High-temperature energy storage monitoring method, device and medium based on capacitive pressure sensor

Abstract

The present invention discloses a high-temperature energy storage monitoring method, device and medium based on a capacitive pressure sensor, relating to the technical field of safety monitoring. The present invention determines whether the state of the energy storage medium in the high-temperature energy storage system is stable. If the state of the energy storage medium is stable, the pressure of the energy storage medium is directly determined according to the output signal corresponding to the fixed input signal. If the state of the energy storage medium is unstable, the input signal is controlled to change within a preset signal range, and then the input-output signal change curve is fitted. The input-output signal change curve not only contains the information of the output signal changing with the input signal, but also contains the change information of the output signal caused by the influence of temperature. Therefore, by analyzing the input-output signal change curve, the pressure value of the energy storage medium in the high-temperature energy storage system is obtained, and the accuracy of the pressure monitoring result of the capacitive pressure sensor for the high-temperature energy storage system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring, and particularly to a high-temperature energy storage monitoring method, device and medium based on a capacitive pressure sensor. Background Art

[0002] A high-temperature energy storage system is an energy storage system that stores energy in the form of heat. During the charging stage, an external energy source (such as solar energy, waste heat, etc.) transfers heat to the energy storage medium, causing its temperature to rise. During the discharging stage, when energy is needed, the stored heat energy is released, and the heat is transferred to a working fluid (such as water, steam, etc.) through a heat exchanger to drive a generator or other heat engines to generate electricity or provide power. Common energy storage media include molten salts, ceramics, metals, etc. These media have high heat capacity and thermal stability and can store a large amount of heat energy at high temperatures. During the operation of a high-temperature energy storage system, it is necessary to monitor the pressure of the energy storage medium in real time to further judge the operating condition of the high-temperature energy storage system.

[0003] High-temperature pressure sensors applied to high-temperature energy storage systems mainly include semiconductor sensors, sputtered alloy film high-temperature pressure sensors, high-temperature fiber optic pressure sensors, high-temperature capacitive pressure sensors, etc. The semiconductor capacitive pressure sensor has high sensitivity and low power consumption compared with the piezoresistive pressure sensor, and has become a commonly used pressure sensor in high-temperature energy storage systems.

[0004] Facing the hundreds of degrees Celsius high temperature of the energy storage medium in a high-temperature energy storage system, the capacitive pressure sensor is often affected by the following various factors: (1) Reduced measurement accuracy: Temperature changes will cause the capacitance value of the sensor to change. For example, in a high-temperature environment, the dielectric constant between the capacitor plates may change, resulting in the capacitance value deviating from the original pressure-capacitance correspondence relationship, thus reducing the measurement accuracy. (2) Zero drift: Temperature changes may cause the output signal of the sensor to change even when there is no pressure input, that is, zero drift occurs, which will bring errors to actual measurements. In the face of the above effects, the main methods in the prior art to improve the measurement accuracy of capacitive pressure sensors when used at high temperatures are as follows:

[0005] (1) Hardware compensation: Using a temperature sensor: Integrate a temperature sensor inside the sensor to monitor the working temperature of the sensor in real time. According to the output signal of the temperature sensor, the output of the capacitive pressure sensor is temperature-compensated through circuit design. For example, temperature sensors such as thermistors and thermocouples can be used to convert the temperature signal into an electrical signal and input it into the compensation circuit for processing. A dedicated compensation circuit is often designed to perform temperature compensation on the output of the capacitive pressure sensor. The compensation circuit can be implemented using analog circuits or digital circuits. According to the output signal of the temperature sensor and the output signal of the pressure sensor, the temperature compensation value is calculated and the output of the pressure sensor is corrected.

[0006] (2) Software compensation: Establish a temperature compensation model: Through experiments and data analysis, establish a temperature compensation model for the capacitive pressure sensor. The temperature compensation model can be an analytical model based on mathematical formulas or an intelligent model based on machine learning algorithms such as neural networks and support vector machines. According to the temperature compensation model, perform software compensation on the output of the sensor. Usually, during the use of the sensor, by collecting the output signals of the temperature sensor and the pressure sensor in real time, use the temperature compensation model to perform online compensation on the output of the pressure sensor. Online compensation can adjust the output of the sensor in real time, improving the measurement accuracy and stability of the sensor at different temperatures.

[0007] However, the temperature of the energy storage medium in the high-temperature energy storage system is often unstable. For example, in the solar high-temperature energy storage system, due to the change in the intensity of sunlight, the temperature of the energy storage medium also changes continuously. And because heat conduction takes time, the change in the temperature of the energy storage medium does not immediately affect the capacitive pressure sensor. Therefore, the above hardware compensation method can only be applied to the state where the temperature of the energy storage medium is stable. When the temperature of the energy storage medium fluctuates, the temperature distribution of the sensor is uneven and constantly changing, making it difficult to obtain the temperature of the sensor in a timely manner. Similarly, the software compensation method is also difficult to cope with the situation where the temperature distribution of the sensor is uneven and constantly changing. This leads to inaccurate pressure monitoring results of the capacitive pressure sensor for the high-temperature energy storage system. Therefore, a new high-temperature energy storage monitoring method based on the capacitive pressure sensor needs to be proposed to improve the accuracy of the pressure monitoring results of the capacitive pressure sensor for the high-temperature energy storage system. Summary of the Invention

[0008] The present invention provides a high-temperature energy storage monitoring method, device, and medium based on a capacitive pressure sensor, which are used to improve the accuracy of the pressure monitoring results of the capacitive pressure sensor for the high-temperature energy storage system.

[0009] To solve the above technical problems, in the first aspect of the present invention, a high-temperature energy storage monitoring method based on a capacitive pressure sensor is disclosed. The method is used to monitor the pressure of the energy storage medium in the high-temperature energy storage system through the capacitive pressure sensor. The capacitance value of the capacitor device in the capacitive pressure sensor changes with the change of the pressure of the energy storage medium, so that the output signal changes after the input signal passes through the capacitive pressure sensor. The method includes:

[0010] Fix the input signal and determine whether the change value of the output signal within a preset time range is greater than or equal to a preset change threshold;

[0011] If it is determined that the change value of the output signal within the preset time range is less than the preset change threshold, the pressure of the energy storage medium in the high-temperature energy storage system is determined according to the output signal;

[0012] If it is determined that the change value of the output signal within the preset time range is greater than or equal to the preset change threshold, the following operations are performed:

[0013] Control the input signal to change within the preset signal range, and obtain the output signals corresponding to different input signals; according to the different input signals and the output signals corresponding to each input signal, fit an input-output signal change curve, and the input-output signal change curve is used to represent the corresponding relationship between the output signal and the input signal;

[0014] According to the input-output signal change curve, determine the pressure value of the energy storage medium in the high-temperature energy storage system.

[0015] As an optional implementation manner, in the first aspect of the present invention, the controlling the input signal to change within the preset signal range, and obtaining the output signals corresponding to different input signals; according to the different input signals and the output signals corresponding to each input signal, fitting an input-output signal change curve includes:

[0016] At each preset target moment, control the input signal to change within the preset signal range, and obtain the output signals corresponding to different input signals; according to the different input signals and the output signals corresponding to each input signal, fit an input-output signal change curve corresponding to the target moment;

[0017] And, the determining the pressure value of the energy storage medium in the high-temperature energy storage system according to the input-output signal change curve includes:

[0018] For the target moment to be monitored, according to the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a preset plurality of the target moments before the target moment to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored.

[0019] As an optional implementation manner, in the first aspect of the present invention, when it is determined that the change value of the output signal within the preset time range is greater than or equal to the preset change threshold, the method further includes:

[0020] Obtain the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to each target moment within a preset set of target moments, and the set of target moments includes a plurality of consecutive target moments;

[0021] Calculate the dispersion parameter of the pressure values of the energy storage medium in the high-temperature energy storage system corresponding to all the target times within the set of target times, where the dispersion parameter includes at least one of range, variance, standard deviation, and mean square deviation;

[0022] Determine whether the dispersion parameter corresponding to the set of target times is less than or equal to a preset dispersion threshold. If it is determined that the dispersion parameter corresponding to the set of target times is less than or equal to the preset dispersion threshold, then re-trigger the operation of fixing the input signal and determining whether the change value of the output signal within a preset time range is greater than or equal to a preset change threshold.

[0023] As an alternative implementation manner, in the first aspect of the present invention, for the target time to be monitored, determining the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target time to be monitored according to the input-output signal change curve corresponding to the target time to be monitored and the input-output signal change curves corresponding to a preset plurality of target times before the target time to be monitored includes:

[0024] For the target time to be monitored, input the input-output signal change curve corresponding to the target time to be monitored and the input-output signal change curves corresponding to a preset plurality of target times before the target time to be monitored into a preset curve analysis model, and obtain the temperature state parameter output by the curve analysis model, where the temperature state parameter is used to represent the temperature change trend of the capacitor component in the capacitive pressure sensor;

[0025] For the target time to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target time to be monitored according to the input-output signal change curve corresponding to the target time to be monitored and the temperature state parameter;

[0026] Wherein, the curve analysis model is obtained using multiple sets of training data sets. Each set of training data sets includes a set of input-output signal training curves and the temperature state parameters corresponding to the set of input-output signal training curves, and the curve analysis model is used to determine the temperature state parameters according to a set of training input-output signal change curves.

[0027] As an alternative implementation manner, in the first aspect of the present invention, a plurality of target capacitive pressure sensors are provided in the high-temperature energy storage system, and the method further includes:

[0028] For each of the target capacitive pressure sensors in the high-temperature energy storage system, save the pressure value of the energy storage medium in the high-temperature energy storage system determined by the target capacitive pressure sensor to the sensor node corresponding to the target capacitive pressure sensor; wherein, the sensor node is the node corresponding to the target capacitive pressure sensor on the pressure knowledge graph constructed based on the high-temperature energy storage system;

[0029] According to the pressure values saved by all the sensor nodes on the pressure knowledge graph, determine several pressure propagation directions from the pressure knowledge graph, and determine the pressure distribution parameters corresponding to the high-temperature energy storage system according to all the pressure propagation directions and the pressure values saved by all the sensor nodes on the pressure knowledge graph. The pressure distribution parameters are used to represent the pressure distribution condition on the high-temperature energy storage system.

[0030] As an optional implementation manner, in the first aspect of the present invention, the method further includes:

[0031] Judge whether the pressure distribution parameters meet the preset abnormal pressure distribution condition. If the pressure distribution parameters meet the preset abnormal pressure distribution condition, trigger the execution of the following operations:

[0032] For each preset update time point, update the pressure values saved by all the sensor nodes on the pressure knowledge graph according to the pressure values determined by all the target capacitive pressure sensors in the high-temperature energy storage system at this update time point, and obtain the updated pressure knowledge graph corresponding to this update time point;

[0033] For each preset update time point, determine the faulty nodes on the updated pressure knowledge graph according to the pressure values saved by all the sensor nodes on the updated pressure knowledge graph corresponding to this update time point, and determine the fault-related nodes corresponding to the faulty nodes; according to all the faulty nodes and all the fault-related nodes corresponding to this update time point, determine the fault weight value of each sensor node on the updated pressure knowledge graph corresponding to this update time point. The fault weight value is used to measure the influence degree of the corresponding sensor node on the fault;

[0034] Determine the target faulty node according to the fault weight values of each sensor node on the updated pressure knowledge graph corresponding to all the update time points, and determine the target fault position on the high-temperature energy storage system according to the target faulty node.

[0035] As an alternative implementation manner, in the first aspect of the present invention, for each preset update time point, determining a faulty node on the updated pressure knowledge graph according to the pressure values saved by all the sensor nodes on the updated pressure knowledge graph corresponding to this update time point includes:

[0036] For each sensor node on the updated pressure knowledge graph corresponding to each preset update time point, determining the expected pressure value corresponding to this sensor node according to the pressure values saved by all the related nodes associated with this sensor node; judging whether the difference between the pressure value saved by this sensor node and the expected pressure value is greater than a preset fault threshold, and if it is judged that the difference between the pressure value saved by this sensor node and the expected pressure value is greater than the preset fault threshold, determining this sensor node as a faulty node.

[0037] The second aspect of the present invention discloses a high-temperature energy storage monitoring device based on a capacitive pressure sensor. The device is used to monitor the pressure of the energy storage medium in the high-temperature energy storage system through the capacitive pressure sensor. The capacitance value of the capacitor component in the capacitive pressure sensor changes with the change of the pressure of the energy storage medium, so that the output signal changes after the input signal passes through the capacitive pressure sensor. The device includes:

[0038] A signal judgment module, configured to fix the input signal and judge whether the change value of the output signal within a preset time range is greater than or equal to a preset change threshold;

[0039] A first monitoring module, configured to determine the pressure of the energy storage medium in the high-temperature energy storage system according to the output signal when it is judged that the change value of the output signal within the preset time range is less than the preset change threshold;

[0040] A curve fitting module, configured to control the input signal to change within a preset signal range and obtain the output signals corresponding to different input signals when it is judged that the change value of the output signal within the preset time range is greater than or equal to the preset change threshold; fitting an input-output signal change curve according to different input signals and the output signals corresponding to each input signal, and the input-output signal change curve is used to represent the corresponding relationship between the output signal and the input signal;

[0041] A second monitoring module, configured to determine the pressure value of the energy storage medium in the high-temperature energy storage system according to the input-output signal change curve.

[0042] As an alternative implementation, in the second aspect of the present invention, the curve fitting module controls the input signal to vary within a preset signal range and obtains the output signals corresponding to different input signals; the specific manner of fitting the input-output signal change curve according to different input signals and the output signals corresponding to each input signal includes:

[0043] At each preset target moment, control the input signal to vary within a preset signal range and obtain the output signals corresponding to different input signals; according to different input signals and the output signals corresponding to each input signal, fit the input-output signal change curve corresponding to this target moment;

[0044] Moreover, the specific manner in which the second monitoring module determines the pressure value of the energy storage medium in the high-temperature energy storage system according to the input-output signal change curve includes:

[0045] For the target moment to be monitored, according to the input-output signal change curve corresponding to this target moment to be monitored and the input-output signal change curves corresponding to a preset plurality of target moments before this target moment to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to this target moment to be monitored.

[0046] As an alternative implementation, in the second aspect of the present invention, the device further includes:

[0047] A period monitoring module, configured to, when the signal judgment module determines that the change value of the output signal within a preset time range is greater than or equal to a preset change threshold, obtain the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to each target moment within a preset target moment set, and the target moment set includes a plurality of consecutive target moments;

[0048] A discrete analysis module, configured to calculate a discrete degree parameter of the pressure values of the energy storage medium in the high-temperature energy storage system corresponding to all target moments within the target moment set, and the discrete degree parameter includes at least one of range, variance, standard deviation, and mean square deviation;

[0049] A trigger judgment module, configured to judge whether the discrete degree parameter corresponding to the target moment set is less than or equal to a preset discrete degree threshold. If it is judged that the discrete degree parameter corresponding to the target moment set is less than or equal to the preset discrete degree threshold, then trigger the signal judgment module again to execute the operation of fixing the input signal and judging whether the change value of the output signal within a preset time range is greater than or equal to the preset change threshold.

[0050] As an alternative implementation manner, in the second aspect of the present invention, for the target moment to be monitored, the specific manner for the second monitoring module to determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored according to the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a preset plurality of the target moments before the target moment to be monitored includes:

[0051] For the target moment to be monitored, input the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a preset plurality of the target moments before the target moment to be monitored into a preset curve analysis model to obtain the temperature state parameter output by the curve analysis model, where the temperature state parameter is used to represent the temperature change trend of the capacitor component in the capacitive pressure sensor;

[0052] For the target moment to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored according to the input-output signal change curve corresponding to the target moment to be monitored and the temperature state parameter;

[0053] Wherein, the curve analysis model is obtained using multiple sets of training data sets. Each set of training data sets includes a set of input-output signal training curves and the temperature state parameter corresponding to the set of input-output signal training curves. The curve analysis model is used to determine the temperature state parameter according to a set of training input-output signal change curves.

[0054] As an alternative implementation manner, in the second aspect of the present invention, a plurality of target capacitive pressure sensors are provided in the high-temperature energy storage system, and the device further includes:

[0055] A map update module, configured to save the pressure value of the energy storage medium in the high-temperature energy storage system determined by each target capacitive pressure sensor in the high-temperature energy storage system to the sensor node corresponding to the target capacitive pressure sensor; wherein, the sensor node is the node corresponding to the target capacitive pressure sensor on the pressure knowledge map constructed based on the high-temperature energy storage system;

[0056] A pressure analysis module, configured to determine a plurality of pressure propagation directions from the pressure knowledge map according to the pressure values saved in all the sensor nodes on the pressure knowledge map, and determine the pressure distribution parameter corresponding to the high-temperature energy storage system according to all the pressure propagation directions and the pressure values saved in all the sensor nodes on the pressure knowledge map, where the pressure distribution parameter is used to represent the pressure distribution condition on the high-temperature energy storage system.

[0057] As an alternative implementation manner, in the second aspect of the present invention, the device further includes:

[0058] A pressure judgment module, configured to judge whether the pressure distribution parameter satisfies a preset abnormal pressure distribution condition;

[0059] A period update module, configured to, when the pressure judgment module judges that the pressure distribution parameter satisfies the preset abnormal pressure distribution condition, for each preset update time point, update the pressure values stored in all the sensor nodes on the pressure knowledge graph according to the pressure values determined by all the target capacitive pressure sensors in the high-temperature energy storage system at this update time point, and obtain an updated pressure knowledge graph corresponding to this update time point;

[0060] A fault analysis module, configured to, for each preset update time point, determine a fault node on the updated pressure knowledge graph according to the pressure values stored in all the sensor nodes on the updated pressure knowledge graph corresponding to this update time point, and determine a fault-related node corresponding to the fault node; according to all the fault nodes and all the fault-related nodes corresponding to this update time point, determine a fault weight value of each sensor node on the updated pressure knowledge graph corresponding to this update time point, where the fault weight value is used to measure the influence degree of the corresponding sensor node on the fault;

[0061] A fault determination module, configured to determine a target fault node according to the fault weight values of each sensor node on the updated pressure knowledge graph corresponding to all the update time points, and determine a target fault position on the high-temperature energy storage system according to the target fault node.

[0062] As an alternative implementation manner, in the second aspect of the present invention, the specific manner in which the fault analysis module determines a fault node on the updated pressure knowledge graph for each preset update time point according to the pressure values stored in all the sensor nodes on the updated pressure knowledge graph corresponding to this update time point includes:

[0063] For each sensor node on the updated pressure knowledge graph corresponding to each preset update time point, determine an expected pressure value of the sensor node according to the pressure values stored in all the related nodes associated with the sensor node; judge whether the difference between the pressure value stored in the sensor node and the expected pressure value is greater than a preset fault threshold, and if it is judged that the difference between the pressure value stored in the sensor node and the expected pressure value is greater than the preset fault threshold, determine that the sensor node is a fault node.

[0064] The third aspect of the present invention discloses another high-temperature energy storage monitoring device based on a capacitive pressure sensor, and the device includes:

[0065] A memory storing executable program codes;

[0066] A processor coupled to the memory;

[0067] The processor calls the executable program codes stored in the memory and executes the high-temperature energy storage monitoring method based on a capacitive pressure sensor disclosed in the first aspect of the present invention.

[0068] The fourth aspect of the present invention discloses a computer storage medium. The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the high-temperature energy storage monitoring method based on a capacitive pressure sensor disclosed in the first aspect of the present invention.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] The present invention can determine whether the state of the energy storage medium in the high-temperature energy storage system is stable. If the state of the energy storage medium is stable, the pressure of the energy storage medium is directly determined according to the output signal corresponding to the fixed input signal, and the operation is simple and efficient. If the state of the energy storage medium is unstable, the input signal is controlled to change within a preset signal range, and then the input-output signal change curve is fitted. The input-output signal change curve not only contains the information of the change of the output signal with the change of the input signal, but also contains the change information of the output signal caused by the influence of temperature. Therefore, by analyzing the input-output signal change curve, the information of the change of the output signal with the change of the input signal and the change information of the output signal caused by the influence of temperature can be distinguished respectively, so as to obtain the pressure value of the energy storage medium in the high-temperature energy storage system, and the accuracy of the pressure monitoring result of the capacitive pressure sensor for the high-temperature energy storage system is improved. Description of the Drawings

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0072] Figure 1 is a schematic flowchart of a high-temperature energy storage monitoring method based on a capacitive pressure sensor disclosed in an embodiment of the present invention;

[0073] Figure 2 is a schematic flowchart of another high-temperature energy storage monitoring method based on a capacitive pressure sensor disclosed in an embodiment of the present invention;

[0074] Figure 3 It is a schematic structural diagram of a high-temperature energy storage monitoring device based on a capacitive pressure sensor disclosed in an embodiment of the present invention;

[0075] Figure 4 It is a schematic structural diagram of another high-temperature energy storage monitoring device based on a capacitive pressure sensor disclosed in an embodiment of the present invention;

[0076] Figure 5 It is a schematic structural diagram of yet another high-temperature energy storage monitoring device based on a capacitive pressure sensor disclosed in an embodiment of the present invention. Detailed implementation manners

[0077] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0078] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or terminal comprising a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or terminals.

[0079] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0080] The present invention discloses a high-temperature energy storage monitoring method, device, and medium based on a capacitive pressure sensor. The main inventive concept lies in: if the state of the energy storage medium is stable, the pressure of the energy storage medium is directly determined according to the output signal corresponding to the fixed input signal; if the state of the energy storage medium is unstable, the input signal is controlled to change within a preset signal range, and then the input-output signal change curve is fitted to obtain the pressure value of the energy storage medium in the high-temperature energy storage system, improving the accuracy of the pressure monitoring result of the capacitive pressure sensor for the high-temperature energy storage system.

[0081] Embodiment 1

[0082] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of a high-temperature energy storage monitoring method based on a capacitive pressure sensor disclosed in an embodiment of the present invention. Among them, Figure 1 The described high-temperature energy storage monitoring method based on a capacitive pressure sensor can be applied to a high-temperature energy storage monitoring device based on a capacitive pressure sensor. The high-temperature energy storage monitoring device based on a capacitive pressure sensor can be integrated in a cloud server or a local server, and the embodiments of the present invention do not make any limitations.

[0083] Among them, Figure 1 The described high-temperature energy storage monitoring method based on a capacitive pressure sensor is used to monitor the pressure of the energy storage medium in the high-temperature energy storage system through a capacitive pressure sensor. The capacitance value of the capacitor device in the capacitive pressure sensor changes with the change of the pressure of the energy storage medium, so that the output signal output after the input signal passes through the capacitive pressure sensor changes. The high-temperature energy storage monitoring method based on a capacitive pressure sensor may include the following operations:

[0084] Step 101: Fix the input signal and determine whether the change value of the output signal within a preset time range is greater than or equal to a preset change threshold.

[0085] In the embodiments of the present invention, during the monitoring of the high-temperature energy storage system, first, in the common mode: fix the input signal, observe the change of the output signal according to the change of the pressure of the energy storage medium, and judge the pressure of the energy storage medium. However, this common mode is applicable to the measurement when the temperature of the energy storage medium is stable. When the temperature of the energy storage medium is unstable, various fluctuations will occur in the output signal. Especially when the temperature of the energy storage medium is constantly changing, for example, the temperature of the energy storage medium continuously decreases due to unstable heat sources, etc. In the embodiments of the present invention, by judging whether the change value of the output signal within a preset time range is greater than or equal to a preset change threshold, the stability of the temperature and pressure of the energy storage medium is judged. Because in the high-temperature energy storage system, the fluctuation of the pressure is usually related to the fluctuation of the temperature. When the high-temperature energy storage system is relatively stable, the pressure and temperature of the energy storage medium are relatively stable or change relatively gently. In the embodiments of the present invention, optionally, the preset time range can be any time period less than 0.5S. The smaller the preset time range, the more the volatility of the temperature can be reflected. Further optionally, a reasonable change threshold can be determined by analyzing the historical data of the high-temperature energy storage system. For example, if the pressure change speed of a certain high-temperature energy storage system under normal operation does not exceed a specific value, then the change threshold is determined based on this specific value. For example, if the change value of the voltage of the output signal within the preset 0.4S time range is 0.9V, exceeding the preset change threshold of 0.1V, it is judged that the energy storage medium is unstable at this time.

[0086] In an optional embodiment, the change value can also be the change value of parameters such as the variance or standard deviation of the curve on the curve of the output signal changing with time, which can more accurately judge the stability of the energy storage medium.

[0087] Step 102: If it is judged that the change value of the output signal within the preset time range is less than the preset change threshold, then determine the pressure of the energy storage medium in the high-temperature energy storage system according to the output signal.

[0088] In the embodiments of the present invention, if it is judged that the change value of the output signal within the preset time range is less than the preset change threshold, it means that the energy storage medium is stable and its temperature has not changed significantly. At this time, the common pressure measurement mode is used: determine the pressure of the energy storage medium in the high-temperature energy storage system according to the output signal.

[0089] Step 103: If it is judged that the change value of the output signal within the preset time range is greater than or equal to the preset change threshold, then perform the following operations:

[0090] Control the input signal to vary within a preset signal range, and obtain the output signals corresponding to different input signals; according to the different input signals and the output signals corresponding to each input signal, fit to obtain an input-output signal variation curve, which is used to represent the corresponding relationship between the output signal and the input signal.

[0091] In an embodiment of the present invention, if it is determined that the variation value of the output signal within a preset time range is greater than or equal to a preset variation threshold, it indicates that the energy storage medium is unstable and its temperature has probably changed significantly. At this time, if the common mode is used for pressure measurement, the accuracy of the measured pressure value will be reduced due to the influence of temperature. In an embodiment of the present invention, the input signal is controlled to vary within a preset signal range, and the output signals corresponding to different input signals are obtained. For example, for an AC input signal, the frequency of the input signal can be fixed, the voltage of the input signal is controlled to increase by 0.1V at intervals within 0V to 36V, and the voltage of the output signal obtained after each increase is obtained. Subsequently, according to the different input signals and the output signals corresponding to each input signal, an input-output signal variation curve is fitted.

[0092] Step 104: Determine the pressure value of the energy storage medium in the high-temperature energy storage system according to the input-output signal variation curve.

[0093] In an embodiment of the present invention, the input-output signal variation curve not only contains the information of the output signal changing with the input signal, but also contains the information of the change of the output signal caused by the influence of temperature. Therefore, by analyzing the input-output signal variation curve, the information of the output signal changing with the input signal and the information of the change of the output signal caused by the influence of temperature can be distinguished respectively, so as to obtain the pressure value of the energy storage medium in the high-temperature energy storage system. Optionally, if the temperature of the energy storage medium does not change, the same operation in step 103 is performed, and a stable input-output signal variation curve can also be obtained. In an embodiment of the present invention, due to the change of temperature, there is a deviation between the finally fitted input-output signal variation curve and the stable input-output signal variation curve. Therefore, based on the analysis of the above deviation, the influence of temperature can be excluded to determine the pressure value of the energy storage medium. Optionally, a series of curves with known temperatures and pressures of the energy storage medium can be determined in advance, and the pressure value of the energy storage medium can be determined by matching the known curve corresponding to the input-output signal variation curve.

[0094] For example, when the energy storage medium in a high-temperature energy storage system is in the endothermic stage and its temperature is continuously rising, the temperature of the capacitive pressure sensor also keeps increasing under the influence of the temperature of the energy storage medium. Therefore, for a capacitive pressure sensor whose temperature is constantly changing, the method of measuring its temperature in the prior art can only obtain the temperature information at a certain instant, but cannot obtain the temperature change information. However, the input-output signal change curve in the embodiment of the present invention contains the temperature change information. Based on the analysis of the input-output signal change curve, a more accurate measurement result can be obtained while taking into account the temperature change information.

[0095] It can be seen that by implementing the high-temperature energy storage monitoring method based on a capacitive pressure sensor in the embodiment of the present invention, it is possible to determine whether the state of the energy storage medium in the high-temperature energy storage system is stable. If the state of the energy storage medium is stable, the pressure of the energy storage medium can be directly determined according to the output signal corresponding to the fixed input signal, and the operation is simple and efficient. If the state of the energy storage medium is unstable, the input signal is controlled to change within a preset signal range, and then the input-output signal change curve is fitted. The input-output signal change curve not only contains the information of the output signal changing with the input signal, but also contains the information of the change of the output signal caused by the influence of temperature. Therefore, by analyzing the input-output signal change curve, the information of the output signal changing with the input signal and the information of the change of the output signal caused by the influence of temperature can be distinguished respectively, so as to obtain the pressure value of the energy storage medium in the high-temperature energy storage system, and the accuracy of the pressure monitoring result of the capacitive pressure sensor for the high-temperature energy storage system is improved.

[0096] In an optional embodiment, controlling the input signal to change within a preset signal range and obtaining the output signals corresponding to different input signals; fitting the input-output signal change curve according to the different input signals and the output signals corresponding to each input signal may include:

[0097] At each preset target moment, controlling the input signal to change within a preset signal range and obtaining the output signals corresponding to different input signals; fitting the input-output signal change curve corresponding to the target moment according to the different input signals and the output signals corresponding to each input signal;

[0098] And determining the pressure value of the energy storage medium in the high-temperature energy storage system according to the input-output signal change curve includes:

[0099] For the target moment to be monitored, according to the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a preset plurality of target moments before the target moment to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored.

[0100] Since the temperature change of the energy storage medium is difficult to predict, if the input-output signal change curve is obtained by fitting based on only one-time data acquisition, the accuracy is still insufficient. Therefore, in order to further improve the accuracy of the monitoring result, in this alternative embodiment, once it is determined that the state of the energy storage medium is unstable, multiple fittings of the input-output signal change curve will be performed. For example, the input-output signal change curve can be obtained periodically. In addition, for the determination of the pressure value of the energy storage medium at a certain moment, it will be obtained based on the analysis of the input-output signal change curves obtained by fitting at several historical moments combined with the input-output signal change curve obtained by fitting at this moment.

[0101] This alternative embodiment is illustrated as follows:

[0102] If it is determined at time a that the change value of the output signal within the preset time range is greater than or equal to the preset change threshold, then at times b, c, d, e, and f after time a with a time interval of 1 s, the following operations will be performed once each: control the voltage of the input signal to increase by 0.1 V at intervals within the range of 0 V to 36 V, and obtain the voltage of the output signal after each increase. Subsequently, according to different input signals and the output signals corresponding to each input signal, the input-output signal change curves corresponding to each moment are obtained by fitting.

[0103] For the monitoring of the pressure value of the energy storage medium at time f, it is obtained by analyzing the five curves corresponding to times b, c, d, e, and f. Among them, the five curves corresponding to times b, c, d, e, and f not only contain the information of the output signal changing with the input signal, but also contain the information of the change of the output signal caused by the influence of temperature within a period of time. Therefore, by analyzing the five curves corresponding to times b, c, d, e, and f, the change of the temperature of the capacitive sensor can be measured more accurately, thereby obtaining a more accurate pressure value of the energy storage medium.

[0104] It can be seen that in this alternative embodiment, once it is determined that the state of the energy storage medium is unstable, multiple fittings of the input-output signal change curve will be performed. For the determination of the pressure value of the energy storage medium at a certain moment, it will be obtained based on the analysis of the input-output signal change curves obtained by fitting at several historical moments combined with the input-output signal change curve obtained by fitting at this moment. The change of the temperature of the capacitive sensor can be measured more accurately, thereby obtaining a more accurate pressure value of the energy storage medium.

[0105] In another alternative embodiment, when it is determined that the change value of the output signal within the preset time range is greater than or equal to the preset change threshold, the method may further include:

[0106] Obtain the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to each target moment within the preset set of target moments, where the set of target moments includes a number of consecutive target moments;

[0107] Calculate the dispersion parameter of the pressure values of the energy storage medium in the high-temperature energy storage system corresponding to all target moments within the set of target moments;

[0108] Determine whether the dispersion parameter corresponding to the set of target moments is less than or equal to a preset dispersion threshold. If it is determined that the dispersion parameter corresponding to the set of target moments is less than or equal to the preset dispersion threshold, then re-trigger the operation of fixing the input signal and determining whether the change value of the output signal within the preset time range is greater than or equal to the preset change threshold.

[0109] In this alternative embodiment, after determining that the state of the energy storage medium is unstable, a method of fitting the input-output signal change curve will be used for the monitoring process of the pressure of the energy storage medium. However, the above monitoring mode requires a high computational load. If the above mode is always used, it will bring a huge consumption in terms of computational volume. Therefore, in this alternative embodiment, by calculating the dispersion parameter, it is determined whether the fluctuations of the temperature or pressure of the energy storage medium are gradually becoming gentle. Among them, the dispersion parameter includes at least one of range, variance, standard deviation, and mean square deviation. The dispersion parameter can measure the fluctuations of the curve and can be well used to determine whether the fluctuations of the temperature or pressure of the energy storage medium are gradually becoming gentle. Once it is determined that the dispersion parameter corresponding to the set of target moments is less than or equal to the preset dispersion threshold, then re-trigger the operation of fixing the input signal and determining whether the change value of the output signal within the preset time range is greater than or equal to the preset change threshold. Thus, it enters a conventional pressure monitoring mode with a lower computational load.

[0110] It can be seen that in this alternative embodiment, by calculating the dispersion parameter, it can be determined whether the fluctuations of the temperature or pressure of the energy storage medium are gradually becoming gentle. Once it is determined that the dispersion parameter corresponding to the set of target moments is less than or equal to the preset dispersion threshold, it enters a conventional pressure monitoring mode with a lower computational load, thereby reducing the computational volume of pressure monitoring and improving the monitoring efficiency of the pressure of the energy storage medium in the high-temperature energy storage system.

[0111] In yet another alternative embodiment, for the target moment to be monitored, according to the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a preset number of target moments before the target moment to be monitored, determining the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored may include:

[0112] For the target moment to be monitored, input the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a preset number of target moments before the target moment to be monitored into a preset curve analysis model, and obtain the temperature state parameter output by the curve analysis model. The temperature state parameter is used to represent the temperature change trend of the capacitor device in the capacitive pressure sensor;

[0113] For the target moment to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored according to the input-output signal change curve corresponding to the target moment to be monitored and the temperature state parameter;

[0114] In this optional embodiment, the curve analysis model is obtained using multiple sets of training data sets. Each set of training data sets includes a set of input-output signal training curves and the temperature state parameters corresponding to the set of input-output signal training curves. The curve analysis model is used to determine the temperature state parameter according to a set of training input-output signal change curves.

[0115] This optional embodiment is illustrated as follows:

[0116] At moment a, if it is determined that the change value of the output signal within the preset time range is greater than or equal to the preset change threshold, then at moments b, c, d, e, and f after moment a with a time interval of 1 s, the following operations are respectively performed once: control the voltage of the input signal to increase by 0.1 V at intervals within 0 V to 36 V, and obtain the voltage of the output signal obtained after each increase. Subsequently, according to different input signals and the output signals corresponding to each input signal, fit the input-output signal change curves corresponding to each moment.

[0117] For the monitoring of the pressure value of the energy storage medium at moment f, input the five curves corresponding to moments b, c, d, e, and f into the preset curve analysis model, obtain the temperature state parameter output by the curve analysis model, and then determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to moment f according to the curve corresponding to moment f and the temperature state parameter.

[0118] It can be seen that in this optional embodiment, first, the curve analysis model extracts the change information of the output signal caused by temperature over a period of time in the multiple curves corresponding to multiple target moments, that is, the temperature state parameter. Then, according to the input-output signal change curve corresponding to the target moment to be monitored and the temperature state parameter, the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored is determined, thereby further improving the monitoring efficiency and monitoring accuracy of the pressure of the energy storage medium in the high-temperature energy storage system.

[0119] Embodiment Two

[0120] Please refer toFigure 2 , Figure 2 is a schematic flowchart of another high-temperature energy storage monitoring method based on a capacitive pressure sensor disclosed in an embodiment of the present invention. Among them, Figure 2 the described high-temperature energy storage monitoring method based on a capacitive pressure sensor can be applied to a high-temperature energy storage monitoring device based on a capacitive pressure sensor. The high-temperature energy storage monitoring device based on a capacitive pressure sensor can be integrated in a cloud server or a local server, which is not limited in the embodiments of the present invention.

[0121] Among them, Figure 2 the described high-temperature energy storage monitoring method based on a capacitive pressure sensor is used to monitor the pressure of the energy storage medium in the high-temperature energy storage system through a capacitive pressure sensor. The capacitance value of the capacitor device in the capacitive pressure sensor changes with the change of the pressure of the energy storage medium, so that the output signal output after the input signal passes through the capacitive pressure sensor changes. The high-temperature energy storage monitoring method based on a capacitive pressure sensor may include the following operations:

[0122] Step 201, fix the input signal, and determine whether the change value of the output signal within a preset time range is greater than or equal to a preset change threshold.

[0123] Step 202, if it is determined that the change value of the output signal within the preset time range is less than the preset change threshold, then determine the pressure of the energy storage medium in the high-temperature energy storage system according to the output signal.

[0124] Step 203, if it is determined that the change value of the output signal within the preset time range is greater than or equal to the preset change threshold, then perform the following operations:

[0125] Control the input signal to change within a preset signal range, and obtain the output signals corresponding to different input signals; according to the different input signals and the output signals corresponding to each input signal, fit an input-output signal change curve, and the input-output signal change curve is used to represent the corresponding relationship between the output signal and the input signal.

[0126] Step 204, determine the pressure value of the energy storage medium in the high-temperature energy storage system according to the input-output signal change curve.

[0127] For the specific descriptions of steps 201 to 204, please refer to the descriptions of steps 101-step 104 in Embodiment 1, which will not be repeated in the embodiments of the present invention.

[0128] Step 205, for each target capacitive pressure sensor in the high-temperature energy storage system, save the pressure value of the energy storage medium in the high-temperature energy storage system determined by the target capacitive pressure sensor to the sensor node corresponding to the target capacitive pressure sensor.

[0129] In the embodiments of the present invention, the sensor node is the node corresponding to the target capacitive pressure sensor on the pressure knowledge graph constructed based on the high-temperature energy storage system. The knowledge graph is a technology that describes knowledge and information in a graphical structure. It constructs a huge knowledge network by representing entities (such as people, places, things, etc.) and the relationships between them in the form of nodes and edges. Entities in the knowledge graph refer to specific things or abstract concepts in the real world. For example, people, places, organizations, events, products, etc. can all be used as entities. Entities are usually represented by unique identifiers, such as using digital numbers, names, or URLs, etc. In the knowledge graph, an entity can have multiple attributes to describe its characteristics. For example, a sensor node can include position, current pressure magnitude, historical pressure magnitude, etc. A relationship refers to the connection or association between entities. For example, the upstream and downstream relationships between sensor nodes, the kinship between people, the geographical location relationship between places, the causal relationship between events, etc. are all relationships in the knowledge graph.

[0130] In the embodiments of the present invention, a pressure knowledge graph is constructed based on the high-temperature energy storage system, so as to realize more efficient storage and analysis of the pressure data on the high-temperature energy storage system.

[0131] Step 206: According to the pressure values saved by all sensor nodes on the pressure knowledge graph, determine several pressure propagation directions from the pressure knowledge graph, and determine the pressure distribution parameters corresponding to the high-temperature energy storage system according to all the pressure propagation directions and the pressure values saved by all sensor nodes on the pressure knowledge graph.

[0132] In the embodiments of the present invention, a single capacitive pressure sensor can only monitor the pressure at a certain position in the high-temperature energy storage system. For the pressure distribution of the energy storage medium at each position in the entire high-temperature energy storage system, a more efficient storage and representation method is also required. In the embodiments of the present invention, a pressure knowledge graph is constructed based on the high-temperature energy storage system. According to the pressure values saved by all sensor nodes on the pressure knowledge graph, several pressure propagation directions are determined from the pressure knowledge graph. When the high-temperature energy storage medium operates stably, only the relationships between all sensor nodes in the pressure knowledge graph are needed to determine the theoretical pressure propagation direction. However, in practical applications, especially when the high-temperature energy storage system starts or is about to stop running, due to the instability of the energy storage medium, the pressure propagation direction changes; on the other hand, when there are faults such as blockages in the high-temperature energy storage system, it will also cause changes in the pressure propagation direction. Therefore, in the embodiments of the present invention, several pressure propagation directions are determined from the pressure knowledge graph according to the pressure values saved by all sensor nodes on the pressure knowledge graph, so as to obtain the real pressure propagation direction.

[0133] In the embodiments of the present invention, the pressure distribution parameter is used to represent the pressure distribution on the high-temperature energy storage system. It not only represents the pressure magnitude at each sensor position, but also includes the pressure values at the positions between any two sensors. Therefore, it is necessary to calculate the pressure values at the positions between any two sensors based on the true pressure propagation direction and the pressure results monitored by the capacitive pressure sensors, so as to obtain the pressure distribution parameter. Based on the pressure distribution parameter, the user can determine the pressure value at any position on the high-temperature energy storage system.

[0134] It can be seen that by implementing the high-temperature energy storage monitoring method based on capacitive pressure sensors in the embodiments of the present invention, a pressure knowledge graph is constructed based on the high-temperature energy storage system, so that more efficient storage and analysis of the pressure data on the high-temperature energy storage system can be realized. In addition, according to all the pressure propagation directions and the pressure values stored in all the sensor nodes on the pressure knowledge graph in the embodiments of the present invention, the pressure distribution parameter corresponding to the high-temperature energy storage system is determined, which can more accurately analyze the pressure distribution on the high-temperature energy storage system.

[0135] In an optional embodiment, the method may further include:

[0136] Judge whether the pressure distribution parameter meets the preset abnormal pressure distribution condition. If the pressure distribution parameter meets the preset abnormal pressure distribution condition, trigger the execution of the following operations:

[0137] For each preset update time point, update the pressure values stored in all the sensor nodes on the pressure knowledge graph according to the pressure values determined by all the target capacitive pressure sensors in the high-temperature energy storage system at this update time point, and obtain the updated pressure knowledge graph corresponding to this update time point;

[0138] For each preset update time point, determine the faulty nodes on the updated pressure knowledge graph according to the pressure values stored in all the sensor nodes on the updated pressure knowledge graph corresponding to this update time point, and determine the faulty-related nodes corresponding to the faulty nodes; according to all the faulty nodes and all the faulty-related nodes corresponding to this update time point, determine the faulty weight value of each sensor node on the updated pressure knowledge graph corresponding to this update time point. The faulty weight value is used to measure the influence degree of the corresponding sensor node on the fault;

[0139] Determine the target faulty node according to the faulty weight values of each sensor node on the updated pressure knowledge graphs corresponding to all the update time points, and determine the target faulty position on the high-temperature energy storage system according to the target faulty node.

[0140] In this alternative embodiment, once a fault occurs at a certain point on the high-temperature energy storage system, the fault will affect a series of subsequent positions and may even cause the entire energy storage system to shut down. Therefore, a method for tracing the fault location is proposed in this alternative embodiment. Among them, the preset abnormal pressure distribution condition can be based on the pressure distribution recorded in previous fault situations. For example, the pressure at a certain medium outlet should be lower than that at other positions. Therefore, once the pressure at this medium outlet is higher than that at other positions, a fault may have occurred.

[0141] In this alternative embodiment, once it is determined that the pressure distribution parameter meets the preset abnormal pressure distribution condition, a series of update time points are preset within a certain period in the future, and the updated pressure knowledge graph is updated at each update time point, so as to obtain the influence process of the fault on the high-temperature energy storage system. For example, if there is a blockage at position A, then as time goes by, the blockage at position A will gradually affect positions B, C, D, E, etc. By updating the updated pressure knowledge graph at each update time point in this alternative embodiment, it can exactly reflect the above-mentioned fault diffusion process.

[0142] For each preset update time point, the fault nodes on the updated pressure knowledge graph are determined, and the fault-related nodes corresponding to the fault nodes are determined. At this time, the fault nodes are only the node positions where the pressure is abnormal, and may not be the actual fault positions, because a fault at one position will cause abnormal conditions at different positions. Therefore, a method for tracing the fault location needs to be adopted to determine the target fault node where the actual fault occurs from several fault nodes.

[0143] In the embodiment of the present invention, the fault weight value is used to measure the influence degree of the corresponding sensor node on the fault. According to all the fault nodes and all the fault-related nodes corresponding to this update time point, the fault weight value of each sensor node on the updated pressure knowledge graph corresponding to this update time point can be determined. Optionally, the corresponding fault weight value is determined according to the frequency of each node. Finally, according to the fault weight values of each sensor node on the updated pressure knowledge graphs corresponding to all update time points, the target fault node is determined, and the target fault location on the high-temperature energy storage system is determined according to the target fault node.

[0144] It can be seen that this alternative embodiment proposes a method for tracing the fault location. Once it is determined that the pressure distribution parameter meets the preset abnormal pressure distribution condition, a series of update time points are preset within a certain period in the future, and the updated pressure knowledge graph is updated at each update time point, so as to obtain the influence process of the fault on the high-temperature energy storage system. Finally, according to the calculation of the fault weight values of each sensor node, the target fault location is determined, thus realizing the tracing of the fault location on the high-temperature energy storage system.

[0145] In another optional embodiment, for each preset update time point, determining the faulty nodes on the updated pressure knowledge graph according to the pressure values saved by all sensor nodes on the updated pressure knowledge graph corresponding to the update time point may include:

[0146] For each sensor node on the updated pressure knowledge graph corresponding to each preset update time point, determining the expected pressure value corresponding to the sensor node according to the pressure values saved by all related nodes associated with the sensor node; determining whether the difference between the pressure value saved by the sensor node and the expected pressure value is greater than a preset fault threshold. If it is determined that the difference between the pressure value saved by the sensor node and the expected pressure value is greater than the preset fault threshold, then determining that the sensor node is a faulty node.

[0147] In this optional embodiment, the expected pressure value corresponding to the sensor node represents the pressure value of the sensor deduced according to the pressure values of other sensors related to the sensor on the assumption that the high-temperature energy storage system has no faults. Under normal circumstances, the difference between the expected pressure value corresponding to the sensor node and the actually obtained pressure value is not too large. If it is determined that the difference between the pressure value saved by the sensor node and the expected pressure value is greater than the preset fault threshold, then determining that the sensor node is a faulty node. It can be seen that this optional embodiment can more reasonably determine the faulty nodes based on the analysis of the expected pressure values of the sensor nodes.

[0148] Embodiment III

[0149] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of a high-temperature energy storage monitoring device based on a capacitive pressure sensor disclosed in an embodiment of the present invention. The high-temperature energy storage monitoring device based on a capacitive pressure sensor is used to monitor the pressure of the energy storage medium in the high-temperature energy storage system through a capacitive pressure sensor. The capacitance value of the capacitor component in the capacitive pressure sensor changes with the change of the pressure of the energy storage medium, so that the output signal output after the input signal passes through the capacitive pressure sensor changes. As Figure 3 shown, the high-temperature energy storage monitoring device based on a capacitive pressure sensor may include:

[0150] A signal judgment module 301, configured to fix the input signal and judge whether the change value of the output signal within a preset time range is greater than or equal to a preset change threshold;

[0151] A first monitoring module 302, configured to determine the pressure of the energy storage medium in the high-temperature energy storage system according to the output signal when it is judged that the change value of the output signal within the preset time range is less than the preset change threshold;

[0152] A curve fitting module 303 is configured to, when it is determined that the change value of the output signal within a preset time range is greater than or equal to a preset change threshold, control the input signal to change within a preset signal range and obtain the output signals corresponding to different input signals; and fit an input-output signal change curve based on the different input signals and the output signals corresponding to each input signal, where the input-output signal change curve is used to represent the corresponding relationship between the output signal and the input signal.

[0153] A second monitoring module 304 is configured to determine the pressure value of the energy storage medium in the high-temperature energy storage system according to the input-output signal change curve.

[0154] It can be seen that the high-temperature energy storage monitoring device based on the capacitive pressure sensor in the embodiment of the present invention can determine whether the state of the energy storage medium in the high-temperature energy storage system is stable. If the state of the energy storage medium is stable, the pressure of the energy storage medium is directly determined according to the output signal corresponding to the fixed input signal, and the operation is simple and efficient. If the state of the energy storage medium is unstable, the input signal is controlled to change within the preset signal range, and then the input-output signal change curve is fitted. The input-output signal change curve not only includes the information of the change of the output signal with the change of the input signal, but also includes the change information of the output signal caused by the influence of temperature. Therefore, by analyzing the input-output signal change curve, the information of the change of the output signal with the change of the input signal and the change information of the output signal caused by the influence of temperature can be distinguished respectively, so as to obtain the pressure value of the energy storage medium in the high-temperature energy storage system, and the accuracy of the pressure monitoring result of the capacitive pressure sensor for the high-temperature energy storage system is improved.

[0155] In an optional embodiment, the specific manner in which the curve fitting module 303 controls the input signal to change within the preset signal range and obtains the output signals corresponding to different input signals, and fits an input-output signal change curve based on the different input signals and the output signals corresponding to each input signal, may include:

[0156] At each preset target moment, control the input signal to change within the preset signal range and obtain the output signals corresponding to different input signals; and fit an input-output signal change curve corresponding to the target moment based on the different input signals and the output signals corresponding to each input signal.

[0157] In addition, the specific manner in which the second monitoring module 304 determines the pressure value of the energy storage medium in the high-temperature energy storage system according to the input-output signal change curve may include:

[0158] For a target moment to be monitored, based on the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a preset plurality of target moments before the target moment to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored.

[0159] It can be seen that in this alternative embodiment, once it is determined that the state of the energy storage medium is unstable, fitting of the input-output signal change curves will be performed multiple times. For the determination of the pressure value of the energy storage medium at a certain moment, it will be obtained based on the analysis of the input-output signal change curve fitted from several historical moments combined with the input-output signal change curve fitted at this moment. It can more accurately measure the change of the temperature of the capacitive sensor, and thus obtain a more accurate pressure value of the energy storage medium.

[0160] In another alternative embodiment, as Figure 4 shown, the device may further include:

[0161] A periodic monitoring module 305, configured to, when the signal judgment module 301 determines that the change value of the output signal within a preset time range is greater than or equal to a preset change threshold, obtain the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to each target moment in a preset set of target moments, and the set of target moments includes several consecutive target moments;

[0162] A discrete analysis module 306, configured to calculate a discrete degree parameter of the pressure values of the energy storage medium in the high-temperature energy storage system corresponding to all target moments in the set of target moments, and the discrete degree parameter includes at least one of range, variance, standard deviation, and mean square deviation;

[0163] A trigger judgment module 307, configured to judge whether the discrete degree parameter corresponding to the set of target moments is less than or equal to a preset discrete degree threshold. If it is judged that the discrete degree parameter corresponding to the set of target moments is less than or equal to the preset discrete degree threshold, then trigger the signal judgment module 301 again to execute the operation of judging whether the change value of the output signal within a preset time range is greater than or equal to the preset change threshold for a fixed input signal.

[0164] It can be seen that in this alternative embodiment, it is possible to judge whether the fluctuation of the temperature or pressure of the energy storage medium is gradually becoming gentle through the calculation of the discrete degree parameter. Once it is judged that the discrete degree parameter corresponding to the set of target moments is less than or equal to the preset discrete degree threshold, it enters a conventional pressure monitoring mode with a lower calculation amount, thereby reducing the calculation amount of pressure monitoring and improving the monitoring efficiency of the pressure of the energy storage medium in the high-temperature energy storage system.

[0165] In yet another alternative embodiment, for the target moment to be monitored, the specific manner in which the second monitoring module 304 determines the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored according to the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a plurality of preset target moments before the target moment to be monitored may include:

[0166] For the target moment to be monitored, input the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a plurality of preset target moments before the target moment to be monitored into a preset curve analysis model, and obtain the temperature state parameter output by the curve analysis model. The temperature state parameter is used to represent the temperature change trend of the capacitor device in the capacitive pressure sensor;

[0167] For the target moment to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored according to the input-output signal change curve corresponding to the target moment to be monitored and the temperature state parameter;

[0168] Among them, the curve analysis model is obtained using multiple sets of training data sets. Each set of training data sets includes a set of input-output signal training curves and the temperature state parameters corresponding to the set of input-output signal training curves. The curve analysis model is used to determine the temperature state parameter according to a set of training input-output signal change curves.

[0169] It can be seen that in this alternative embodiment, the curve analysis model is first used to extract the change information of the output signal caused by temperature influence within a period of time in the multiple curves corresponding to multiple target moments, that is, the temperature state parameter. Then, according to the input-output signal change curve corresponding to the target moment to be monitored and the temperature state parameter, the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored is determined, thereby further improving the monitoring efficiency and monitoring accuracy of the pressure of the energy storage medium in the high-temperature energy storage system.

[0170] In yet another alternative embodiment, several target capacitive pressure sensors are provided in the high-temperature energy storage system, and the device further includes:

[0171] A map update module 308, configured to save, for each target capacitive pressure sensor in the high-temperature energy storage system, the pressure value of the energy storage medium in the high-temperature energy storage system determined by the target capacitive pressure sensor to the sensor node corresponding to the target capacitive pressure sensor; wherein, the sensor node is the node corresponding to the target capacitive pressure sensor on the pressure knowledge map constructed based on the high-temperature energy storage system;

[0172] A pressure analysis module 309 is configured to determine a plurality of pressure propagation directions from a pressure knowledge graph based on the pressure values stored in all sensor nodes on the pressure knowledge graph, and determine pressure distribution parameters corresponding to the high-temperature energy storage system according to all the pressure propagation directions and the pressure values stored in all sensor nodes on the pressure knowledge graph. The pressure distribution parameters are used to represent the pressure distribution on the high-temperature energy storage system.

[0173] It can be seen that in this alternative embodiment, a pressure knowledge graph is constructed based on the high-temperature energy storage system, so as to achieve more efficient storage and analysis of the pressure data on the high-temperature energy storage system. In addition, in the embodiment of the present invention, according to all the pressure propagation directions and the pressure values stored in all sensor nodes on the pressure knowledge graph, the pressure distribution parameters corresponding to the high-temperature energy storage system are determined, which can more accurately analyze the pressure distribution on the high-temperature energy storage system.

[0174] In yet another alternative embodiment, the device may further include:

[0175] A pressure judgment module 310 is configured to judge whether the pressure distribution parameters meet a preset abnormal pressure distribution condition;

[0176] A period update module 311 is configured to, when the pressure judgment module 310 judges that the pressure distribution parameters meet the preset abnormal pressure distribution condition, for each preset update time point, update the pressure values stored in all sensor nodes on the pressure knowledge graph according to the pressure values determined by all target capacitive pressure sensors in the high-temperature energy storage system at this update time point, and obtain an updated pressure knowledge graph corresponding to this update time point;

[0177] A fault analysis module 312 is configured to, for each preset update time point, determine fault nodes on the updated pressure knowledge graph according to the pressure values stored in all sensor nodes on the updated pressure knowledge graph corresponding to this update time point, and determine fault-related nodes corresponding to the fault nodes; according to all the fault nodes and all the fault-related nodes corresponding to this update time point, determine the fault weight value of each sensor node on the updated pressure knowledge graph corresponding to this update time point. The fault weight value is used to measure the influence degree of the corresponding sensor node on the fault;

[0178] A fault determination module 313 is configured to determine a target fault node according to the fault weight values of each sensor node on the updated pressure knowledge graphs corresponding to all update time points, and determine the target fault location on the high-temperature energy storage system according to the target fault node.

[0179] It can be seen that in this optional embodiment, a method for tracing the fault location is proposed. Once it is determined that the pressure distribution parameter satisfies the preset abnormal pressure distribution condition, a series of update time points are preset within a certain period in the future, and the updated pressure knowledge graph is updated at each update time point, so as to obtain the influence process of the fault on the high-temperature energy storage system. Finally, based on the calculation of the fault weight value of each sensor node, the target fault location is determined, thus realizing the tracing of the fault location on the high-temperature energy storage system.

[0180] In another optional embodiment, for each preset update time point, the specific manner for the fault analysis module 312 to determine the fault nodes on the updated pressure knowledge graph according to the pressure values saved by all sensor nodes on the updated pressure knowledge graph corresponding to this update time point may include:

[0181] For each sensor node on the updated pressure knowledge graph corresponding to each preset update time point, according to the pressure values saved by all related nodes associated with this sensor node, determine the expected pressure value corresponding to this sensor node; judge whether the difference between the pressure value saved by this sensor node and the expected pressure value is greater than the preset fault threshold. If it is determined that the difference between the pressure value saved by this sensor node and the expected pressure value is greater than the preset fault threshold, then determine that this sensor node is a fault node.

[0182] In this optional embodiment, the expected pressure value corresponding to the sensor node represents the pressure value of this sensor deduced according to the pressure values of other sensors related to this sensor assuming that the high-temperature energy storage system has no fault. Under normal circumstances, the difference between the expected pressure value corresponding to the sensor node and the actually obtained pressure value is not too large. If it is determined that the difference between the pressure value saved by this sensor node and the expected pressure value is greater than the preset fault threshold, then determine that this sensor node is a fault node. It can be seen that this optional embodiment can more reasonably determine the fault nodes based on the analysis of the expected pressure values of the sensor nodes.

[0183] Embodiment 4

[0184] Please refer to Figure 5 , Figure 5 which is a schematic structural diagram of another high-temperature energy storage monitoring device based on a capacitive pressure sensor disclosed in the embodiments of the present invention. As Figure 5 shown, the high-temperature energy storage monitoring device based on a capacitive pressure sensor may include:

[0185] A memory 401 storing executable program code;

[0186] A processor 402 coupled to the memory 401;

[0187] The processor 402 calls the executable program code stored in the memory 401 and executes the steps in the method for monitoring high-temperature energy storage based on a capacitive pressure sensor described in Embodiment 1 or Embodiment 2 of the present invention.

[0188] Embodiment 5

[0189] An embodiment of the present invention discloses a computer storage medium. The computer storage medium stores computer instructions, which are used to execute the steps in the method for monitoring high-temperature energy storage based on a capacitive pressure sensor described in Embodiment 1 or Embodiment 2 of the present invention when the computer instructions are called.

[0190] Embodiment 6

[0191] An embodiment of the present invention discloses a computer program product. The computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the method for monitoring high-temperature energy storage based on a capacitive pressure sensor described in Embodiment 1 or Embodiment 2.

[0192] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0193] Through the specific descriptions of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, and the storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other computer-readable medium that can be used to carry or store data.

[0194] Finally, it should be noted that: the monitoring method, device, and medium based on a capacitive pressure sensor disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, and are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A high-temperature energy storage monitoring method based on a capacitive pressure sensor, which is used to monitor the pressure of the energy storage medium in a high-temperature energy storage system through the capacitive pressure sensor. The capacitance value of the capacitor device in the capacitive pressure sensor changes with the change of the pressure of the energy storage medium, so that the voltage of the input signal changes after passing through the capacitive pressure sensor to output the voltage of the output signal. It is characterized in that, The method includes: Fix the voltage of the input signal, and determine whether the change value of the voltage of the output signal within a preset time range is greater than or equal to a preset change threshold; If it is determined that the change value of the voltage of the output signal within the preset time range is less than the preset change threshold, determine the pressure of the energy storage medium in the high-temperature energy storage system according to the output signal; If it is determined that the change value of the voltage of the output signal within a preset time range is greater than or equal to the preset change threshold, perform the following operations: At each preset target moment, control the voltage of the input signal to change within a preset voltage range, and obtain the output signals corresponding to different input signals; according to different input signals and the output signals corresponding to each input signal, fit an input-output signal change curve corresponding to this target moment, and the input-output signal change curve is used to represent the corresponding relationship between the output signal and the input signal; For the to-be-monitored target moment, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to this to-be-monitored target moment according to the input-output signal change curve corresponding to this to-be-monitored target moment and the input-output signal change curves corresponding to a preset plurality of the target moments before this to-be-monitored target moment.

2. The high-temperature energy storage monitoring method based on a capacitive pressure sensor according to claim 1, characterized in that When it is determined that the change value of the voltage of the output signal within a preset time range is greater than or equal to the preset change threshold, the method further includes: Obtain the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to each target moment within a preset set of target moments, and the set of target moments includes several consecutive target moments; Calculate the dispersion parameter of the pressure values of the energy storage medium in the high-temperature energy storage system corresponding to all the target moments within the set of target moments, and the dispersion parameter includes at least one of range, variance, standard deviation and mean square deviation; Judge whether the dispersion parameter corresponding to the set of target moments is less than or equal to a preset dispersion threshold. If it is determined that the dispersion parameter corresponding to the set of target moments is less than or equal to the preset dispersion threshold, re-trigger the operation of fixing the voltage of the input signal and determining whether the change value of the voltage of the output signal within a preset time range is greater than or equal to the preset change threshold.

3. The high-temperature energy storage monitoring method based on a capacitive pressure sensor according to claim 1, wherein The step of determining the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the to-be-monitored target moment according to the input-output signal change curve corresponding to the to-be-monitored target moment and the input-output signal change curves corresponding to a preset plurality of the target moments before the to-be-monitored target moment includes: For the target moment to be monitored, input the input-output signal change curve corresponding to the target moment to be monitored and the input-output signal change curves corresponding to a preset number of the target moments before the target moment to be monitored into a preset curve analysis model, and obtain the temperature state parameter output by the curve analysis model. The temperature state parameter is used to represent the temperature change trend of the capacitor device in the capacitive pressure sensor; For the target moment to be monitored, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to the target moment to be monitored according to the input-output signal change curve corresponding to the target moment to be monitored and the temperature state parameter; Among them, the curve analysis model is obtained using multiple sets of training data sets. Each set of training data sets includes a set of input-output signal training curves and the temperature state parameter corresponding to the set of input-output signal training curves. The curve analysis model is used to determine the temperature state parameter according to a set of training input-output signal change curves.

4. The high-temperature energy storage monitoring method based on a capacitive pressure sensor according to any one of claims 1-3, characterized in that, A number of target capacitive pressure sensors are arranged in the high-temperature energy storage system, and the method further includes: For each of the target capacitive pressure sensors in the high-temperature energy storage system, save the pressure value of the energy storage medium in the high-temperature energy storage system determined by the target capacitive pressure sensor to the sensor node corresponding to the target capacitive pressure sensor; among them, the sensor node is the node corresponding to the target capacitive pressure sensor on the pressure knowledge graph constructed based on the high-temperature energy storage system; According to the pressure values saved by all the sensor nodes on the pressure knowledge graph, determine a number of pressure propagation directions from the pressure knowledge graph. According to all the pressure propagation directions and the pressure values saved by all the sensor nodes on the pressure knowledge graph, determine the pressure distribution parameter corresponding to the high-temperature energy storage system. The pressure distribution parameter is used to represent the pressure distribution condition on the high-temperature energy storage system.

5. The high-temperature energy storage monitoring method based on a capacitive pressure sensor according to claim 4, wherein, The method further includes: Judge whether the pressure distribution parameter meets the preset abnormal pressure distribution condition. If the pressure distribution parameter meets the preset abnormal pressure distribution condition, trigger the execution of the following operations: For each preset update time point, update the pressure values saved by all the sensor nodes on the pressure knowledge graph according to the pressure values determined by all the target capacitive pressure sensors in the high-temperature energy storage system at the update time point, and obtain the updated pressure knowledge graph corresponding to the update time point; For each preset update time point, determine the fault nodes on the updated pressure knowledge graph according to the pressure values saved by all the sensor nodes on the updated pressure knowledge graph corresponding to the update time point, and determine the fault-related nodes corresponding to the fault nodes; according to all the fault nodes and all the fault-related nodes corresponding to the update time point, determine the fault weight value of each sensor node on the updated pressure knowledge graph corresponding to the update time point. The fault weight value is used to measure the influence degree of the corresponding sensor node on the fault; Based on the fault weight values of each sensor node on the updated pressure knowledge graph corresponding to all the above-mentioned update time points, a target fault node is determined, and based on the target fault node, the target fault location on the high-temperature energy storage system is determined.

6. The high-temperature energy storage monitoring method based on a capacitive pressure sensor according to claim 5, wherein For each preset update time point, determining the fault nodes on the updated pressure knowledge graph according to the pressure values stored by all the sensor nodes on the updated pressure knowledge graph corresponding to this update time point includes: For each sensor node on the updated pressure knowledge graph corresponding to each preset update time point, determining the expected pressure value corresponding to this sensor node according to the pressure values stored by all the related nodes having an association relationship with this sensor node; judging whether the difference between the pressure value stored by this sensor node and the expected pressure value is greater than a preset fault threshold, and if it is judged that the difference between the pressure value stored by this sensor node and the expected pressure value is greater than the preset fault threshold, determining that this sensor node is a fault node.

7. A high-temperature energy storage monitoring device based on a capacitive pressure sensor, which is used to monitor the pressure of the energy storage medium in the high-temperature energy storage system through the capacitive pressure sensor. The capacitance value of the capacitor device in the capacitive pressure sensor changes with the change of the pressure of the energy storage medium, so that the voltage of the input signal changes after passing through the capacitive pressure sensor to output the voltage of the output signal. It is characterized in that, The device includes: A signal judgment module, configured to fix the voltage of the input signal and judge whether the change value of the voltage of the output signal within a preset time range is greater than or equal to a preset change threshold; A first monitoring module, configured to, when it is judged that the change value of the voltage of the output signal within the preset time range is less than the preset change threshold, determine the pressure of the energy storage medium in the high-temperature energy storage system according to the output signal; A curve fitting module, configured to, when it is judged that the change value of the voltage of the output signal within a preset time range is greater than or equal to the preset change threshold, control the voltage of the input signal to change within a preset voltage range at each preset target moment, and obtain the output signals corresponding to different input signals; according to different input signals and the output signals corresponding to each input signal, fitting to obtain the input-output signal change curve corresponding to this target moment, and the input-output signal change curve is used to represent the corresponding relationship between the output signal and the input signal; A second monitoring module, configured to, for a to-be-monitored target moment, determine the pressure value of the energy storage medium in the high-temperature energy storage system corresponding to this to-be-monitored target moment according to the input-output signal change curve corresponding to this to-be-monitored target moment and the input-output signal change curves corresponding to a preset plurality of the target moments before this to-be-monitored target moment.

8. A high-temperature energy storage monitoring device based on a capacitive pressure sensor, characterized in that, The device includes: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory and executes the high-temperature energy storage monitoring method based on a capacitive pressure sensor according to any one of claims 1-6.

9. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the high-temperature energy storage monitoring method based on a capacitive pressure sensor according to any one of claims 1-6.

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