge sensor is ε ij (i, j = x, y, z), in the finite element model, the strain-displacement relationship satisfies the geometric equation:

[0037]

[0038] Among them, u i is the displacement component. By applying appropriate constraints and loads on the model boundary, the equilibrium equation is solved according to the principle of virtual work or the principle of minimum potential energy:

[0039] ∫ V σ ij δε ij dV-∫ S t i δu i dS=0

[0040] Among them, σ ij is the stress component, t i is the surface force on the boundary, δε ij and δu i It is virtual strain and virtual displacement; the measured strain data is substituted into the finite element model for back calculation to obtain the stress distribution inside the equipment, and then evaluate whether the equipment is safe.

[0041] Furthermore, the processing process of the temperature sensor data is as follows:

[0042] Based on the temperature data on the surface and inside of the equipment collected by the temperature sensor, the boundary conditions and initial conditions are determined, and the temperature distribution field inside the equipment is solved;

[0043]

[0044] Where ρ is the material density, c is the specific heat capacity, T is the temperature, t is the time, k is the thermal conductivity, and Q is the internal heat source, which is the heat generated by chemical reactions or friction in hydrogen storage devices;

[0045] Then, the thermal stress caused by temperature change is solved according to the thermal expansion coefficient α of the material;

[0046]

[0047] Where T0 is the initial temperature, δ ijIt is the Kronecker symbol, which is used to analyze the thermal stress distribution and evaluate the impact of temperature changes on the structural integrity of hydrogen storage equipment.

[0048] Furthermore, the evaluation process of the health evaluation model is as follows:

[0049] Assume that the ultrasonic sensor data is processed to obtain the feature vector x1, the strain gauge sensor data is processed to obtain the feature vector x2, and the temperature sensor data is processed to obtain the feature vector x3. These feature vectors are combined into a comprehensive feature vector X = [x1, x2, x3];

[0050] The health status of hydrogen storage equipment is divided into two categories: healthy (y = +1) and unhealthy (y = -1), and the weight vector w and bias b of an optimal hyperplane are solved to maximize the interval;

[0051] For the linearly separable case, the optimization problem can be expressed as:

[0052]

[0053]

[0054] Among them, ||w|| 2 =w T w is the feature vector of the sample, which is the corresponding category label;

[0055] In practical applications, the following functions are used to handle nonlinear problems;

[0056]

[0057] Through the training data set, the weight vector w and bias b are obtained;

[0058] When new sensor data is combined into a feature vector X new When , the value of the decision function is calculated:

[0059] f(X new )=sign(w·X new +b)

[0060] If f(X new )=+1, the hydrogen storage equipment is judged to be in a healthy state; if, f(X new )=-1, it is judged as unhealthy state.

[0061] A method for detecting the health status of hydrogen storage equipment in a hydrogen refueling station comprises the following steps:

[0062] S1. Initialization and calibration: After the hydrogen storage equipment is installed, the sensor module is initialized, including setting the transmission frequency and gain parameters of the ultrasonic sensor, and performing zero point calibration and range calibration on the strain gauge sensor and temperature sensor;

[0063] S2. Establish the initial health record of the hydrogen storage equipment: Through comprehensive non-destructive testing of the hydrogen storage equipment, obtain the data of the hydrogen storage equipment in its initial health state, and use it as the benchmark data of the health assessment model;

[0064] S3. Real-time monitoring: During the operation of the hydrogen refueling station, the sensor module continuously collects ultrasonic signals, strain signals and temperature signals of the hydrogen storage equipment; the data acquisition and transmission module transmits the data to the data processing and analysis module of the remote monitoring center at the set time interval;

[0065] S4. Data processing and analysis: The data processing and analysis module uses data analysis algorithms to process the real-time data of the sensor module, extract defect information from the ultrasonic signal, calculate the stress change measured by the strain gauge, and analyze the temperature distribution feedback from the temperature sensor. The health assessment model evaluates the real-time health status of the hydrogen storage equipment based on the real-time data and benchmark data;

[0066] S5. When the health assessment model determines that the health status of the hydrogen storage equipment is abnormal, the alarm and display module immediately activates the alarm mechanism; at the same time, the data processing and analysis module further analyzes the abnormal data, combines historical data and expert systems, tries to determine the type and location of the fault, and provides detailed fault diagnosis information for maintenance personnel.

[0067] In summary, the present invention has the following beneficial effects:

[0068] By setting ultrasonic sensors, strain gauge sensors and temperature sensors at different locations of the hydrogen storage device, internal micro cracks, scratches, and micro abnormalities can be accurately detected. At the same time, by obtaining the data of the hydrogen storage device in its initial health state and using it as the baseline data of the health assessment model; then during real-time detection, the health assessment model evaluates the real-time health status of the hydrogen storage device based on the real-time data and the baseline data. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a framework diagram of the health status detection system described in the present invention.

[0070] Figure 2 This is a structural diagram of the health status detection system of the present invention.

[0071] Figure 3 It is a distribution diagram of the sensor modules described in the present invention.

[0072] Figure 4 It is a flow chart of the health status detection described in the present invention. DETAILED DESCRIPTION

[0073] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further described below in conjunction with illustrations and specific embodiments.

[0074] like Figures 1 to 3 As shown, the present invention proposes a health status detection system for hydrogen storage equipment in a hydrogen refueling station, comprising:

[0075] The sensor module is arranged on the hydrogen storage device of the hydrogen refueling station, and is used to detect the hydrogen storage device in real time, and send the detected analog signal data to the data acquisition and transmission module;

[0076] A data acquisition and transmission module, which is respectively connected to the sensor module and the data processing and analysis module for converting the analog signal data sent by the sensor module into digital signal data and sending the digital signal data to the data processing and analysis module;

[0077] A data processing and analysis module is used to receive and store digital signal data of hydrogen storage equipment. After the digital signal data is processed by signal processing and data analysis algorithms, it is input into a health assessment model. The health assessment model uses a machine learning algorithm to classify and evaluate the hydrogen storage equipment, and outputs the health assessment results to the alarm and display module;

[0078] The alarm and display module is used to display the real-time status of the hydrogen storage equipment. The display content includes the real-time curve of the sensor module data, the three-dimensional model of the hydrogen storage equipment and the health assessment results. When the health assessment results output by the health assessment model reach the preset alarm threshold, an alarm is triggered.

[0079] Example

[0080] 1. System composition:

[0081] 1. Sensor placement

[0082] Ultrasonic sensor array: Installed on the outer wall of the hydrogen storage tank, distributed in a grid pattern, used to transmit and receive ultrasonic signals. These sensors can cover most of the surface of the hydrogen storage tank to detect possible defects such as cracks and delamination in the hydrogen storage tank wall. The frequency and sensitivity of the ultrasonic sensor are specially designed to detect tiny internal structural changes.

[0083] Strain gauge sensor: attached to key parts of the hydrogen storage tank, such as the equator, head, and welds of the tank. The strain gauge can measure the strain caused by pressure changes in the hydrogen storage tank during the hydrogen filling and discharging process in real time. High-precision and high-sensitivity strain gauges are used, and their measurement range and accuracy meet the strain measurement requirements of hydrogen storage tanks under normal working and extreme working conditions.

[0084] Temperature sensors: distributed on the surface and inside of the hydrogen storage tank (through a special installation method to ensure that it does not affect the structure and safety of the hydrogen storage tank). Temperature sensors are used to monitor the temperature changes of the hydrogen storage tank during operation, because temperature has an important influence on the material properties and structural stability of the hydrogen storage tank. These temperature sensors have the characteristics of fast response and high precision, and can feedback temperature data in real time.

[0085] Acoustic monitoring: highly sensitive acoustic sensors are placed around the valve to collect sound signals during the valve opening and closing process. The sound frequency and amplitude changes are analyzed to establish a normal acoustic characteristic model. When the signal characteristics deviate from the model to a certain extent, it is determined that the valve may have a fault, such as wear, internal leakage, etc.

[0086] Torque monitoring: Install a torque sensor on the operating part of the valve to monitor the valve operating torque in real time. The normal operating torque has a certain range. If it exceeds the range, it indicates that the valve may be stuck or have sealing problems.

[0087] 2. Data acquisition and transmission module

[0088] Data acquisition unit: The data acquisition module of this system uses Siemens PLC controller, IO module and communication card, which is connected to each sensor and is responsible for collecting the reflection signal of ultrasonic sensor, strain signal of strain gauge, temperature signal of temperature sensor, acoustic and torque signal. The data acquisition unit has high sampling rate and high-precision analog-to-digital conversion function, which can accurately convert analog signals into digital signals.

[0089] The hardware modules mainly include: programmable controller, analog input and output modules (AI, AO), digital input and output modules (DI, DO) and communication cards (Modbus, TCP / IP, Profinet).

[0090] 3. Data Processing and Analysis

[0091] Data storage unit: A large-capacity data storage device is equipped in the remote monitoring center to store the collected historical data. The data storage structure is reasonably designed to facilitate data query, retrieval and backup, providing sufficient data support for subsequent data analysis and health assessment.

[0092] Data analysis algorithm: The collected data is processed using advanced signal processing and data analysis algorithms. For ultrasonic sensor data, a defect recognition algorithm based on wavelet transform is used to extract defect features from complex ultrasonic reflection signals; for strain gauge data, stress analysis is performed through finite element model combined with measured strain data to evaluate the stress condition of the hydrogen storage tank; for temperature data, a heat conduction model is used to analyze the impact of temperature distribution on the structure of the hydrogen storage tank.

[0093] Health assessment model: A health assessment model for hydrogen storage tanks based on multi-parameter fusion is established. The model comprehensively considers the results of ultrasonic testing, strain analysis results and temperature effects, and uses machine learning algorithms (such as neural networks, support vector machines, etc.) to classify and evaluate the health status of hydrogen storage tanks. The health status is divided into different levels, such as normal, slight damage, moderate damage, severe damage, etc.

[0094] The processing process of the ultrasonic sensor data is as follows:

[0095] For the ultrasonic reflection signal, its continuous wavelet transform CWT is defined as:

[0096]

[0097] Among them, a is the scale factor used to scale the wavelet function; b is the translation factor used to move the wavelet function, ψ(t) is the wavelet basis function, is its complex conjugate;

[0098] In practical applications, the ultrasonic reflection signal received by the ultrasonic sensor is subjected to wavelet transformation; the wavelet coefficients at different scales reflect the characteristics of the signal at different frequencies and time positions; defects are identified by analyzing the changes in these wavelet coefficients;

[0099] When the ultrasonic reflection signal encounters a defect, the frequency component and amplitude of the signal will change, and these changes will be reflected in the sudden change of the wavelet coefficients;

[0100] Set a threshold T, when the absolute value of the wavelet coefficient |W f The area where (a, b)|>T corresponds to the defect position or the abnormal signal part; combined with the known wavelet coefficient characteristics when there is no defect, comparative analysis is performed to determine the defect type and size.

[0101] The processing process of the strain gauge sensor data is as follows:

[0102] Firstly, a finite element model of the hydrogen storage device is established, and the mesh is divided according to the geometric shape, elastic modulus and Poisson's ratio of the device; assuming that the strain value measured by the strain gauge sensor is ε ij (i, j = x, y, z), in the finite element model, the strain-displacement relationship satisfies the geometric equation:

[0103]

[0104] Among them, u i is the displacement component. By applying appropriate constraints and loads on the model boundary, the equilibrium equation is solved according to the principle of virtual work or the principle of minimum potential energy:

[0105]

[0106] Among them, σ ij is the stress component, t i is the surface force on the boundary, δε ij and δu i It is virtual strain and virtual displacement; the measured strain data is substituted into the finite element model for back calculation to obtain the stress distribution inside the equipment, and then evaluate whether the equipment is safe.

[0107] The processing process of the temperature sensor data is as follows:

[0108] Based on the temperature data on the surface and inside of the equipment collected by the temperature sensor, the boundary conditions and initial conditions are determined, and the temperature distribution field inside the equipment is solved;

[0109]

[0110] Where ρ is the material density, c is the specific heat capacity, T is the temperature, t is the time, k is the thermal conductivity, and Q is the internal heat source, which is the heat generated by chemical reactions or friction in hydrogen storage devices;

[0111] Then, the thermal stress caused by temperature change is solved according to the thermal expansion coefficient α of the material;

[0112]

[0113] Where T0 is the initial temperature, δ ij It is the Kronecker symbol, which is used to analyze the thermal stress distribution and evaluate the impact of temperature changes on the structural integrity of hydrogen storage equipment.

[0114] The evaluation process of the health assessment model is as follows:

[0115] Assume that the ultrasonic sensor data is processed to obtain the feature vector x1, the strain gauge sensor data is processed to obtain the feature vector x2, and the temperature sensor data is processed to obtain the feature vector x3. These feature vectors are combined into a comprehensive feature vector X = [x1, x2, x3];

[0116] The health status of hydrogen storage equipment is divided into two categories: healthy (y = +1) and unhealthy (y = -1), and the weight vector w and bias b of an optimal hyperplane are solved to maximize the interval;

[0117] For the linearly separable case, the optimization problem can be expressed as:

[0118]

[0119] Among them, ||w|| 2 =w T w is the feature vector of the sample, and is the corresponding category label;

[0120] In practical applications, the following functions are used to handle nonlinear problems;

[0121]

[0122] Through the training data set, the weight vector w and bias b are obtained;

[0123] When new sensor data is combined into a feature vector X new When , the value of the decision function is calculated:

[0124] f(X new )=sign(w·X new +b)

[0125] If f(X new )=+1, the hydrogen storage equipment is judged to be in a healthy state; if, f(X new )=-1, it is judged as unhealthy state.

[0126] 4. Alarm and display module

[0127] Alarm unit: When the health assessment model determines that the health status of the hydrogen storage tank and valve components reaches the preset alarm threshold, an alarm is triggered. The alarm methods include sound and light alarm, SMS notification, push notification to the monitoring personnel's mobile terminal, etc., to ensure that relevant personnel can be informed of abnormal conditions of the hydrogen storage tank and valve components in a timely manner.

[0128] Display interface: An intuitive display interface is set up in the remote monitoring center to display the real-time health status of hydrogen storage tanks and valve components in a graphical and visual way. The display content includes real-time curves of sensor data, three-dimensional models of hydrogen storage tanks and valve components with abnormal locations marked, health assessment results, etc., which makes it convenient for monitoring personnel to quickly understand the status of hydrogen storage tanks and valve components.

[0129] like Figure 4 As shown, a method for detecting the health status of hydrogen storage equipment in a hydrogen refueling station comprises the following steps:

[0130] S1. Initialization and calibration: After the hydrogen storage equipment is installed, the sensor module is initialized, including setting the transmission frequency and gain parameters of the ultrasonic sensor, and performing zero point calibration and range calibration on the strain gauge sensor and temperature sensor;

[0131] S2. Establish the initial health record of the hydrogen storage equipment: Through comprehensive non-destructive testing of the hydrogen storage equipment, obtain the data of the hydrogen storage equipment in its initial health state, and use it as the benchmark data of the health assessment model;

[0132] S3. Real-time monitoring: During the operation of the hydrogen refueling station, the sensor module continuously collects ultrasonic signals, strain signals and temperature signals of the hydrogen storage equipment; the data acquisition and transmission module transmits the data to the data processing and analysis module of the remote monitoring center at the set time interval;

[0133] S4. Data processing and analysis: The data processing and analysis module uses data analysis algorithms to process the real-time data of the sensor module, extract defect information from the ultrasonic signal, calculate the stress change measured by the strain gauge, and analyze the temperature distribution feedback from the temperature sensor. The health assessment model evaluates the real-time health status of the hydrogen storage equipment based on the real-time data and benchmark data;

[0134] S5. When the health assessment model determines that the health status of the hydrogen storage equipment is abnormal, the alarm and display module immediately activates the alarm mechanism; at the same time, the data processing and analysis module further analyzes the abnormal data, combines historical data and expert systems, tries to determine the type and location of the fault, and provides detailed fault diagnosis information for maintenance personnel.

[0135] In this document, the directions or positional relationships indicated by terms such as "up", "down", "front", "back", "left", "right", "top", "bottom", "inside", "outside", "vertical", and "horizontal" are based on the directions or positional relationships shown in the accompanying drawings and are only for the clarity of expressing the technical solutions and the convenience of description, and therefore should not be understood as limitations of the present invention.

[0136] In this document, the terms "comprises," "comprising," or any other variations thereof, are intended to cover a non-exclusive inclusion of elements other than those listed and may also include additional elements not expressly listed.

[0137] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A health status detection system for hydrogen storage equipment in a hydrogen refueling station, characterized in that: It includes a sensor module, which is arranged on the hydrogen storage device of the hydrogen refueling station, and is used to detect the hydrogen storage device in real time, and send the detected analog signal data to the data acquisition and transmission module; A data acquisition and transmission module, which is respectively connected to the sensor module and the data processing and analysis module for converting the analog signal data sent by the sensor module into digital signal data and sending the digital signal data to the data processing and analysis module; A data processing and analysis module is used to receive and store digital signal data of hydrogen storage equipment. After the digital signal data is processed by signal processing and data analysis algorithms, it is input into a health assessment model. The health assessment model uses a machine learning algorithm to classify and evaluate the hydrogen storage equipment, and outputs the health assessment results to the alarm and display module; The alarm and display module is used to display the real-time status of the hydrogen storage equipment. The display content includes the real-time curve of the sensor module data, the three-dimensional model of the hydrogen storage equipment and the health assessment results. When the health assessment results output by the health assessment model reach the preset alarm threshold, an alarm is triggered.

2. The health status detection system for hydrogen storage equipment in a hydrogen refueling station according to claim 1, characterized in that: The sensor module includes Ultrasonic sensors, which are installed in an array on the outer wall of the hydrogen storage device and detect cracks and delamination in the hydrogen storage device by transmitting and receiving ultrasonic signals; A strain gauge sensor is arranged at a key position of the hydrogen storage device and is used to measure in real time the strain caused by pressure changes during the hydrogen storage device charging and discharging process; Temperature sensors, which are distributed on the surface and inside of the hydrogen storage device and are used to monitor temperature changes of the hydrogen storage device during operation; An acoustic sensor is arranged around the valve to collect sound signals during the valve opening and closing process. The sound signals are used to analyze the changes in sound frequency and amplitude and establish a normal acoustic characteristic model. The torque sensor is arranged on the operating component of the valve and is used for real-time monitoring whether the valve operating torque exceeds the normal operating torque range.

3. The health status detection system for hydrogen storage equipment in a hydrogen refueling station according to claim 1, characterized in that: The data acquisition and transmission module includes A programmable controller, wherein the programmable controller is a PLC controller, which is used to control the analog input and output unit, the digital input and output unit and the communication unit; An analog input and output unit, which is used to receive analog signal data sent by the sensor module; A digital input and output unit, which is used to convert analog signal data into digital signal data; The communication unit is used to communicate with the sensor module and the data processing and analysis module.

4. The health status detection system for hydrogen storage equipment in a hydrogen refueling station according to claim 1, characterized in that: The data processing and analysis module includes A data storage unit, which is used to store the collected sensor module data; Data analysis algorithm: The collected data are processed using signal processing and data analysis algorithms. For ultrasonic sensor data, a defect recognition algorithm based on wavelet transform is used to extract defect features from ultrasonic reflection signals. For strain gauge sensor data, stress analysis is performed through finite element model combined with measured strain data to evaluate the stress condition of hydrogen storage equipment. For temperature sensor data, a heat conduction model is used to analyze the impact of temperature distribution on the structure of hydrogen storage equipment. Health assessment model: The health assessment model is established based on multi-parameter fusion. It uses a machine learning algorithm to classify and evaluate the health status of the hydrogen storage equipment according to the analysis results of the ultrasonic sensor data, strain gauge sensor data and temperature sensor data by the data analysis algorithm.

5. The health status detection system for hydrogen storage equipment in a hydrogen refueling station according to claim 4, characterized in that: The processing process of the ultrasonic sensor data is as follows: For the ultrasonic reflection signal, its continuous wavelet transform CWT is defined as: Among them, a is the scale factor used to scale the wavelet function; b is the translation factor used to move the wavelet function, ψ(t) is the wavelet basis function, is its complex conjugate; In practical applications, the ultrasonic reflection signal received by the ultrasonic sensor is subjected to wavelet transformation; the wavelet coefficients at different scales reflect the characteristics of the signal at different frequencies and time positions; defects are identified by analyzing the changes in these wavelet coefficients; When the ultrasonic reflection signal encounters a defect, the frequency component and amplitude of the signal will change, and these changes will be reflected in the sudden change of the wavelet coefficients; Set a threshold T, when the absolute value of the wavelet coefficient |W f The area where (a, b)|>T corresponds to the defect position or the abnormal signal part; combined with the known wavelet coefficient characteristics when there is no defect, comparative analysis is performed to determine the defect type and size.

6. The health status detection system for hydrogen storage equipment in a hydrogen refueling station according to claim 4, characterized in that: The processing process of the strain gauge sensor data is as follows: Firstly, a finite element model of the hydrogen storage device is established, and the mesh is divided according to the geometric shape, elastic modulus and Poisson's ratio of the device; assuming that the strain value measured by the strain gauge sensor is ε ij (i, j = x, y, z), in the finite element model, the strain-displacement relationship satisfies the geometric equation: Among them, u i is the displacement component. By applying appropriate constraints and loads on the model boundary, the equilibrium equation is solved according to the principle of virtual work or the principle of minimum potential energy: ∫ V s ij not ij dV-∫ s t i you i dS=0 Among them, σ ij is the stress component, t i is the surface force on the boundary, δε ij and δu i It is virtual strain and virtual displacement; the measured strain data is substituted into the finite element model for back calculation to obtain the stress distribution inside the equipment, and then evaluate whether the equipment is safe.

7. The health status detection system for hydrogen storage equipment in a hydrogen refueling station according to claim 4, characterized in that: The processing process of the temperature sensor data is as follows: Based on the temperature data on the surface and inside of the equipment collected by the temperature sensor, the boundary conditions and initial conditions are determined, and the temperature distribution field inside the equipment is solved; Where ρ is the material density, c is the specific heat capacity, T is the temperature, t is the time, k is the thermal conductivity, and Q is the internal heat source, which is the heat generated by chemical reactions or friction in hydrogen storage devices; Then, the thermal stress caused by temperature change is solved according to the thermal expansion coefficient α of the material; Where T0 is the initial temperature, δ ij It is the Kronecker symbol, which is used to analyze the thermal stress distribution and evaluate the impact of temperature changes on the structural integrity of hydrogen storage equipment.

8. The health status detection system for hydrogen storage equipment in a hydrogen refueling station according to claim 4, characterized in that: The evaluation process of the health assessment model is as follows: Assume that the ultrasonic sensor data is processed to obtain the feature vector x1, the strain gauge sensor data is processed to obtain the feature vector x2, and the temperature sensor data is processed to obtain the feature vector x3. These feature vectors are combined into a comprehensive feature vector X = [x1, x2, x3]; The health status of hydrogen storage equipment is divided into two categories: healthy (y = +1) and unhealthy (y = -1), and the weight vector w and bias b of an optimal hyperplane are solved to maximize the interval; For the linearly separable case, the optimization problem can be expressed as: Among them, ||W|| 2 =w T w is the feature vector of the sample, and is the corresponding category label; In practical applications, the following functions are used to handle nonlinear problems; Through the training data set, the weight vector w and bias b are obtained; When new sensor data is combined into a feature vector X new When , the value of the decision function is calculated: f(X new )=sign(w·X new +b) If f(X new )=+1, the hydrogen storage equipment is judged to be in a healthy state; if, f(X new )=-1, it is judged as unhealthy state.

9. A method for detecting the health status of hydrogen storage equipment in a hydrogen refueling station, comprising a health status detection system as claimed in any one of claims 1 to 8, characterized in that: The steps include: S1. Initialization and calibration: After the hydrogen storage equipment is installed, the sensor module is initialized, including setting the transmission frequency and gain parameters of the ultrasonic sensor, and performing zero point calibration and range calibration on the strain gauge sensor and temperature sensor; S2. Establish the initial health record of the hydrogen storage equipment: Through comprehensive non-destructive testing of the hydrogen storage equipment, obtain the data of the hydrogen storage equipment in its initial health state, and use it as the benchmark data of the health assessment model; S3. Real-time monitoring: During the operation of the hydrogen refueling station, the sensor module continuously collects ultrasonic signals, strain signals and temperature signals of the hydrogen storage equipment; the data acquisition and transmission module transmits the data to the data processing and analysis module of the remote monitoring center at the set time interval; S4. Data processing and analysis: The data processing and analysis module uses data analysis algorithms to process the real-time data of the sensor module, extract defect information from the ultrasonic signal, calculate the stress change measured by the strain gauge, and analyze the temperature distribution feedback from the temperature sensor. The health assessment model evaluates the real-time health status of the hydrogen storage equipment based on the real-time data and benchmark data; S5. When the health assessment model determines that the health status of the hydrogen storage equipment is abnormal, the alarm and display module immediately activates the alarm mechanism; at the same time, the data processing and analysis module further analyzes the abnormal data, combines historical data and expert systems, tries to determine the type and location of the fault, and provides detailed fault diagnosis information for maintenance personnel.

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