Performance detection method and system for solar-driven hydrogen fuel cell

Abstract

The invention provides a method and a system for detecting the performance of a solar-driven hydrogen fuel cell, and the method and the system are used for detecting the performance of one or more hydrogen fuel cells in the performance abnormality description range of one or more hydrogen fuel cells. The abnormal description is based on target hydrogen fuel cell performance data performance description elements obtained through hydrogen fuel cell performance data expansion operation of the corresponding to-be-processed performance description elements, and target abnormal description hydrogen fuel cell performance data is obtained; target abnormal description hydrogen fuel cell performance data is obtained, the target abnormal description hydrogen fuel cell performance data and hydrogen fuel cell data needing to be detected are fused, and a hydrogen fuel cell performance detection result is obtained; according to the method, the performance description elements of the same hydrogen fuel cell performance data can be accurately determined, and the performance detection result of the hydrogen fuel cell is improved, so that the performance information of the hydrogen fuel cell can be accurately obtained, and the hydrogen fuel cell can be timely repaired or replaced.

Description

Technical Field

[0001] The present application relates to the technical field of performance detection, and in particular, to a method and system for detecting the performance of a solar-driven hydrogen fuel cell. Background Art

[0002] A solar cell is a thin photovoltaic semiconductor sheet that directly generates electricity using sunlight, also known as a "solar chip" or "photovoltaic cell". As long as it is illuminated by light with a certain illuminance condition, it can instantaneously output voltage and generate current in the case of a circuit. It is called solar photovoltaic (abbreviated as PV) in physics, simply referred to as photovoltaic.

[0003] Currently, the performance detection of a solar-driven hydrogen fuel cell is a detection method to ensure the normal operation of the battery. The specific contents of the current battery detection are as follows: The capacity of the battery: It refers to the amount of electricity stored in the battery, usually measured in milliampere-hours (mAh) or ampere-hours (Ah). It reflects the total amount of electrical energy that the battery can release under certain conditions (such as discharge current, temperature, etc.). The larger the capacity of the battery, the longer the device can be used after a single charge. The energy density of the battery: Energy density refers to the energy that the battery can store per unit volume or weight, usually measured in watt-hours (Wh). A battery with a high energy density can provide a longer battery life under the same volume and weight. The cycle life of the battery: Cycle life refers to the number of times the battery can maintain its performance in a complete charge and discharge cycle. A battery with a high cycle life can provide stable power for a longer time. The charge and discharge rate of the battery: The charge and discharge rate (C-rate) represents the speed of battery charging and discharging. The higher the C-rate, the faster the charging or discharging speed. The internal resistance of the battery: The internal resistance is the degree of obstruction to current inside the battery. The smaller the internal resistance, the higher the discharge efficiency and output power of the battery. The voltage of the battery: The voltage of the battery includes the open-circuit voltage and the working voltage. The open-circuit voltage is the voltage of the battery when it is not connected to a load, and the working voltage is the voltage of the battery during discharge or charging. The self-discharge rate of the battery: The self-discharge rate refers to the magnitude of the natural discharge amount of the battery when it is not connected to a circuit. The lower the self-discharge rate, the stronger the battery's ability to maintain the stored electricity during storage. The safety of the battery: The safety of the battery includes the ability to prevent potential hazards such as overheating and short circuits. A battery with high safety is more reliable during use. The above-mentioned detection contents are very cumbersome and require a large amount of time cost and labor cost. As a result, the work efficiency may be very slow. Therefore, there is an urgent need for a method for detecting the performance of a solar-driven hydrogen fuel cell to overcome the above problems. Summary of the Invention

[0004] To improve the technical problems existing in the related art, the present application provides a method and system for detecting the performance of a solar-driven hydrogen fuel cell.

[0005] In a first aspect, a method for detecting the performance of a solar-powered hydrogen fuel cell is provided, including: extracting features from the data of the hydrogen fuel cell to be detected to obtain the performance data features of each extended hydrogen fuel cell, and extracting features from the performance data extension instruction of the hydrogen fuel cell to obtain the description features of the detection instruction; based on the performance data features of each extended hydrogen fuel cell, obtaining the performance data features of each target hydrogen fuel cell, and fusing the performance data features of each target hydrogen fuel cell and the description features of the detection instruction according to the association between each performance data feature of each target hydrogen fuel cell and the description features of the detection instruction to obtain the fused hydrogen fuel cell performance data features; respectively determining one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data extension operations in the data of the hydrogen fuel cell to be detected according to the fused hydrogen fuel cell performance data features, and obtaining the abnormal description range of the hydrogen fuel cell performance of each of the one or more performance description elements to be processed in the hydrogen fuel cell performance data to be processed with the same data volume as the data of the hydrogen fuel cell to be detected; respectively in one or more abnormal description ranges of the hydrogen fuel cell performance, abnormally describing the performance description elements of the target hydrogen fuel cell performance data obtained based on the hydrogen fuel cell performance data extension operation corresponding to the corresponding performance description element to be processed to obtain the target abnormally described hydrogen fuel cell performance data, and fusing the target abnormally described hydrogen fuel cell performance data and the data of the hydrogen fuel cell to be detected to obtain the hydrogen fuel cell performance detection result.

[0006] In the present application, before obtaining the fused hydrogen fuel cell performance data features, it further includes: extracting features from the performance data of the target reference hydrogen fuel cell to obtain the performance data features of each reference hydrogen fuel cell; It can be understood that extracting features before obtaining the fused hydrogen fuel cell performance data features can improve the accuracy of the performance data features of each reference hydrogen fuel cell.

[0007] Based on the performance data features of each extended hydrogen fuel cell, obtaining the performance data features of each target hydrogen fuel cell, and fusing the performance data features of each target hydrogen fuel cell and the description features of the detection instruction according to the association between each performance data feature of each target hydrogen fuel cell and the description features of the detection instruction to obtain the fused hydrogen fuel cell performance data features, including: obtaining the performance data features of each target hydrogen fuel cell according to the performance data features of each extended hydrogen fuel cell and the performance data features of each reference hydrogen fuel cell; fusing the performance data features of each target hydrogen fuel cell and the description features of the detection instruction according to the association between each performance data feature of each target hydrogen fuel cell and the description features of the detection instruction to obtain the fused hydrogen fuel cell performance data features.

[0008] It can be understood that when obtaining the performance data characteristics of each target hydrogen fuel cell and fusing the performance data characteristics of each target hydrogen fuel cell with the characteristics described in the detection instruction according to the association between each performance data characteristic of the target hydrogen fuel cell and the characteristics described in the detection instruction, the problem of inaccurate association is improved, so that the fused hydrogen fuel cell performance data characteristics can be obtained more accurately.

[0009] In this application, the target hydrogen fuel cell performance data with abnormal description, which is obtained by expanding the hydrogen fuel cell performance data based on the corresponding performance description elements to be processed in one or more abnormal description ranges of hydrogen fuel cell performance, includes: performing the following operations on the one or more abnormal description ranges of hydrogen fuel cell performance respectively to obtain the target hydrogen fuel cell performance data with abnormal description: for the hydrogen fuel cell performance data expansion operation that does not cover the indication of abnormal description information, taking the hydrogen fuel cell performance data performance description element obtained after performing the hydrogen fuel cell performance data expansion operation on one performance description element to be processed as the performance description element of the target hydrogen fuel cell performance data, and abnormally describing the performance description element of the target hydrogen fuel cell performance data in the abnormal description range of the hydrogen fuel cell performance of the one performance description element to be processed; for the hydrogen fuel cell performance data expansion operation that covers the indication of abnormal description information, obtaining the performance description element of the target hydrogen fuel cell performance data based on each same hydrogen fuel cell performance data performance description element associated with the indication of abnormal description information in the pre-configured hydrogen fuel cell performance data performance description element set, or extracting the performance description element of the target hydrogen fuel cell performance data associated with the indication of abnormal description information from the target reference hydrogen fuel cell performance data, and abnormally describing the performance description element of the target hydrogen fuel cell performance data in the abnormal description range of the hydrogen fuel cell performance of the one performance description element to be processed.

[0010] It can be understood that when abnormally describing the performance description element of the target hydrogen fuel cell performance data obtained by expanding the hydrogen fuel cell performance data based on the corresponding performance description element to be processed in one or more abnormal description ranges of hydrogen fuel cell performance, the problem of inaccurate performance description element of the target hydrogen fuel cell performance data is improved, so that the target hydrogen fuel cell performance data with abnormal description can be accurately obtained.

[0011] In this application, obtaining the target hydrogen fuel cell performance data performance description elements by aggregating the same hydrogen fuel cell performance data performance description elements associated with the indicated abnormal description information in the previously configured hydrogen fuel cell performance data performance description element set includes: obtaining the same hydrogen fuel cell performance data performance description elements associated with the performance description element type according to the performance description element type carried by the indicated abnormal description information in the previously configured hydrogen fuel cell performance data performance description element set; using any one of the same hydrogen fuel cell performance data performance description elements as the target hydrogen fuel cell performance data performance description element; or obtaining the target hydrogen fuel cell performance data performance description element by fusing multiple same hydrogen fuel cell performance data performance description elements.

[0012] It can be understood that when aggregating the same hydrogen fuel cell performance data performance description elements associated with the indicated abnormal description information in the previously configured hydrogen fuel cell performance data performance description element set, the problem of inaccurate same hydrogen fuel cell performance data performance description elements is improved, so that the target hydrogen fuel cell performance data performance description elements can be accurately obtained.

[0013] In this application, obtaining the hydrogen fuel cell performance abnormal description range of each of the one or more to-be-processed performance description elements in the to-be-processed hydrogen fuel cell performance data having the same data volume as the hydrogen fuel cell data to be detected includes: performing feature extraction on the to-be-processed hydrogen fuel cell performance data having the same data volume as the hydrogen fuel cell data to be detected to obtain the characteristics of each abnormal description hydrogen fuel cell performance data; obtaining the degree of association between each of the characteristics of the abnormal description hydrogen fuel cell performance data and the fused hydrogen fuel cell performance data characteristics, and based on the abnormal data description set corresponding to the characteristics of the abnormal description hydrogen fuel cell performance data with the degree of association greater than or equal to the set threshold, obtaining the hydrogen fuel cell performance abnormal description range of each of the one or more to-be-processed performance description elements.

[0014] It can be understood that when in the to-be-processed hydrogen fuel cell performance data having the same data volume as the hydrogen fuel cell data to be detected, the problem of inaccurate characteristics of each abnormal description hydrogen fuel cell performance data is improved, so that the hydrogen fuel cell performance abnormal description range of each of the one or more to-be-processed performance description elements can be obtained more accurately.

[0015] In this application, obtaining the hydrogen fuel cell performance anomaly description ranges of the one or more performance description elements to be processed based on the anomaly data description set corresponding to the anomaly description hydrogen fuel cell performance data features with an association degree greater than or equal to a set threshold includes: integrating the anomaly description hydrogen fuel cell performance data features with an association degree greater than or equal to the set threshold to obtain one or more anomaly description hydrogen fuel cell performance data feature sets; respectively performing the following operations on the one or more anomaly description hydrogen fuel cell performance data feature sets: obtaining the battery anomaly operation ranges corresponding to the respective anomaly description hydrogen fuel cell performance data features in an anomaly description hydrogen fuel cell performance data feature set, each battery anomaly operation range including one or more anomaly data description sets; based on the obtained battery anomaly operation ranges, determining the limiting conditions of the hydrogen fuel cell performance anomaly description range, and by connecting the limiting conditions, obtaining the hydrogen fuel cell performance anomaly description range of the corresponding performance description element to be processed in the hydrogen fuel cell performance data to be processed.

[0016] It can be understood that when based on the anomaly data description set corresponding to the anomaly description hydrogen fuel cell performance data features with an association degree greater than or equal to the set threshold, the problem of inaccurate battery anomaly operation ranges of each battery is improved, so that the hydrogen fuel cell performance anomaly description ranges of the one or more performance description elements to be processed can be accurately obtained.

[0017] In this application, fusing the target anomaly description hydrogen fuel cell performance data and the hydrogen fuel cell data to be detected to obtain a hydrogen fuel cell performance detection result includes: covering the target anomaly description hydrogen fuel cell performance data above the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result; or, extracting the remaining hydrogen fuel cell performance data performance description elements other than the one or more performance description elements to be processed from the hydrogen fuel cell data to be detected, and fusing the one or more remaining hydrogen fuel cell performance data performance description elements into the target anomaly description hydrogen fuel cell performance data to obtain the hydrogen fuel cell performance detection result; or, extracting one or more target hydrogen fuel cell performance data performance description elements from the target anomaly description hydrogen fuel cell performance data, and fusing the one or more target hydrogen fuel cell performance data performance description elements into the hydrogen fuel cell data to be detected from which the one or more performance description elements to be processed have been filtered to obtain the hydrogen fuel cell performance detection result.

[0018] It can be understood that when fusing the target abnormal description of the hydrogen fuel cell performance data and the hydrogen fuel cell data to be detected, the problem of inaccurate hydrogen fuel cell performance detection results is improved, so that the hydrogen fuel cell performance detection results can be obtained more accurately.

[0019] In this application, the following method is adopted to obtain the hydrogen fuel cell data to be detected: obtaining the original extended hydrogen fuel cell performance data input by the target detection item, and using the original extended hydrogen fuel cell performance data as the hydrogen fuel cell data to be detected; or, in response to the hydrogen fuel cell performance data extraction instruction, performing hydrogen fuel cell performance data extraction on the original extended hydrogen fuel cell performance data input by the target detection item to obtain the hydrogen fuel cell data to be detected.

[0020] In this application, the performance detection method of the solar-driven hydrogen fuel cell is implemented through a hydrogen fuel cell performance data extension model. By performing the following operations, the hydrogen fuel cell performance data extension model is trained: adopting a cyclic iteration method, based on each training hydrogen fuel cell performance data example of the standard extended performance, training the untrained hydrogen fuel cell performance data extension model until the iterative training terminates, and obtaining the hydrogen fuel cell performance data extension model that has completed the first training; adopting a cyclic iteration method, based on each training hydrogen fuel cell performance data example of the directory retention performance, training the hydrogen fuel cell performance data extension model that has completed the first training until the iterative training terminates, and obtaining the hydrogen fuel cell performance data extension model that has completed the second training and is output.

[0021] In this application, the method of adopting a cyclic iteration method, based on each training hydrogen fuel cell performance data example of the standard extended performance, training the untrained hydrogen fuel cell performance data extension model until the iterative training terminates, and obtaining the hydrogen fuel cell performance data extension model that has completed the first training includes: where each iteration includes: based on one or more extension instruction examples, performing a standard extension operation on the corresponding training hydrogen fuel cell performance data example to obtain their respective extended hydrogen fuel cell performance data examples; obtaining the respective set extended hydrogen fuel cell performance data of the corresponding training hydrogen fuel cell performance data examples, and based on one or more extended hydrogen fuel cell performance data examples and the corresponding set extended hydrogen fuel cell performance data, obtaining the hydrogen fuel cell performance data extension loss result generated in this iteration, and debugging each performance unit in the model in turn according to the hydrogen fuel cell performance data extension loss result.

[0022] It can be understood that, based on the performance data examples of each training hydrogen fuel cell for standard extension performance, the untrained hydrogen fuel cell performance data extension model is trained until the iterative training terminates, and the hydrogen fuel cell performance data extension model that has completed the first training is obtained.

[0023] In the present application, the method of using an iterative loop, based on the performance data examples of each training hydrogen fuel cell for directory retention performance, trains the hydrogen fuel cell performance data extension model that has completed the first training until the iterative training terminates, and obtains the hydrogen fuel cell performance data extension model that has completed the secondary training, including: where each iteration includes: performing a directory retention operation on the corresponding training hydrogen fuel cell performance data example based on one or more retention instruction examples to obtain their respective retained hydrogen fuel cell performance data examples; obtaining the respective set retained hydrogen fuel cell performance data of the corresponding training hydrogen fuel cell performance data examples, obtaining the directory retention loss result generated in this iteration based on one or more retained hydrogen fuel cell performance data examples and the corresponding set retained hydrogen fuel cell performance data, and debugging each performance unit in the model in sequence according to the directory retention loss result.

[0024] It can be understood that the model can be optimized to improve the processing ability of the model.

[0025] In a second aspect, a performance detection system for a solar-driven hydrogen fuel cell is provided, including a processor and a memory that communicate with each other, and the processor is configured to read and execute a computer program from the memory to implement the above method.

[0026] A performance detection method and system for a solar-driven hydrogen fuel cell provided by an embodiment of the present application, based on the performance data characteristics of each extended hydrogen fuel cell of the hydrogen fuel cell data to be detected, obtains the performance data characteristics of each target hydrogen fuel cell, and loads the detection instruction description characteristics into the performance data characteristics of each target hydrogen fuel cell of the hydrogen fuel cell data to be detected to obtain the fused hydrogen fuel cell performance data characteristics; then, respectively based on the fused hydrogen fuel cell performance data characteristics, one or more performance description elements to be processed and their respective corresponding hydrogen fuel cell performance data extension operations are determined in the hydrogen fuel cell data to be detected, and the hydrogen fuel cell performance anomaly description ranges of one or more performance description elements to be processed are obtained in the hydrogen fuel cell performance data to be processed that has the same data volume as the hydrogen fuel cell data to be detected.

[0027] The extended operation of hydrogen fuel cell performance data that combines catalog retention performance binds the performance description element catalog of the hydrogen fuel cell performance data performance description elements to the extended operation of the hydrogen fuel cell performance data. That is, it covers multiple performance description elements of the same type of hydrogen fuel cell performance data. It can also determine which hydrogen fuel cell performance data performance description elements are the performance description elements to be processed and which are the remaining hydrogen fuel cell performance data performance description elements that do not require the extended operation of the hydrogen fuel cell performance data based on the performance description element catalog of the hydrogen fuel cell performance data performance description elements, reducing the interference of performance detection and reducing the error rate of performance description elements.

[0028] Finally, in one or more abnormal description ranges of hydrogen fuel cell performance, the target hydrogen fuel cell performance data performance description elements obtained from the extended operation of the hydrogen fuel cell performance data based on the corresponding performance description elements to be processed are abnormally described to obtain the target abnormally described hydrogen fuel cell performance data. Then, the target abnormally described hydrogen fuel cell performance data is fused with the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result. By using the performance detection method of the solar-driven hydrogen fuel cell provided by the embodiments of the present disclosure, for the hydrogen fuel cell data to be detected that covers multiple identical hydrogen fuel cell performance data performance description elements, it is also possible to accurately determine the same hydrogen fuel cell performance data performance description elements, improve the performance detection result, so as to be able to accurately obtain the performance information of the hydrogen fuel cell and be able to repair or replace the hydrogen fuel cell in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present application, so they should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0030] Figure 1 It is a flowchart of a performance detection method for a solar-driven hydrogen fuel cell provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] To better understand the above technical solutions, the following will make a detailed description of the technical solutions of the present application through the drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solutions of the present application, rather than limitations on the technical solutions of the present application. Without conflict, the technical features in the embodiments of the present application and the embodiments can be combined with each other.

[0032] Please refer to Figure 1, which shows a performance detection method for a solar-driven hydrogen fuel cell. This method may include the technical solutions described in the following steps S301 - S304.

[0033] S301: Extract features from the hydrogen fuel cell data to be detected to obtain the performance data features of each extended hydrogen fuel cell, and extract features from the hydrogen fuel cell performance data expansion instruction to obtain the detection instruction description features.

[0034] For example, the hydrogen fuel cell performance data can be obtained through a monitoring device.

[0035] For example, the hydrogen fuel cell performance data expansion instruction can be understood as an instruction mined from the hydrogen fuel cell performance data.

[0036] Among them, the specific content of feature extraction includes: the operating conditions of the battery, the charge and discharge conditions of the battery, and the life cycle of the battery, etc.

[0037] The present disclosure supports the following two ways to obtain the hydrogen fuel cell data to be detected, where: Way 1: Obtain the original extended hydrogen fuel cell performance data input by the target detection item, and use the original extended hydrogen fuel cell performance data as the hydrogen fuel cell data to be detected; For example, the original extended hydrogen fuel cell performance data can be understood as in-situ information.

[0038] Way 2: In response to the hydrogen fuel cell performance data extraction instruction, perform hydrogen fuel cell performance data extraction on the original extended hydrogen fuel cell performance data input by the target detection item to obtain the hydrogen fuel cell data to be detected.

[0039] In the second way of obtaining the hydrogen fuel cell data to be detected, through the hydrogen fuel cell performance data compression model of the model, extract features from the original extended hydrogen fuel cell performance data, and then input each original hydrogen fuel cell performance data feature and the hydrogen fuel cell performance data extraction instruction into the hydrogen fuel cell performance data extraction unit, compare the detection instruction description features of each original hydrogen fuel cell performance data feature and the hydrogen fuel cell performance data extraction instruction, and obtain the hydrogen fuel cell performance data content corresponding to the original hydrogen fuel cell performance data feature with a relatively high degree of association with the detection instruction description feature, so as to obtain the hydrogen fuel cell data to be detected.

[0040] Through the instruction recognition unit of the model, feature extraction is performed on the hydrogen fuel cell data to be detected, and the performance data features of each extended hydrogen fuel cell are obtained, converting the hydrogen fuel cell performance data in the form of displacement data into data that the model can recognize; and, through the instruction recognition unit of the model, feature extraction is performed on the extended instruction of the hydrogen fuel cell performance data to obtain the description features of the detection instruction, converting the extended instruction of the hydrogen fuel cell performance data in the form of a string into data that the model can recognize.

[0041] S302: Based on the performance data features of each extended hydrogen fuel cell, the performance data features of each target hydrogen fuel cell are obtained. Based on the association between each target hydrogen fuel cell performance data feature and the detection instruction description feature, the performance data feature of each target hydrogen fuel cell and the detection instruction description feature are fused to obtain the fused hydrogen fuel cell performance data feature.

[0042] For example, the detection instruction description feature can be understood as the content of the instruction that needs to be inspected, including location information, etc., such as: at the xx position of the battery, etc.

[0043] Take the performance data features of each extended hydrogen fuel cell as the corresponding performance data features of the target hydrogen fuel cell. Based on the association between each target hydrogen fuel cell performance data feature and the detection instruction description feature, the detection instruction description feature is loaded into each target hydrogen fuel cell performance data feature of the hydrogen fuel cell data to be detected to obtain the fused hydrogen fuel cell performance data feature.

[0044] In a possible embodiment, the process of fusing the performance data features of each target hydrogen fuel cell and the detection instruction description feature is as follows: S3021: Multiply each target hydrogen fuel cell performance data feature by the function transformation matrix AB to obtain the search vector matrix B, multiply each target hydrogen fuel cell performance data feature by the function transformation matrix AC to obtain the value vector matrix C, and multiply the detection instruction description feature by the function transformation matrix AD to obtain the key vector matrix D.

[0045] S3022: Multiply the search vector matrix by the key vector matrix to obtain the importance ratio of the detection instruction description feature to each target hydrogen fuel cell performance data feature.

[0046] S3023: Multiply the value vector matrix by the importance ratio matrix to obtain the fused hydrogen fuel cell performance data feature.

[0047] S303: Based on the characteristics of the fused hydrogen fuel cell performance data respectively, determine one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data expansion operations in the hydrogen fuel cell data to be detected. In the hydrogen fuel cell performance data to be processed with the same data volume as the hydrogen fuel cell data to be detected, obtain the hydrogen fuel cell performance abnormal description ranges of one or more performance description elements to be processed respectively; the hydrogen fuel cell performance data expansion operation is an operation that combines the performance of maintaining the directory.

[0048] For example, the expansion operation can be understood as magnifying the data to obtain more and more detailed relevant data.

[0049] To further improve the effect of expanding the hydrogen fuel cell performance data, a difference recognition unit is added to the model to recognize the differences in the characteristics of the fused hydrogen fuel cell performance data located in the first three-dimensional space, and obtain the characteristics of the fused hydrogen fuel cell performance data located in the second three-dimensional space. The spatial dimension of the transformed fused hydrogen fuel cell performance data characteristics is more compatible with the hydrogen fuel cell performance data expansion unit; among them, the spatial dimension of the first three-dimensional space is lower than that of the second three-dimensional space.

[0050] Among them, the three-dimensional space can be understood as a three-dimensional coordinate system.

[0051] The hydrogen fuel cell performance data expansion unit adopts the idea of the attention mechanism to obtain the degree of association between each expanded hydrogen fuel cell performance data characteristic of the hydrogen fuel cell data to be detected and the fused hydrogen fuel cell performance data characteristic. Based on the expanded hydrogen fuel cell performance data characteristics with a higher degree of association, determine one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data expansion operations in the hydrogen fuel cell data to be detected. And obtain the degree of association between each abnormal description hydrogen fuel cell performance data characteristic of the hydrogen fuel cell performance data to be processed and the fused hydrogen fuel cell performance data characteristic. Based on the abnormal description hydrogen fuel cell performance data characteristics with a higher degree of association, obtain the hydrogen fuel cell performance abnormal description ranges of one or more performance description elements to be processed respectively in the hydrogen fuel cell performance data to be processed with the same data volume as the hydrogen fuel cell data to be detected. The implementation method of obtaining the degree of association between features.

[0052] In some possible embodiments, the specific process of obtaining the hydrogen fuel cell performance abnormal description ranges of one or more performance description elements to be processed respectively is as follows: S3031: Extract features from the hydrogen fuel cell performance data to be processed with the same data volume as the hydrogen fuel cell data to be detected, and obtain the corresponding abnormal description hydrogen fuel cell performance data characteristics respectively; S3032: Obtain the degree of association between each abnormal description of the hydrogen fuel cell performance data characteristics and the fused hydrogen fuel cell performance data characteristics. Based on the set of abnormal data descriptions corresponding to the abnormal description of the hydrogen fuel cell performance data characteristics whose degree of association is greater than or equal to the set threshold, obtain the hydrogen fuel cell performance abnormal description range for each of one or more performance description elements to be processed.

[0053] For example, it can be understood as a displacement interval. First, integrate the abnormal description of the hydrogen fuel cell performance data characteristics whose degree of association is greater than or equal to the set threshold to obtain one or more sets of abnormal description of the hydrogen fuel cell performance data characteristics. Second, for one or more sets of abnormal description of the hydrogen fuel cell performance data characteristics, perform the following operations respectively: obtain the abnormal operation range of the battery corresponding to each abnormal description of the hydrogen fuel cell performance data characteristics in an abnormal description set of the hydrogen fuel cell performance data characteristics, and each abnormal operation range of the battery includes one or more sets of abnormal data descriptions; based on the obtained abnormal operation ranges of the batteries, determine the limiting conditions of the hydrogen fuel cell performance abnormal description range, and generate the hydrogen fuel cell performance abnormal description range of a performance description element to be processed by connecting the limiting conditions.

[0054] In the embodiment of the present disclosure, the hydrogen fuel cell performance data to be processed is an interfering hydrogen fuel cell performance data.

[0055] S304: Respectively in one or more hydrogen fuel cell performance abnormal description ranges, abnormally describe the performance description elements of the target hydrogen fuel cell performance data obtained by expanding the hydrogen fuel cell performance data based on the corresponding performance description elements to be processed, obtain the target abnormal description of the hydrogen fuel cell performance data, and fuse the target abnormal description of the hydrogen fuel cell performance data with the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result.

[0056] For example, the performance description elements of the target hydrogen fuel cell performance data can be understood as the elements affecting the stability of the slope of the landslide, such as: the looseness of the soil, the water content of the soil, and human factors, etc.

[0057] For example, the hydrogen fuel cell performance detection result can be understood as the battery operation performance information obtained through mining.

[0058] In the related art, since the hydrogen fuel cell data to be detected is not input into the hydrogen fuel cell performance data extension layer, the hydrogen fuel cell performance data extension layer does not directly extend the hydrogen fuel cell data to be detected, nor does it extend based on the hydrogen fuel cell data to be detected. Instead, it outputs one-dimensional text features and regenerates a brand-new hydrogen fuel cell performance detection result. As a result, it is difficult to maintain the consistency of the local structure and local texture between the remaining hydrogen fuel cell performance data performance description elements that are not extended in the hydrogen fuel cell performance detection result and the remaining hydrogen fuel cell performance data performance description elements that are not extended in the hydrogen fuel cell data to be detected.

[0059] To solve this problem, the present disclosure inputs the hydrogen fuel cell data to be detected, the hydrogen fuel cell performance data to be processed full of interference, and the fused hydrogen fuel cell performance data features into the hydrogen fuel cell performance data extension unit. In the hydrogen fuel cell performance data to be processed, the target hydrogen fuel cell performance data performance description elements obtained by the hydrogen fuel cell performance data extension operation for the abnormal description based on the corresponding performance description elements to be processed are obtained, and the target abnormal description hydrogen fuel cell performance data is obtained. Then, by fusing the target abnormal description hydrogen fuel cell performance data with the hydrogen fuel cell data to be detected, the hydrogen fuel cell performance detection result is obtained. Therefore, the remaining hydrogen fuel cell performance data performance description elements that are not extended in the hydrogen fuel cell performance detection result are derived from the hydrogen fuel cell data to be detected, so that the hydrogen fuel cell performance data before and after extension is consistent in terms of the local structure and local texture of the hydrogen fuel cell performance data.

[0060] The following operations are respectively performed on one or more hydrogen fuel cell performance abnormal description ranges to obtain the target abnormal description hydrogen fuel cell performance data: Regarding the hydrogen fuel cell performance data extension operation that does not cover the indication of abnormal description information, it is stated that the performance description element to be processed itself is directly extended. Then, based on the hydrogen fuel cell performance data extension operation, the hydrogen fuel cell performance data performance description element obtained after performing the hydrogen fuel cell performance data extension operation on a performance description element to be processed is used as the target hydrogen fuel cell performance data performance description element, and in the hydrogen fuel cell performance abnormal description range of a performance description element to be processed, the target hydrogen fuel cell performance data performance description element is abnormally described.

[0061] The indication of abnormal description information is used to represent the target hydrogen fuel cell performance data performance description element for modifying the performance description element to be processed into other content.

[0062] For the extended operation of hydrogen fuel cell performance data covering the indication of abnormal description information, based on each same hydrogen fuel cell performance data performance description element associated with the indication of abnormal description information in the previously configured hydrogen fuel cell performance data performance description element set, the target hydrogen fuel cell performance data performance description element is obtained, and within the abnormal description range of the hydrogen fuel cell performance of a performance description element to be processed, the target hydrogen fuel cell performance data performance description element is abnormally described.

[0063] Among them, the process of obtaining the corresponding target hydrogen fuel cell performance data performance description element based on the same hydrogen fuel cell performance data performance description element set is as follows: based on the performance description element type carried by the indication of abnormal description information, obtain the same hydrogen fuel cell performance data performance description element associated with the performance description element type in the previously configured hydrogen fuel cell performance data performance description element set; then use any one of the same hydrogen fuel cell performance data performance description elements as the target hydrogen fuel cell performance data performance description element; or obtain the target hydrogen fuel cell performance data performance description element by fusing multiple same hydrogen fuel cell performance data performance description elements.

[0064] In the embodiments of the present disclosure, the following three hydrogen fuel cell performance data fusion methods are provided: Method 1: Cover the target abnormally described hydrogen fuel cell performance data above the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result.

[0065] Method 2: Load the remaining hydrogen fuel cell performance data performance description elements in the hydrogen fuel cell data to be detected that have not been extended into the target abnormally described hydrogen fuel cell performance data.

[0066] Extract the remaining hydrogen fuel cell performance data performance description elements in the hydrogen fuel cell data to be detected except for one or more performance description elements to be processed, and fuse one or more remaining hydrogen fuel cell performance data performance description elements into the target abnormally described hydrogen fuel cell performance data to obtain the hydrogen fuel cell performance detection result.

[0067] Method 3: Load the target hydrogen fuel cell performance data performance description elements in the target abnormally described hydrogen fuel cell performance data into the hydrogen fuel cell data to be detected.

[0068] Extract one or more target hydrogen fuel cell performance data performance description elements in the target abnormally described hydrogen fuel cell performance data, and fuse one or more target hydrogen fuel cell performance data performance description elements into the hydrogen fuel cell data to be detected that has been filtered of one or more performance description elements to be processed to obtain the hydrogen fuel cell performance detection result.

[0069] In addition, the present disclosure can also perform hydrogen fuel cell performance data expansion on the corresponding performance description elements to be processed based on the target reference hydrogen fuel cell performance data, and obtain the performance description elements of the expanded target hydrogen fuel cell performance data. The process of modifying the hydrogen fuel cell data to be detected into the performance description elements of the target hydrogen fuel cell performance data in the target reference hydrogen fuel cell performance data is as follows: S401: Extract features from the hydrogen fuel cell data to be detected to obtain the features of each expanded hydrogen fuel cell performance data, extract features from the hydrogen fuel cell performance data expansion instruction to obtain the detection instruction description features, and extract features from the target reference hydrogen fuel cell performance data to obtain the features of each reference hydrogen fuel cell performance data.

[0070] The present disclosure supports the following two methods for obtaining the hydrogen fuel cell data to be detected, where: Method 1: Obtain the original expanded hydrogen fuel cell performance data input by the target detection item, and use the original expanded hydrogen fuel cell performance data as the hydrogen fuel cell data to be detected; Method 2: In response to the hydrogen fuel cell performance data extraction instruction, perform hydrogen fuel cell performance data extraction on the original expanded hydrogen fuel cell performance data input by the target detection item to obtain the hydrogen fuel cell data to be detected.

[0071] The present disclosure also supports the following two methods for obtaining the target reference hydrogen fuel cell performance data, where: Method 1: Obtain the original reference hydrogen fuel cell performance data input by the target detection item, and use the original reference hydrogen fuel cell performance data as the target reference hydrogen fuel cell performance data; Method 2: In response to the hydrogen fuel cell performance data extraction instruction, perform hydrogen fuel cell performance data extraction on the original reference hydrogen fuel cell performance data input by the target detection item to obtain the target reference hydrogen fuel cell performance data.

[0072] To achieve the performance of hydrogen fuel cell performance data extraction, two hydrogen fuel cell performance data compression units and two hydrogen fuel cell performance data extraction units are added to the model. Among them, the hydrogen fuel cell performance data compression unit 1 and the hydrogen fuel cell performance data extraction unit 1 are used to perform hydrogen fuel cell performance data extraction on the original expanded hydrogen fuel cell performance data input by the target detection item to obtain the hydrogen fuel cell data to be detected; the hydrogen fuel cell performance data compression unit 2 and the hydrogen fuel cell performance data extraction unit 2 are used to perform hydrogen fuel cell performance data extraction on another original reference hydrogen fuel cell performance data input by the target detection item to obtain the target reference hydrogen fuel cell performance data.

[0073] After that, through the instruction recognition unit of the model, feature extraction is performed on the hydrogen fuel cell data to be detected to obtain the features of each extended hydrogen fuel cell performance data, and feature extraction is performed on the reference hydrogen fuel cell performance data to obtain the features of each reference hydrogen fuel cell performance data, and the hydrogen fuel cell performance data in the form of displacement data is converted into data that the model can recognize; and, through the instruction recognition unit of the model, feature extraction is performed on the hydrogen fuel cell performance data extension instruction to obtain the detection instruction description features, and the hydrogen fuel cell performance data extension instruction existing in the form of text or string is converted into data that the model can recognize.

[0074] S402: Based on the features of each extended hydrogen fuel cell performance data and the features of each reference hydrogen fuel cell performance data, obtain the features of each target hydrogen fuel cell performance data, and according to the association between each of the features of the target hydrogen fuel cell performance data and the detection instruction description features, fuse the features of the target hydrogen fuel cell performance data and the detection instruction description features to obtain the fused hydrogen fuel cell performance data features.

[0075] Take the features of each extended hydrogen fuel cell performance data and the features of each reference hydrogen fuel cell performance data as the corresponding features of the target hydrogen fuel cell performance data. The instruction recognition unit adopting the idea of the attention mechanism, based on the association between each of the features of the target hydrogen fuel cell performance data and the detection instruction description features, loads the detection instruction description features into the features of each target hydrogen fuel cell performance data of the hydrogen fuel cell data to be detected and the target reference hydrogen fuel cell performance data to obtain the fused hydrogen fuel cell performance data features.

[0076] The fused hydrogen fuel cell performance data features can assist the hydrogen fuel cell performance data extension unit in determining one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data extension operations in the hydrogen fuel cell data to be detected, obtaining the abnormal description ranges of the hydrogen fuel cell performance of each of the one or more performance description elements to be processed in the hydrogen fuel cell performance data to be processed, and extracting the performance description elements of the target hydrogen fuel cell performance data associated with the abnormal description information indication in the target reference hydrogen fuel cell performance data.

[0077] S403: Based on the fused hydrogen fuel cell performance data features respectively, determine one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data extension operations in the hydrogen fuel cell data to be detected, and obtain the abnormal description ranges of the hydrogen fuel cell performance of each of the one or more performance description elements to be processed in the hydrogen fuel cell performance data to be processed that has the same data volume as the hydrogen fuel cell data to be detected; the hydrogen fuel cell performance data extension operation is an operation that combines the directory retention performance.

[0078] To further improve the effect of expanding the performance data of hydrogen fuel cells, a difference recognition unit is added to the model to recognize the differences in the fused hydrogen fuel cell performance data features located in the first three-dimensional space, obtaining the fused hydrogen fuel cell performance data features located in the second three-dimensional space. The spatial dimension of the transformed fused hydrogen fuel cell performance data features is more compatible with the hydrogen fuel cell performance data expansion unit; among them, the spatial dimension of the first three-dimensional space is lower than that of the second three-dimensional space.

[0079] Based on the fused hydrogen fuel cell performance data features, determine one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data expansion operations in the hydrogen fuel cell data to be detected, and determine the hydrogen fuel cell performance abnormal description ranges of each of the one or more performance description elements to be processed in the hydrogen fuel cell performance data to be processed. The specific implementation method can refer to the relevant content in step 303 and will not be elaborated here.

[0080] S404: In one or more hydrogen fuel cell performance abnormal description ranges respectively, abnormally describe the performance description elements of the target hydrogen fuel cell performance data obtained based on the hydrogen fuel cell performance data expansion operation corresponding to the corresponding performance description element to be processed, obtain the target abnormally described hydrogen fuel cell performance data, and fuse the target abnormally described hydrogen fuel cell performance data with the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result.

[0081] For the hydrogen fuel cell performance data expansion operation covering the indication of abnormal description information, extract the performance description elements of the target hydrogen fuel cell performance data associated with the indication of abnormal description information from the target reference hydrogen fuel cell performance data, and abnormally describe the performance description elements of the target hydrogen fuel cell performance data in one or more hydrogen fuel cell performance abnormal description ranges respectively to obtain the target abnormally described hydrogen fuel cell performance data.

[0082] In the embodiments of the present disclosure, the following three hydrogen fuel cell performance data fusion methods are provided: Method 1: Cover the target abnormally described hydrogen fuel cell performance data above the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result; Method 2: Load the remaining performance description elements of the hydrogen fuel cell performance data in the hydrogen fuel cell data to be detected that have not been expanded into the target abnormally described hydrogen fuel cell performance data; Method 3: Load the performance description elements of the target hydrogen fuel cell performance data in the target abnormally described hydrogen fuel cell performance data into the hydrogen fuel cell data to be detected.

[0083] Compared with the related art, the performance detection method of the solar-driven hydrogen fuel cell provided by the present disclosure can achieve a higher-precision local expansion, especially when performing local expansion operations on hydrogen fuel cell data that needs to detect the performance description elements covering the performance data of multiple identical hydrogen fuel cells, the model performance is better than the hydrogen fuel cell performance data expansion model disclosed under the related art.

[0084] In addition, it should be noted that in the specific embodiments of the present disclosure, there are detection item data related to obtaining original expanded hydrogen fuel cell performance data, obtaining original reference hydrogen fuel cell performance data, etc. When the above embodiments of the present disclosure are applied to specific products or technologies, permission or consent for detection items needs to be obtained, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions.

[0085] S201: Adopt a cyclic iteration method to train the untrained hydrogen fuel cell performance data expansion model based on each training hydrogen fuel cell performance data example of the original expansion performance until the iterative training terminates, and obtain the hydrogen fuel cell performance data expansion model that has completed the first training.

[0086] For example, Before the formal training, the set expanded hydrogen fuel cell performance data for each training example needs to be generated in advance.

[0087] Among them, each iteration includes: performing a standard expansion operation on the corresponding training hydrogen fuel cell performance data example based on one or more expansion instruction examples to obtain their respective expanded hydrogen fuel cell performance data examples; obtaining the set expanded hydrogen fuel cell performance data for each corresponding training hydrogen fuel cell performance data example, obtaining the hydrogen fuel cell performance data expansion loss result generated in this iteration based on one or more expanded hydrogen fuel cell performance data examples and the corresponding set expanded hydrogen fuel cell performance data, and debugging each performance unit in the model in turn based on the hydrogen fuel cell performance data expansion loss result.

[0088] To solve this problem, the present disclosure adopts a joint optimization method. First, based on the hydrogen fuel cell performance data expansion loss results generated in this iteration, the hydrogen fuel cell performance data expansion unit is debugged; then, the hydrogen fuel cell performance data monitoring signal generated in the hydrogen fuel cell performance data expansion unit and the hydrogen fuel cell performance data expansion loss results are fed back to the difference identification unit together to debug the difference identification unit; then, the hydrogen fuel cell performance monitoring signal, the hydrogen fuel cell performance data expansion loss results, and the corresponding monitoring signals generated by the difference identification unit are fed back to the instruction identification unit together to debug the instruction identification unit, and so on, until the debugging of the hydrogen fuel cell performance data extraction unit and the hydrogen fuel cell performance data compression unit is completed.

[0089] The iteration termination requirements include: (1) The difference between the hydrogen fuel cell performance data expansion loss results generated in this iteration and the hydrogen fuel cell performance data expansion loss results generated in the previous iteration does not exceed the threshold; (2) The hydrogen fuel cell performance data expansion loss results generated in this iteration do not exceed the threshold; (3) The number of iterations in this iteration has reached the set number threshold.

[0090] When any of the above iteration termination requirements is met, it indicates that after multiple iterations, the internal parameters of the model have reached a stable range. Therefore, the model after parameter adjustment that meets the iteration termination requirements is used as the hydrogen fuel cell performance data expansion model that has been trained for the first time; if none of the iteration termination requirements are met, the configured hydrogen fuel cell performance data examples of the next batch are read to continue configuring the model.

[0091] S202: Adopt a cyclic iteration method to train the hydrogen fuel cell performance data expansion model that has been trained for the first time based on each training hydrogen fuel cell performance data example that maintains performance in the directory until the iterative training terminates, and obtain the output hydrogen fuel cell performance data expansion model that has been trained for the second time.

[0092] Among them, each iteration includes: performing a directory maintenance operation on the corresponding training hydrogen fuel cell performance data example based on one or more maintenance instruction examples to obtain their respective maintained hydrogen fuel cell performance data examples; obtaining the respective set maintained hydrogen fuel cell performance data of the corresponding training hydrogen fuel cell performance data examples, obtaining the directory maintenance loss results generated in this iteration based on one or more maintained hydrogen fuel cell performance data examples and the corresponding set maintained hydrogen fuel cell performance data, and debugging each performance unit in the model in sequence based on the directory maintenance loss results.

[0093] The iteration termination requirements and the method of joint optimization parameter adjustment are the same as the steps of configuring the model based on each training hydrogen fuel cell performance data example with standard expansion performance, and will not be elaborated here.

[0094] On this basis, a performance detection device for a solar-driven hydrogen fuel cell is provided. The device includes: A feature acquisition module, configured to extract features from the hydrogen fuel cell data to be detected, obtain the performance data features of each extended hydrogen fuel cell, and extract features from the hydrogen fuel cell performance data extension instruction to obtain the detection instruction description features; A feature fusion module, configured to obtain the performance data features of each target hydrogen fuel cell based on the performance data features of each extended hydrogen fuel cell, and fuse the performance data features of each target hydrogen fuel cell and the detection instruction description features according to the association between the performance data features of each target hydrogen fuel cell and the detection instruction description features, to obtain the fused hydrogen fuel cell performance data features; A description range acquisition module, configured to respectively determine one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data extension operations in the hydrogen fuel cell data to be detected according to the fused hydrogen fuel cell performance data features, and obtain the hydrogen fuel cell performance abnormal description ranges of the one or more performance description elements to be processed in the hydrogen fuel cell performance data to be processed with the same data volume as the hydrogen fuel cell data to be detected; A result detection and determination module, configured to respectively in one or more hydrogen fuel cell performance abnormal description ranges, abnormally describe the performance description elements of the target hydrogen fuel cell performance data obtained by the hydrogen fuel cell performance data extension operation based on the corresponding performance description elements to be processed, to obtain the target abnormal description hydrogen fuel cell performance data, and fuse the target abnormal description hydrogen fuel cell performance data and the hydrogen fuel cell data to be detected, to obtain the hydrogen fuel cell performance detection result.

[0095] On this basis, a performance detection system for a solar-driven hydrogen fuel cell is shown, including a processor and a memory that communicate with each other. The processor is configured to read and execute a computer program from the memory to implement the above method.

[0096] On this basis, a computer-readable storage medium is further provided, on which a computer program is stored, and when the computer program runs, it implements the above method.

[0097] In summary, based on the above solution, according to the characteristics of each extended hydrogen fuel cell performance data of the hydrogen fuel cell data to be detected, the characteristics of each target hydrogen fuel cell performance data are obtained, and the detection instruction description characteristics are loaded into the characteristics of each target hydrogen fuel cell performance data of the hydrogen fuel cell data to be detected to obtain the fused hydrogen fuel cell performance data characteristics; then, respectively based on the fused hydrogen fuel cell performance data characteristics, one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data extension operations are determined in the hydrogen fuel cell data to be detected, and in the hydrogen fuel cell performance data to be processed with the same data volume as the hydrogen fuel cell data to be detected, the abnormal description ranges of the hydrogen fuel cell performance of one or more performance description elements to be processed are obtained.

[0098] The hydrogen fuel cell performance data extension operation combined with the directory retention performance binds the performance description element directory of the hydrogen fuel cell performance data performance description element to the hydrogen fuel cell performance data extension operation, that is, it covers multiple hydrogen fuel cell performance data performance description elements of the same type, and can also determine which hydrogen fuel cell performance data performance description elements are the performance description elements to be processed and which are the remaining hydrogen fuel cell performance data performance description elements that do not need to perform the hydrogen fuel cell performance data extension operation based on the performance description element directory of the hydrogen fuel cell performance data performance description element, reducing the interference of performance detection and reducing the error rate of performance description elements.

[0099] Finally, in one or more abnormal description ranges of the hydrogen fuel cell performance, the target hydrogen fuel cell performance data performance description elements obtained by the hydrogen fuel cell performance data extension operation based on the corresponding performance description elements to be processed are abnormally described to obtain the target abnormally described hydrogen fuel cell performance data, and the target abnormally described hydrogen fuel cell performance data is fused with the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result. Using the performance detection method of the solar-driven hydrogen fuel cell provided by the embodiments of the present disclosure, for the hydrogen fuel cell data to be detected covering multiple identical hydrogen fuel cell performance data performance description elements, it is also possible to accurately determine the same hydrogen fuel cell performance data performance description elements, improve the hydrogen fuel cell performance detection result, so as to accurately obtain the performance information of the hydrogen fuel cell and be able to repair or replace the hydrogen fuel cell in time.

[0100] It should be understood that the systems and their modules shown above can be implemented in various ways. For example, in some embodiments, the systems and their modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art can understand that the above methods and systems can be implemented using computer-executable instructions and / or included in processor control code, for example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and their modules of the present application can be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software implemented by various types of processors, or by a combination of the above hardware circuits and software (for example, firmware).

[0101] It should be noted that the beneficial effects that may be produced by different embodiments are different. In different embodiments, the beneficial effects that may be produced can be any one or several combinations of the above, or any other beneficial effects that may be obtained.

Claims

1. A performance detection method for a solar-driven hydrogen fuel cell, characterized in that, The method includes: extracting features from the hydrogen fuel cell data to be detected to obtain the characteristics of each extended hydrogen fuel cell performance data, and extracting features from the hydrogen fuel cell performance data extension instruction to obtain the detection instruction description features; obtaining the characteristics of each target hydrogen fuel cell performance data based on the characteristics of each extended hydrogen fuel cell performance data, and fusing the characteristics of each target hydrogen fuel cell performance data and the detection instruction description features according to the association between each target hydrogen fuel cell performance data characteristic and the detection instruction description feature to obtain the fused hydrogen fuel cell performance data characteristics; respectively determining one or more performance description elements to be processed and their corresponding hydrogen fuel cell performance data extension operations in the hydrogen fuel cell data to be detected, and obtaining the abnormal description ranges of the hydrogen fuel cell performance of each of the one or more performance description elements to be processed in the hydrogen fuel cell performance data to be processed having the same data volume as the hydrogen fuel cell data to be detected; respectively in one or more abnormal description ranges of the hydrogen fuel cell performance, abnormally describing the performance description elements of the target hydrogen fuel cell performance data obtained by the hydrogen fuel cell performance data extension operation based on the corresponding performance description element to be processed, obtaining the target abnormally described hydrogen fuel cell performance data, and fusing the target abnormally described hydrogen fuel cell performance data and the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result.

2. The method according to claim 1, wherein Before obtaining the fused hydrogen fuel cell performance data characteristics, it further includes: extracting features from the target reference hydrogen fuel cell performance data to obtain the characteristics of each reference hydrogen fuel cell performance data; obtaining the characteristics of each target hydrogen fuel cell performance data based on the characteristics of each extended hydrogen fuel cell performance data, and fusing the characteristics of each target hydrogen fuel cell performance data and the detection instruction description features according to the association between each target hydrogen fuel cell performance data characteristic and the detection instruction description feature to obtain the fused hydrogen fuel cell performance data characteristics, including: obtaining the characteristics of each target hydrogen fuel cell performance data according to the characteristics of each extended hydrogen fuel cell performance data and the characteristics of each reference hydrogen fuel cell performance data; fusing the characteristics of each target hydrogen fuel cell performance data and the detection instruction description features according to the association between each target hydrogen fuel cell performance data characteristic and the detection instruction description feature to obtain the fused hydrogen fuel cell performance data characteristics.

3. The method according to claim 1, wherein The step of respectively in one or more abnormal description ranges of the hydrogen fuel cell performance, abnormally describing the performance description elements of the target hydrogen fuel cell performance data obtained by the hydrogen fuel cell performance data extension operation based on the corresponding performance description element to be processed, obtaining the target abnormally described hydrogen fuel cell performance data, includes: Perform the following operations on the one or more abnormal hydrogen fuel cell performance description ranges respectively to obtain the target abnormal description hydrogen fuel cell performance data: For the hydrogen fuel cell performance data expansion operation that does not cover the indication of abnormal description information, use the hydrogen fuel cell performance data performance description element obtained after performing the hydrogen fuel cell performance data expansion operation on a to-be-processed performance description element as the target hydrogen fuel cell performance data performance description element, and abnormally describe the target hydrogen fuel cell performance data performance description element within the hydrogen fuel cell performance abnormal description range of the to-be-processed performance description element. For the hydrogen fuel cell performance data expansion operation that covers the indication of abnormal description information, obtain the target hydrogen fuel cell performance data performance description element based on each same hydrogen fuel cell performance data performance description element associated with the indication of abnormal description information in the pre-configured hydrogen fuel cell performance data performance description element set, or extract the target hydrogen fuel cell performance data performance description element associated with the indication of abnormal description information from the target reference hydrogen fuel cell performance data, and abnormally describe the target hydrogen fuel cell performance data performance description element within the hydrogen fuel cell performance abnormal description range of the to-be-processed performance description element.

4. The method according to claim 3, wherein The obtaining of the target hydrogen fuel cell performance data performance description element based on each same hydrogen fuel cell performance data performance description element associated with the indication of abnormal description information in the pre-configured hydrogen fuel cell performance data performance description element set includes: Obtain the same hydrogen fuel cell performance data performance description element associated with the performance description element type according to the performance description element type carried by the indication of abnormal description information in the pre-configured hydrogen fuel cell performance data performance description element set; Use any one of the same hydrogen fuel cell performance data performance description elements as the target hydrogen fuel cell performance data performance description element; Alternatively, obtain the target hydrogen fuel cell performance data performance description element by fusing multiple same hydrogen fuel cell performance data performance description elements.

5. The method according to claim 1, wherein The obtaining of the hydrogen fuel cell performance abnormal description range of each of the one or more to-be-processed performance description elements in the to-be-processed hydrogen fuel cell performance data having the same data volume as the hydrogen fuel cell data to be detected includes: Perform feature extraction on the to-be-processed hydrogen fuel cell performance data having the same data volume as the hydrogen fuel cell data to be detected to obtain the characteristics of each abnormal description hydrogen fuel cell performance data; Obtain the association degree between each of the characteristics of the abnormal description hydrogen fuel cell performance data and the fused hydrogen fuel cell performance data characteristics, and based on the abnormal data description set corresponding to the characteristics of the abnormal description hydrogen fuel cell performance data with the association degree greater than or equal to the set threshold, obtain the hydrogen fuel cell performance abnormal description range of each of the one or more to-be-processed performance description elements.

6. The method according to claim 5, characterized in that, Based on the abnormal data description set corresponding to the characteristics of the hydrogen fuel cell performance data with an association degree greater than or equal to a set threshold, obtaining the hydrogen fuel cell performance abnormal description range for each of the one or more performance description elements to be processed, including: Integrating the characteristics of the abnormal description of the hydrogen fuel cell performance data with an association degree greater than or equal to a set threshold to obtain one or more sets of characteristics of the abnormal description of the hydrogen fuel cell performance data; Respectively perform the following operations on the one or more sets of characteristics of the abnormal description of the hydrogen fuel cell performance data: obtain the abnormal operation range of the battery corresponding to each characteristic of the abnormal description of the hydrogen fuel cell performance data in a set of characteristics of the abnormal description of the hydrogen fuel cell performance data, and each abnormal operation range of the battery includes one or more abnormal data description sets; Based on the obtained abnormal operation ranges of each battery, determine the limiting conditions of the hydrogen fuel cell performance abnormal description range, and by connecting the limiting conditions, obtain the hydrogen fuel cell performance abnormal description range of the corresponding performance description element to be processed in the hydrogen fuel cell performance data to be processed.

7. The method according to claim 6, wherein Fusing the target abnormal description of the hydrogen fuel cell performance data and the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result, including: Cover the target abnormal description of the hydrogen fuel cell performance data above the hydrogen fuel cell data to be detected to obtain the hydrogen fuel cell performance detection result; Or, extract the remaining hydrogen fuel cell performance data performance description elements other than the one or more performance description elements to be processed from the hydrogen fuel cell data to be detected, and fuse the one or more remaining hydrogen fuel cell performance data performance description elements into the target abnormal description of the hydrogen fuel cell performance data to obtain the hydrogen fuel cell performance detection result; Or, extract one or more target hydrogen fuel cell performance data performance description elements from the target abnormal description of the hydrogen fuel cell performance data, and fuse the one or more target hydrogen fuel cell performance data performance description elements into the hydrogen fuel cell data to be detected that has been filtered for the one or more performance description elements to be processed to obtain the hydrogen fuel cell performance detection result.

8. The method according to claim 6, characterized in that Obtain the hydrogen fuel cell data to be detected in the following manner: Obtain the original extended hydrogen fuel cell performance data input by the target detection item, and use the original extended hydrogen fuel cell performance data as the hydrogen fuel cell data to be detected; Or, in response to the hydrogen fuel cell performance data extraction instruction, perform hydrogen fuel cell performance data extraction on the original extended hydrogen fuel cell performance data input by the target detection item to obtain the hydrogen fuel cell data to be detected.

9. The method according to claim 6, wherein The performance detection method of the solar-driven hydrogen fuel cell is implemented through a hydrogen fuel cell performance data extension model. By performing the following operations, the hydrogen fuel cell performance data extension model is trained: In a cyclic iteration manner, based on each training hydrogen fuel cell performance data example of the standard extended performance, the untrained hydrogen fuel cell performance data extension model is trained until the iterative training terminates, and the hydrogen fuel cell performance data extension model that has completed the first training is obtained; In a cyclic iteration manner, based on each training hydrogen fuel cell performance data example of the directory retention performance, the hydrogen fuel cell performance data extension model that has completed the first training is trained until the iterative training terminates, and the hydrogen fuel cell performance data extension model that has completed the second training is obtained; Among them, the step of training the untrained hydrogen fuel cell performance data extension model in a cyclic iteration manner based on each training hydrogen fuel cell performance data example of the standard extended performance until the iterative training terminates to obtain the hydrogen fuel cell performance data extension model that has completed the first training includes: Among them, each iteration includes: Based on one or more extension instruction examples, perform standard extension operations on the corresponding training hydrogen fuel cell performance data examples to obtain their respective extended hydrogen fuel cell performance data examples; Obtain the respective set extended hydrogen fuel cell performance data of the corresponding training hydrogen fuel cell performance data examples. Based on one or more extended hydrogen fuel cell performance data examples and the corresponding set extended hydrogen fuel cell performance data, obtain the hydrogen fuel cell performance data extension loss result generated in this iteration, and debug each performance unit in the model in sequence according to the hydrogen fuel cell performance data extension loss result; Among them, the step of training the hydrogen fuel cell performance data extension model that has completed the first training in a cyclic iteration manner based on each training hydrogen fuel cell performance data example of the directory retention performance until the iterative training terminates to obtain the hydrogen fuel cell performance data extension model that has completed the second training includes: Among them, each iteration includes: Based on one or more retention instruction examples, perform directory retention operations on the corresponding training hydrogen fuel cell performance data examples to obtain their respective retained hydrogen fuel cell performance data examples; Obtain the respective set retained hydrogen fuel cell performance data of the corresponding training hydrogen fuel cell performance data examples. Based on one or more retained hydrogen fuel cell performance data examples and the corresponding set retained hydrogen fuel cell performance data, obtain the directory retention loss result generated in this iteration, and debug each performance unit in the model in sequence according to the directory retention loss result.

10. A performance detection system for a solar-driven hydrogen fuel cell, characterized in that, It includes a processor and a memory that communicate with each other. The processor is configured to read and execute a computer program from the memory to implement the method according to any one of claims 1-9.

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