Device for testing stress and temperature of thick wall of energy storage cylinder for compressing air

Abstract

The invention relates to the technical field of stress and temperature testing devices, in particular to an energy storage cylinder thick wall stress and temperature testing device for compressing air, which comprises an air tank, a support frame and a control system, the output of the air tank is connected with a first pipeline, and a second pipeline is arranged outside the support frame; a gas booster pump is arranged between the first pipeline and the second pipeline, the input end of the gas booster pump is fixedly connected with the first pipeline, the output end of the gas booster pump is fixedly connected with the second pipeline, one end of the second pipeline is fixedly connected with a sealing cover, and multiple sets of connecting bolts are arranged in the sealing cover in a penetrating mode; a thick-wall cylinder is arranged on the supporting frame, a plurality of sets of strain gauges and thermocouples are installed at the end of the thick-wall cylinder, stress and temperature detection is conducted through the strain gauges and the thermocouples, and through arrangement of the control system, stress and inflation flow can be monitored and controlled cooperatively at the same time.

Description

Technical Field

[0001] The invention relates to the technical field of stress and temperature testing devices, in particular to a thick-wall stress and temperature testing device for an energy storage cylinder used for compressed air. Background Art

[0002] The compressed air energy storage cylinder thick wall stress and temperature testing device is a key equipment for monitoring the performance of compressed air energy storage cylinders. Structurally, it is equipped with a variety of high-precision sensors. Stress sensors are installed at various locations on the thick wall of the cylinder. Based on the principle of resistance strain, they can capture the stress changes on the thick wall of the cylinder during the charging and discharging of compressed air in real time, and convert the mechanical strain into an electrical signal output. The temperature sensor uses thermocouples or thermal resistors to accurately measure the temperature of the cylinder wall and the air inside. From a functional perspective, the safety and reliability of the cylinder under different working conditions can be evaluated by continuously monitoring stress and temperature.

[0003] In the existing technology, the thick wall stress and temperature testing device of the energy storage cylinder cannot monitor and control the stress and the inflation flow rate in a coordinated manner. The two are performed separately. During the compressed air energy storage process, the thick wall of the cylinder will be subjected to different degrees of stress due to the change of inflation pressure. If the stress exceeds the bearing limit of the material, it may cause serious consequences such as cracks, deformation or even rupture of the cylinder. Summary of the invention

[0004] In view of the technical problem that the energy storage cylinder thick wall stress and temperature testing device used in the prior art cannot coordinately monitor and control stress and inflation flow, the present invention provides an energy storage cylinder thick wall stress and temperature testing device for compressed air.

[0005] The technical solution adopted by the present invention is: a thick-wall stress and temperature testing device for an energy storage cylinder for compressed air, comprising a gas tank, a support frame and a control system, wherein the output of the gas tank is connected to a first pipeline, a second pipeline is arranged on the outside of the support frame, a gas pressure pump is arranged between the first pipeline and the second pipeline, the input end of the gas pressure pump is fixedly connected to the first pipeline, the output end of the gas pressure pump is fixedly connected to the second pipeline, one end of the second pipeline is fixedly connected to a sealing cover, a plurality of groups of connecting bolts are penetrated through the sealing cover, a thick-walled cylinder is arranged on the support frame, a plurality of groups of strain gauges and thermocouples are installed on the end of the thick-walled cylinder, and the groups of strain gauges and thermocouples are electrically coupled to the control system.

[0006] In one embodiment, a first valve is installed in the first pipeline, a second valve and a pressure gauge are installed in the second pipeline, and a pressure relief valve is also installed in the second pipeline.

[0007] In one embodiment, the outside of the support frame is fixedly connected to a ring frame, the outside of the ring frame is fixedly connected to multiple groups of air bags, the outside of the second pipe is fixedly connected to a third pipe, the third pipe is fixedly connected to a third valve, one end of the third pipe is fixedly connected to a fourth pipe, and the fourth pipe is fixedly connected to the air bags.

[0008] In one embodiment, the outside of the annular frame is fixedly connected to a connecting frame, the outside of the connecting frame is fixedly connected to multiple groups of fixed blocks, a piston groove is provided in the fixed block, a piston block is slidably connected in the piston groove, a spring is connected between the piston block and the piston groove, a limiting rod is fixedly connected to the bottom of the piston block, a sixth pipe is fixedly connected between two adjacent fixed blocks, the sixth pipe is communicated with the piston groove, the outside of the third pipe is fixedly connected to a fifth pipe, one end of the fifth pipe is fixedly connected to one of the fixed blocks.

[0009] In one embodiment, the control system includes a data acquisition unit, an inflation flow control unit, an early warning unit and a control unit.

[0010] In one of the embodiments, the data acquisition module includes a stress analysis module for thick-walled cylinders and a stress and strain monitoring submodule;

[0011] Among them, the thick-walled cylinder stress analysis module is based on the elastic mechanics theory. The stress distribution of the thick-walled cylinder under the action of internal pressure follows the Lame formula:

[0012] ;

[0013] ;

[0014] Where: The radial stress is , is the pressure inside the thick-walled cylinder, is the external pressure of the thick-walled cylinder, is the inner radius of the thick-walled cylinder, is the outer radius of the thick-walled cylinder;

[0015] When considering the influence of temperature gradient, a thermal stress correction term is introduced:

[0016] ;

[0017] Where: is the thermal stress caused by temperature change, is the linear expansion coefficient of the material, which reflects the expansion or contraction characteristics of the material when the temperature changes; is the elastic modulus of the material, which indicates the material's ability to resist elastic deformation; is the Poisson's ratio of the material, which describes the relationship between the lateral strain and the longitudinal strain of the material when it is subjected to stress; is the temperature change;

[0018] The stress strain monitoring submodule includes collecting the output voltage of the strain gauge, and the calculation formula is:

[0019] ;

[0020] in, To calculate the output voltage of the strain gauge when using a four-arm full-bridge circuit, is the sensitivity coefficient of the strain gauge, which reflects the sensitivity of the strain gauge to strain; It is the relative change of the resistance of the strain gauge, which is proportional to the strain of the object being measured; is the excitation voltage, that is, the voltage applied to the strain gauge bridge.

[0021] In one embodiment, the inflation flow control unit includes a thermodynamic coupling model, a pneumatic execution module and a pressure closed-loop control module;

[0022] The thermodynamic coupling model is used to calculate the rate of change of the internal energy of the air in the thick-walled cylinder, specifically as follows:

[0023] ;

[0024] in, It represents the mass m of air in the thick-walled cylinder multiplied by the specific heat capacity at constant volume. Multiply by the rate of change of temperature over time , which is the rate of change of the internal energy of the air in the thick-walled cylinder; represents the convective heat transfer between the intake air and the air in the thick-walled cylinder, is the convective heat transfer coefficient, is the heat exchange area, is the intake air temperature, is the air temperature in the thick-walled cylinder; It represents the heat loss rate of thick-walled cylinder to the outside world;

[0025] Combined with the ideal gas state equation: ;

[0026] in is the gas pressure, is the gas volume, is the gas mass, is the gas constant, is the gas temperature;

[0027] The pneumatic actuator module uses the proportional valve flow characteristic equation to calculate the inflation flow, and the characteristic equation is as follows:

[0028] ;

[0029] in, is the flow through the first valve, is the flow coefficient of the first valve, reflecting the flow capacity of the first valve; is the pressure difference before and after the first valve, is the density of air;

[0030] The pressure closed-loop control module estimates the state of the system based on the robust control algorithm formula of the state observer:

[0031] ;

[0032] ;

[0033] in is the derivative of the state estimate, is the state matrix of the system, is the input matrix, is the control input, is the observer gain matrix, is the actual output of the system, is an estimate of the system output.

[0034] In one of the embodiments, the early warning unit includes a reliability assessment module and a threshold early warning module;

[0035] The reliability assessment module adopts the fault tree analysis method, and the top event probability is calculated as follows:

[0036] ;

[0037] To calculate the top event probability of the fault tree, Bottom event The probability of occurrence, is the number of bottom events; this formula assumes that the bottom events are independent of each other;

[0038] The threshold warning module adopts the stress safety threshold calculation formula:

[0039] ;

[0040] is the stress safety threshold, where is the strength of the material, that is, the maximum stress that the material can withstand; is the safety factor.

[0041] In one embodiment, the control method of the control unit is as follows:

[0042] First, based on deep neural network predictive control (DNN-MPC), its objective function is:

[0043] ;

[0044] in, For the The predicted stress value at time is the reference value of stress; For the prediction time domain; For the Control the input change at all times. To control the time domain; is the weighting coefficient, which is used to balance the output error and the weight of the control input change;

[0045] At the same time, the output of the controller in the control unit is calculated by the fuzzy adaptive PID control algorithm formula;

[0046] ;

[0047] in, is the output of the controller, is the proportionality coefficient, is the integration coefficient, is the differential coefficient; For the The error at the moment, that is, the difference between the set value and the actual value; is the integral of the error, reflecting the cumulative effect of the error; is the differential of the error;

[0048] Secondly, based on the digital twin system, stress and temperature control equations are established;

[0049] ;

[0050] ;

[0051] in is the stress diffusion tensor, represents the diffusion term of stress, and f is the source term of stress; is the thermal diffusion coefficient, is the Laplace operator of temperature, which indicates the diffusion of temperature. is the heat source term;

[0052] Subsequently, the error is calculated based on the error correction equation;

[0053] ;

[0054] For physical experiment data Simulating data with virtual models The error between represents the 2-norm, which is the square root of the sum of the squares of the vector elements;

[0055] Next, based on the dynamic adjustment formula of the security threshold, dynamically adjust the security threshold ;

[0056] ;

[0057] in, For the The safety threshold at the moment, is the learning rate, which is used to control the step size of the safety threshold adjustment; is the reward function, which gives the corresponding reward value according to the state of the system;

[0058] Finally, the reward function formula is used according to the actual stress With safety threshold The size relationship gives the reward value;

[0059] ;

[0060] When the actual stress is less than the safety threshold, the reward value is +1, indicating that the system is in a safe state; when the actual stress is greater than or equal to the safety threshold, the reward value is -1, indicating that the system is in a dangerous state.

[0061] The beneficial effects of the present invention are:

[0062] 1. Compared with the prior art, in the present invention, a thick-walled cylinder is placed on a support frame, and then one end of the second pipe is inserted into the thick-walled cylinder. The sealing cover is firmly mounted on the thick-walled cylinder by connecting the thick-walled cylinder with a connecting bolt, and the gas is pressurized by a gas booster pump and then transported into the thick-walled cylinder. Finally, stress and temperature detection can be performed by strain gauges and thermocouples. Through the setting of the control system, stress and inflation flow can be coordinated and controlled at the same time. Through coordinated monitoring and control, when it is monitored that the stress is close to or reaches the safety threshold, the inflation flow can be adjusted in time to reduce the pressure change rate, thereby reducing stress concentration, avoiding damage to the equipment due to excessive stress, and extending the service life of the equipment.

[0063] 2. Compared with the prior art, the present invention can analyze the stress distribution of thick-walled cylinders based on the Lame formula of elastic mechanics, introduce thermal stress correction terms considering the influence of temperature gradient; combine the thermodynamic energy conservation equation and the ideal gas state equation to construct a thermodynamic coupling model of the inflation process; adopt fuzzy adaptive PID The control algorithm can dynamically adjust the control parameters according to the error and the error change rate, collect stress-strain and temperature field data respectively through strain gauges and distributed optical fiber temperature measurement systems, use signal conditioning circuits and analog-to-digital conversion for data preprocessing, and discretize the temperature data of the heat conduction equation. Through deep neural network predictive control (DNN-MPC), the future state can be predicted through the offline trained DNN model, and the control input sequence can be optimized in a rolling manner to achieve multi-parameter collaborative control. By constructing a two-way mapping between the virtual model and the real-time data of the physical experiment, the error correction equation can be used to improve the model accuracy, and the safety threshold can be dynamically adjusted through reinforcement learning. Rewards or penalties can be given according to whether the stress exceeds the safety range. Experimental tests within a specific internal pressure and temperature range are possible. In the existing technology, there may only be monitoring or control of a single physical quantity, while this system can simultaneously monitor and control the stress and inflation flow of the thick wall of the compressed air energy storage cylinder. Through the multi-parameter coupling control algorithm, the mutual influence between stress and flow is comprehensively considered to achieve more accurate experimental process control and improve the reliability and accuracy of the experimental results.

[0064] 3. Compared with the prior art, the predictive control (DNN-MPC) algorithm based on deep neural network in the present invention can more accurately predict the future state of the system and adjust the control strategy in advance, thereby significantly improving the control accuracy and response speed. By introducing digital twin technology, two-way mapping and error correction of real-time data between virtual models and physical experiments are realized, which enables the experimental process to be rehearsed and optimized in a virtual environment, and potential problems can be discovered and adjusted in time, greatly shortening the experimental cycle and cost. Traditional safety monitoring usually uses fixed threshold warnings, which are difficult to adapt to dynamic changes in the experimental process. Through the adaptive safety boundary mechanism of reinforcement learning, the safety threshold can be dynamically adjusted according to the real-time data of the experiment, and potential safety risks can be discovered and handled in time, providing more reliable safety protection for experimental personnel and equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a schematic diagram of the structure of the present invention;

[0066] Figure 2 It is a schematic diagram of the structure of the thick-walled cylinder test in the present invention;

[0067] Figure 3 It is a structural schematic diagram of another viewing angle of the thick-walled cylinder test in the present invention;

[0068] Figure 4 It is a structural schematic diagram of the support frame in the present invention;

[0069] Figure 5 yes Figure 4 Schematic diagram of the enlarged structure of the A area in the middle;

[0070] Figure 6 It is a schematic diagram of the cross-sectional structure of the fixing block in the present invention.

[0071] The markings in the figure are:

[0072] 1. Gas tank; 2. First valve; 3. First pipeline; 4. Gas booster pump; 5. Second pipeline; 6. Pressure gauge; 7. Second valve; 8. Pressure relief valve; 9. Third pipeline; 10. Third valve; 11. Fourth pipeline; 12. Fifth pipeline; 13. Airbag; 14. Sealing cover; 15. Connecting bolt; 16. Support frame; 17. Strain gauge; 18. Thermocouple; 19. Ring frame; 20. Connecting frame; 21. Fixed block; 22. Sixth pipeline; 23. Piston groove; 24. Spring; 25. Piston block; 26. Limit rod; 27. Thick-walled cylinder. DETAILED DESCRIPTION

[0073] In the description of the present invention, it should be noted that the orientations or positional relationships indicated by terms such as “front”, “up”, “down”, “left”, “right”, “vertical” and “horizontal” are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0074] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0075] The following is combined with Figure 1-6 The present invention is further described.

[0076] Embodiment 1:

[0077] In order to solve the problems existing in the background technology, the present application proposes the following technical solutions: a thick-wall stress and temperature testing device for an energy storage cylinder for compressed air, comprising a gas tank 1, a support frame 16 and a control system, wherein the output of the gas tank 1 is connected to a first pipe 3, a second pipe 5 is provided on the outside of the support frame 16, a gas booster pump 4 is provided between the first pipe 3 and the second pipe 5, an input end of the gas booster pump 4 is fixedly connected to the first pipe 3, and an output end of the gas booster pump 4 is fixedly connected to the second pipe 5, and the gas is pressurized to a set pressure by the gas booster pump and then transported to the thick-wall cylinder 27.

[0078] In a further design, one end of the second pipe 5 is fixedly connected to a sealing cover 14, and one end of the second pipe 5 is also fixedly connected to a pressure sensor for measuring the pressure inside the thick-walled cylinder 27. A plurality of groups of connecting bolts 15 are penetrated through the sealing cover 14, and one end of the second pipe 5 is inserted into the thick-walled cylinder 27. The sealing cover 14 is firmly installed on the outside of the thick-walled cylinder 27 through the connection between the connecting bolts 15 and the thick-walled cylinder 27.

[0079] Among them, a thick-walled cylinder 27 is provided on the support frame 16, and multiple sets of strain gauges 17 and thermocouples 18 are installed at the end of the thick-walled cylinder 27. The sets of strain gauges 17 and thermocouples 18 are electrically coupled to the controller in the control system, and stress and temperature detection are performed through the strain gauges 17 and thermocouples 18.

[0080] In a further design, a first valve 2 is installed in the first pipeline 3, a second valve 7 and a pressure gauge 6 are installed in the second pipeline 5, a pressure relief valve 8 is also installed in the second pipeline 5, an annular frame 19 is fixedly connected to the outside of the support frame 16, a plurality of groups of air bags 13 are fixedly connected to the outside of the annular frame 19, a third pipeline 9 is fixedly connected to the outside of the second pipeline 5, a third valve 10 is fixedly connected to the third pipeline 9, a fourth pipeline 11 is fixedly connected to one end of the third pipeline 9, the fourth pipeline 11 is fixedly connected to the air bag 13, the gas will also enter the fourth pipeline 11 through the third pipeline 9, and finally enter the air bag 13, expand the air bag 13, and the thick-walled cylinder 27 on the support frame 16 is resisted and limited by the air bag 13.

[0081] In a further design, the outside of the annular frame 19 is fixedly connected to a connecting frame 20, and the outside of the connecting frame 20 is fixedly connected to multiple groups of fixed blocks 21. A piston groove 23 is provided in the fixed block 21, and a piston block 25 is slidably connected in the piston groove 23. A spring 24 is connected between the piston block 25 and the piston groove 23, and a limiting rod 26 is fixedly connected to the bottom of the piston block 25. A sixth pipeline 22 is fixedly connected between two adjacent fixed blocks 21, and the sixth pipeline 22 is communicated with the piston groove 23. The outside of the third pipeline 9 is fixedly connected to a fifth pipeline 12, and one end of the fifth pipeline 12 is fixedly connected to one of the fixed blocks 21. The gas is transported to the piston groove 23 through the fifth pipeline 12, and the piston block 25 in the piston groove 23 is squeezed, so that the piston block 25 drives the limiting rod 26 to move downward, and the limiting rod 26 is used to resist the end of the thick-walled cylinder 27 to ensure the stability of the thick-walled cylinder 27 during measurement.

[0082] The method of using this embodiment is as follows: the thick-walled cylinder 27 is placed on the support frame 16, and then one end of the second pipe 5 is inserted into the thick-walled cylinder 27, and the sealing cover 14 is firmly installed on the thick-walled cylinder 27 by connecting the thick-walled cylinder 27 with the connecting bolt 15;

[0083] Open all valves, pressurize the gas through the gas booster pump, and then deliver it to the thick-walled cylinder 27. At the same time, the gas will also enter the fourth pipe 11 through the third pipe 9, and finally enter the airbag 13, expand the airbag 13, and use the airbag 13 to limit the thick-walled cylinder 27 on the support frame 16. At the same time, the gas in the second pipe 5 will also pass into the fifth pipe 12, and the gas will be delivered to the piston groove 23 through the fifth pipe 12, and the piston block 25 in the piston groove 23 will be squeezed, so that the piston block 25 drives the limit rod 26 to move downward, and the limit rod 26 is used to contact the end of the thick-walled cylinder 27 to ensure the stability of the thick-walled cylinder 27 during measurement; finally, stress and temperature detection can be performed through the strain gauge 17 and the thermocouple 18.

[0084] Embodiment 2:

[0085] The control system includes a data acquisition unit, an inflation flow control unit, an early warning unit and a control unit.

[0086] The data acquisition module includes a stress analysis module for the thick-walled cylinder 27 and a stress and strain monitoring submodule;

[0087] Among them, the stress analysis module of the thick-walled cylinder 27 is based on the elastic mechanics theory. The stress distribution of the thick-walled cylinder 27 under the action of internal pressure follows the Lame formula:

[0088] ;

[0089] ;

[0090] Where: The radial stress is , is the pressure inside the thick-walled cylinder 27, is the external pressure of the thick-walled cylinder 27, is the inner radius of the thick-walled cylinder 27, is the outer radius of the thick-walled cylinder 27;

[0091] Among them, this formula can be used to accurately calculate the radial stress distribution at different positions inside the thick-walled cylinder 27, providing an important basis for the strength design and material selection of the thick-walled cylinder 27. In the design of the thick-walled cylinder 27, understanding the radial stress distribution helps to determine the wall thickness of the thick-walled cylinder 27 to ensure that it will not rupture or other dangerous situations when subjected to internal pressure.

[0092] When considering the influence of temperature gradient, a thermal stress correction term is introduced:

[0093] ;

[0094] Where: is the thermal stress caused by temperature change, is the linear expansion coefficient of the material, which reflects the expansion or contraction characteristics of the material when the temperature changes; is the elastic modulus of the material, which indicates the material's ability to resist elastic deformation; is the Poisson's ratio of the material, which describes the relationship between the lateral strain and the longitudinal strain of the material when it is subjected to stress; is the temperature change, and the temperature is measured by the thermocouple 18;

[0095] Among them, during the compressed air energy storage process, the air pressure and temperature in the thick-walled cylinder 27 will change, and the temperature change will cause thermal stress in the thick-walled cylinder 27. The thermal stress may be superimposed on the mechanical stress, thereby affecting the strength and life of the thick-walled cylinder 27. By calculating the thermal stress through this formula, the influence of thermal stress can be considered in the design, and corresponding measures can be taken to reduce the harm of thermal stress to the cylinder, such as selecting appropriate materials, optimizing structural design, etc.

[0096] The stress strain monitoring submodule includes collecting the output voltage of the strain gauge 17, and the calculation formula is:

[0097] ;

[0098] Analog-to-digital conversion: 24-bit Δ-Σ ADC, sampling rate 10kHz;

[0099] The "Δ-Σ" is an analog-to-digital conversion technology, namely delta-sigma (delta-sigma) modulation technology, which converts the input analog signal into a digital signal through oversampling and noise shaping.

[0100] "ADC" is the abbreviation of Analog-to-Digital Converter, which means analog-to-digital converter, which is used to convert continuous analog signals into discrete digital signals for processing by digital devices such as computers. 24 bits means that the resolution of the analog-to-digital converter is 24 bits, which means that it can subdivide the analog signal into 2 to the power of 24 (16777216) different quantization levels.

[0101] in, To calculate the output voltage of the strain gauge 17 when the four-arm full-bridge circuit is used, is the sensitivity coefficient of the strain gauge 17, reflecting the sensitivity of the strain gauge 17 to strain; is the relative change in resistance of the strain gauge 17, which is proportional to the strain of the object being measured; is the excitation voltage, i.e., the voltage applied to the bridge of the strain gauge 17.

[0102] Among them, in the stress and strain monitoring submodule, the strain gauge 17 is the key element for measuring stress and strain. The change in resistance of the strain gauge 17 can be converted into a voltage signal through this formula, which is convenient for subsequent signal conditioning and analog-to-digital conversion. According to the magnitude of the output voltage, the strain value of the object under test can be calculated, and then the stress value can be obtained, providing data support for monitoring the stress state of the thick-walled cylinder 27;

[0103] The inflation flow control unit includes a thermodynamic coupling model, a pneumatic execution module and a pressure closed-loop control module;

[0104] The thermodynamic coupling model is used to calculate the rate of change of the internal energy of the air in the thick-walled cylinder 27, specifically as follows:

[0105] ;

[0106] in, It represents the mass m of air in the thick-walled cylinder 27 multiplied by the specific heat capacity at constant volume Multiply by the rate of change of temperature over time , i.e. the rate of change of the internal energy of the air in the thick-walled cylinder 27; represents the convective heat exchange between the intake air and the air in the thick-walled cylinder 27, is the convective heat transfer coefficient, is the heat exchange area, is the intake air temperature, is the air temperature in the thick-walled cylinder 27; It represents the heat loss rate of the thick-walled cylinder 27 to the outside.

[0107] Among them, through this equation, we can analyze the change of air temperature in the cylinder over time and understand the energy transfer during the inflation process. In the design and operation of compressed air energy storage systems, mastering the temperature change law is crucial to optimizing system efficiency and ensuring system safety. For example, the inflation speed can be adjusted according to the temperature change to avoid system failure due to excessive temperature.

[0108] Combined with the ideal gas state equation:

[0109] in is the gas pressure, is the gas volume, is the gas mass, is the gas constant, is the gas temperature;

[0110] Among them, in the compressed air energy storage system, air can be approximately regarded as an ideal gas. Through this equation, the third parameter can be calculated based on any two known parameters of pressure, volume and temperature. In the control and management system of the experimental device, this method can be used in combination with the energy conservation equation to accurately simulate and control the inflation process, such as adjusting the inflation flow rate according to changes in pressure and temperature.

[0111] The pneumatic actuator module uses the proportional valve flow characteristic equation to calculate the inflation flow, and the characteristic equation is as follows:

[0112] ;

[0113] in, is the flow through the first valve 2, is the flow coefficient of the first valve 2, reflecting the flow capacity of the first valve 2; is the pressure difference before and after the first valve 2, is the density of air;

[0114] Function: In the inflation flow control system, the first valve 2 is the key actuator for controlling the inflation flow. Through this equation, the flow through the regulating valve can be calculated based on the pressure difference before and after the first valve 2 and the air density. During the control process, the flow coefficient can be changed by adjusting the opening of the first valve 2. , thereby achieving precise control of the inflation flow.

[0115] The pressure closed-loop control module estimates the state of the system based on the robust control algorithm formula of the state observer:

[0116] ;

[0117] ;

[0118] in is the derivative of the state estimate, is the state matrix of the system, is the input matrix, is the control input, is the observer gain matrix, is the actual output of the system, is the estimated value of the system output. The second equation is the control law, which is based on the state estimate Calculate control input ,in is the feedback gain matrix.

[0119] Function: In the inflation flow control system, due to the uncertainty and interference of the system, the traditional control method may not guarantee the stability and control accuracy of the system. The robust control algorithm based on the state observer estimates the state of the system through the state observer and performs feedback control according to the estimated state, which can effectively suppress the uncertainty and interference of the system and improve the robustness and control performance of the system.

[0120] The early warning unit includes a reliability assessment module and a threshold early warning module;

[0121] The reliability assessment module adopts the fault tree analysis method, and the top event probability is calculated as follows:

[0122] ;

[0123] To calculate the top event probability of the fault tree, Bottom event The probability of occurrence, is the number of bottom events. This formula assumes that the bottom events are independent of each other;

[0124] In the safety monitoring and early warning module, fault tree analysis is a commonly used reliability assessment method. By constructing a fault tree, decomposing the system's faults (top events) into multiple basic faults (bottom events), and calculating the probability of occurrence of bottom events, the probability of occurrence of top events can be obtained. This helps to evaluate the reliability and safety of the system, identify the weak links of the system, and provide a basis for formulating safety measures and maintenance plans.

[0125] The threshold warning module adopts the stress safety threshold calculation formula:

[0126] ;

[0127] is the stress safety threshold, where is the strength of the material, that is, the maximum stress that the material can withstand; It is a safety factor, usually between 1.5 and 2.0, which is used to take into account factors such as uncertainty in material properties and load fluctuations.

[0128] Function: In the safety monitoring and early warning module, the stress safety threshold is an important basis for judging whether the system is safe. The stress safety threshold is calculated by this formula, and the actual measured stress value is compared with the safety threshold. When the actual stress value exceeds the safety threshold, the system sends a warning signal to remind the operator to take corresponding measures to avoid safety accidents. `

[0129] The control method of the control unit is as follows:

[0130] Firstly, a deep neural network-based predictive control (DNN-MPC) is proposed, and its objective function is:

[0131] ;

[0132] in, For the The predicted stress value at time is the reference value of stress; For the prediction time domain; For the Control the input change at all times. To control the time domain; is the weighting coefficient, which is used to balance the output error and the weight of the control input change;

[0133] Function: In the experimental device for testing the thick wall stress and temperature of compressed air energy storage cylinders, the system has the characteristics of multi-parameter coupling, and it is difficult to achieve precise control with traditional control methods. The deep neural network predictive control algorithm predicts the future state of the system through the offline trained deep neural network model, and optimizes the control input sequence according to the objective function. It can effectively deal with the nonlinearity and multi-parameter coupling problems of the system and improve the control accuracy and stability of the system. `

[0134] At the same time, the output of the controller in the control unit is calculated by the fuzzy adaptive PID control algorithm formula;

[0135] ;

[0136] in, is the output of the controller, is the proportionality coefficient, is the integration coefficient, is the differential coefficient; For the The error at the moment, that is, the difference between the set value and the actual value; is the integral of the error, reflecting the cumulative effect of the error; is the differential of the error, reflecting the changing trend of the error.

[0137] PID control algorithm is a widely used control algorithm. By adjusting the proportional, integral and differential coefficients, precise control of the system can be achieved. In the control and management system of the compressed air energy storage cylinder thick wall stress and temperature test experimental device, the PID control algorithm can be used to control the inflation flow, pressure and other parameters, so that the system output can quickly and accurately track the set value. Fuzzy adaptive PID control is based on traditional PID control and dynamically adjusts the and , to adapt to the nonlinearity and uncertainty of the system and improve the control effect.

[0138] Secondly, based on the digital twin system, stress and temperature control equations are established;

[0139] ;

[0140] ;

[0141] Meaning: The first equation is the governing equation of stress, describing the stress The law of change over time. is the stress diffusion tensor, represents the diffusion term of stress, and f is the source term of stress. The second equation is the governing equation for temperature, which describes the temperature The law of change over time. is the thermal diffusion coefficient, is the Laplace operator of temperature, which indicates the diffusion of temperature. is the heat source term.

[0142] Function: In the digital twin system, these two equations are used to build a virtual model to simulate the stress and temperature distribution of the thick wall of the compressed air energy storage cylinder. By bidirectionally mapping the virtual model with the real-time data of the physical experiment, real-time monitoring and prediction of the physical system can be achieved. When the state of the physical system changes, the virtual model can reflect this change in time and make corresponding adjustments to provide support for system optimization and decision-making.

[0143] Subsequently, the error is calculated based on the error correction equation;

[0144] ;

[0145] For physical experiment data Simulating data with virtual models The error between Represents the 2-norm, which is the square root of the sum of the squares of the vector elements.

[0146] Function: In the digital twin system, the error correction equation is used to evaluate the consistency between the virtual model and the physical system. By calculating the error, problems in the virtual model can be discovered in time, and the model can be corrected and optimized to improve the accuracy and reliability of the virtual model.

[0147] Next, based on the dynamic adjustment formula of the security threshold, dynamically adjust the security threshold ;

[0148] ;

[0149] in, For the The safety threshold at the moment, is the learning rate, which is used to control the step size of the safety threshold adjustment; is the reward function, which gives the corresponding reward value according to the state of the system.

[0150] Function: In the compressed air energy storage cylinder thick wall stress and temperature test experimental device, the operating conditions of the system may change, and the traditional fixed safety threshold may not be able to adapt to such changes. The adaptive safety boundary mechanism uses the reinforcement learning method to dynamically adjust the safety threshold according to the real-time status of the system, which can better ensure the safety and reliability of the system.

[0151] Finally, the reward function formula is used according to the actual stress With safety threshold The size relationship gives the reward value;

[0152] ;

[0153] When the actual stress is less than the safety threshold, the reward value is +1, indicating that the system is in a safe state; when the actual stress is greater than or equal to the safety threshold, the reward value is -1, indicating that the system is in a dangerous state.

[0154] In summary, the present invention can analyze the stress distribution of the thick-walled cylinder 27 based on the Lame formula of elastic mechanics, introduce a thermal stress correction term considering the influence of temperature gradient; construct a thermodynamic coupling model of the inflation process by combining the thermodynamic energy conservation equation and the ideal gas state equation; and adopt a fuzzy adaptive PID control algorithm to dynamically adjust the control parameters according to the error and the error change rate.

[0155] In the present invention, stress-strain and temperature field data are collected respectively by strain gauges 17 and distributed optical fiber temperature measurement systems, data preprocessing can be performed using signal conditioning circuits and analog-to-digital conversion, and the heat conduction equation can be discretized to process temperature data.

[0156] The present invention uses the fault tree analysis method to perform reliability assessment, and can set a stress safety threshold based on the material tensile strength and safety factor to achieve threshold warning.

[0157] The present invention proposes a deep neural network-based predictive control DNN-MPC, which can predict future states through an offline trained DNN model, perform rolling optimization of control input sequences, and achieve multi-parameter collaborative control.

[0158] In the present invention, a bidirectional mapping between a virtual model and real-time data of a physical experiment is constructed, and the accuracy of the model can be improved by using an error correction equation.

[0159] The present invention dynamically adjusts the safety threshold based on reinforcement learning, and can give rewards or penalties based on whether the stress exceeds the safety range. It can conduct experimental tests within a specific internal pressure and temperature range to verify the performance of the system in terms of stress control accuracy of ±2.5%FS, temperature control accuracy of ±1.0℃, and flow regulation response time of <500ms.

[0160] In summary, the existing technology may only monitor or control a single physical quantity, while this system can simultaneously monitor and control the stress and inflation flow of the thick wall of the compressed air energy storage cylinder. Through the multi-parameter coupling control algorithm, the mutual influence between stress and flow is comprehensively considered to achieve more precise experimental process control and improve the reliability and accuracy of the experimental results.

[0161] The predictive control DNN-MPC algorithm based on deep neural network in the present invention can more accurately predict the future state of the system and adjust the control strategy in advance, thereby significantly improving the control accuracy and response speed. The digital twin technology is introduced in the present invention to realize the two-way mapping and error correction of the real-time data of the virtual model and the physical experiment, which enables the experimental process to be previewed and optimized in a virtual environment, and potential problems can be discovered and adjusted in time, greatly shortening the experimental cycle and cost. Traditional safety monitoring usually adopts fixed threshold warning, which is difficult to adapt to dynamic changes in the experimental process. The adaptive safety boundary mechanism based on reinforcement learning in the present invention can dynamically adjust the safety threshold according to the real-time data of the experiment, timely discover and deal with potential safety risks, and provide more reliable safety protection for experimental personnel and equipment.

[0162] The standard parts used in the present invention can all be purchased from the market, and special-shaped parts can be customized according to the description in the specification and the drawings. The specific connection methods of each part adopt conventional means such as mature bolts, rivets, welding, etc. in the prior art. Machinery, parts and equipment all adopt conventional models in the prior art, and the circuit connection adopts the conventional connection method in the prior art, which will not be described in detail here. The content not described in detail in this specification belongs to the prior art known to professional and technical personnel in this field.

[0163] While the embodiments of the present invention have been shown and described, it will be apparent to those skilled in the art that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A device for testing the thick wall stress and temperature of a compressed air energy storage cylinder, characterized in that: The invention comprises a gas tank (1), a support frame (16) and a control system, wherein the output of the gas tank (1) is connected to a first pipeline (3), a second pipeline (5) is arranged outside the support frame (16), a gas pressure pump (4) is arranged between the first pipeline (3) and the second pipeline (5), the input end of the gas pressure pump (4) is fixedly connected to the first pipeline (3), the output end of the gas pressure pump (4) is fixedly connected to the second pipeline (5), one end of the second pipeline (5) is fixedly connected to a sealing cover (14), a plurality of groups of connecting bolts (15) are penetrated through the sealing cover (14), a thick-walled cylinder (27) is arranged on the support frame (16), a plurality of groups of strain gauges (17) and thermocouples (18) are installed at the end of the thick-walled cylinder (27), and the groups of strain gauges (17) and thermocouples (18) are electrically coupled to the control system.

2. The thick wall stress and temperature testing device for compressed air energy storage cylinder according to claim 1, characterized in that: A first valve (2) is installed in the first pipeline (3), a second valve (7) and a pressure gauge (6) are installed in the second pipeline (5), and a pressure relief valve (8) is also installed in the second pipeline (5).

3. The thick wall stress and temperature testing device for compressed air energy storage cylinder according to claim 2, characterized in that: The support frame (16) is fixedly connected to an annular frame (19) on the outside, and a plurality of groups of air bags (13) are fixedly connected to the outside of the annular frame (19). The second pipe (5) is fixedly connected to a third pipe (9) on the outside, and a third valve (10) is fixedly connected to the third pipe (9). One end of the third pipe (9) is fixedly connected to a fourth pipe (11), and the fourth pipe (11) is fixedly connected to the air bag (13).

4. The thick wall stress and temperature testing device for compressed air energy storage cylinder according to claim 3, characterized in that: The outside of the annular frame (19) is fixedly connected to a connecting frame (20), and the outside of the connecting frame (20) is fixedly connected to a plurality of fixed blocks (21). A piston groove (23) is provided in the fixed block (21), and a piston block (25) is slidably connected in the piston groove (23). A spring (24) is connected between the piston block (25) and the piston groove (23). A limit rod (26) is fixedly connected to the bottom of the piston block (25). A sixth pipe (22) is fixedly connected between two adjacent fixed blocks (21), and the sixth pipe (22) is communicated with the piston groove (23). The outside of the third pipe (9) is fixedly connected to a fifth pipe (12), and one end of the fifth pipe (12) is fixedly connected to the inside of one of the fixed blocks (21).

5. The thick wall stress and temperature testing device for compressed air energy storage cylinder according to claim 4, characterized in that: The control system includes a data acquisition unit, an inflation flow control unit, an early warning unit and a control unit.

6. The thick wall stress and temperature testing device for compressed air energy storage cylinder according to claim 5, characterized in that: The data acquisition module comprises a stress analysis module for the thick-walled cylinder (27) and a stress and strain monitoring submodule; The stress analysis module of the thick-walled cylinder (27) is based on the theory of elastic mechanics. The stress distribution of the thick-walled cylinder (27) under the action of internal pressure follows the Lame formula: ； ； Where: The radial stress is , represents the stress along the radius of the cylinder, and the circumferential stress is , represents the stress along the circumference of the cylinder is the pressure inside the thick-walled cylinder (27), is the external pressure of the thick-walled cylinder (27), is the inner radius of the thick-walled cylinder (27), is the outer radius of the thick-walled cylinder (27); When considering the influence of temperature gradient, a thermal stress correction term is introduced: ； Where: is the thermal stress caused by temperature change, is the linear expansion coefficient of the material, which reflects the expansion or contraction characteristics of the material when the temperature changes; is the elastic modulus of the material, which indicates the material's ability to resist elastic deformation; is the Poisson's ratio of the material, which describes the relationship between the lateral strain and the longitudinal strain of the material when it is subjected to stress; is the temperature change; The stress-strain monitoring submodule includes collecting the output voltage of the strain gauge (17), and the calculation formula is: ； in, To calculate the output voltage of the strain gauge (17) when using a four-arm full-bridge circuit, is the sensitivity coefficient of the strain gauge (17), reflecting the sensitivity of the strain gauge (17) to strain; is the relative change in resistance of the strain gauge (17), which is proportional to the strain of the object being measured; is the excitation voltage, i.e. the voltage applied to the strain gauge (17) bridge.

7. A device for testing thick wall stress and temperature of energy storage cylinder for compressed air according to claim 6, characterized in that: The inflation flow control unit includes a thermodynamic coupling model, a pneumatic execution module and a pressure closed-loop control module; The thermodynamic coupling model is used to calculate the rate of change of the internal energy of the air in the thick-walled cylinder (27), specifically, the following formula: ； in, represents the mass m of air in the thick-walled cylinder (27) multiplied by the specific heat capacity at constant volume Multiply by the rate of change of temperature over time , i.e., the rate of change of the internal energy of the air in the thick-walled cylinder (27); represents the convective heat transfer between the intake air and the air in the thick-walled cylinder (27), is the convective heat transfer coefficient, is the heat exchange area, is the intake air temperature, is the air temperature in the thick-walled cylinder (27); represents the heat loss rate of the thick-walled cylinder (27) to the outside; Combined with the ideal gas state equation: ; in is the gas pressure, is the gas volume, is the gas mass, is the gas constant, is the gas temperature; The pneumatic actuator module uses the proportional valve flow characteristic equation to calculate the inflation flow, and the characteristic equation is as follows: ； in, is the flow rate through the first valve (2), is the flow coefficient of the first valve (2), reflecting the flow capacity of the first valve (2); is the pressure difference before and after the first valve (2), is the density of air; The pressure closed-loop control module estimates the state of the system based on the robust control algorithm formula of the state observer: ； ； in is the derivative of the state estimate, is the state matrix of the system, is the input matrix, is the control input, is the observer gain matrix, is the actual output of the system, is an estimate of the system output.

8. The thick wall stress and temperature testing device for compressed air energy storage cylinder according to claim 5, characterized in that: The early warning unit includes a reliability assessment module and a threshold early warning module; The reliability assessment module adopts the fault tree analysis method, and the top event probability is calculated as follows: ； To calculate the top event probability of the fault tree, Bottom event The probability of occurrence, is the number of bottom events; This formula assumes that the bottom events are independent of each other; The threshold warning module adopts the stress safety threshold calculation formula: ； is the stress safety threshold, where is the strength of the material, that is, the maximum stress that the material can withstand; is the safety factor.

9. The thick wall stress and temperature testing device for compressed air energy storage cylinder according to claim 5, characterized in that: The control method of the control unit is as follows: First, based on deep neural network predictive control (DNN-MPC), its objective function is: ； in, For the The predicted stress value at time is the reference value of stress; For the prediction time domain; For the Control the input change at all times. To control the time domain; is the weighting coefficient, which is used to balance the output error and the weight of the control input change; At the same time, the output of the controller in the control unit is calculated by the fuzzy adaptive PID control algorithm formula; ； in, is the output of the controller, is the proportionality coefficient, is the integration coefficient, is the differential coefficient; For the The error at the moment, that is, the difference between the set value and the actual value; is the integral of the error, reflecting the cumulative effect of the error; is the differential of the error; Secondly, based on the digital twin system, stress and temperature control equations are established; ； ； in is the stress diffusion tensor, represents the diffusion term of stress, and f is the source term of stress; is the thermal diffusion coefficient, is the Laplace operator of temperature, which indicates the diffusion of temperature. is the heat source term; Subsequently, the error is calculated based on the error correction equation; ； For physical experiment data Simulating data with virtual models The error between represents the 2-norm, which is the square root of the sum of the squares of the vector elements; Next, based on the dynamic adjustment formula of the security threshold, dynamically adjust the security threshold ; ； in, For the The safety threshold at the moment, is the learning rate, which is used to control the step size of the safety threshold adjustment; is the reward function, which gives the corresponding reward value according to the state of the system; Finally, the reward function formula is used according to the actual stress With safety threshold The size relationship gives the reward value; ； When the actual stress is less than the safety threshold, the reward value is +1, indicating that the system is in a safe state; when the actual stress is greater than or equal to the safety threshold, the reward value is -1, indicating that the system is in a dangerous state.

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