Intelligent analysis and evaluation system for test detection of electrochemical energy storage system

Abstract

The invention relates to an intelligent analysis and evaluation system for test detection of an electrochemical energy storage system. The intelligent analysis and evaluation system is characterized in that a registered user database stores registered user data; calling information of each example is stored in the test example database, and evaluation of the to-be-tested equipment in each test item can be obtained according to an input detection result; the registered equipment database is used for storing registered equipment data and generating equipment codes and test item codes of the registered equipment; the registered equipment data comprises characteristic information and detection information of equipment; the test procedure database is used for storing test procedures applied by various types of equipment; and the platform project database can predict possible faults of the to-be-tested equipment according to the current detection result and previous detection results of the to-be-tested equipment. According to the invention, detection personnel can be guided to carry out different detections on equipment of different types and models, and evaluation and fault prediction can be given according to detection results.

Description

Technical Field

[0001] The invention relates to an intelligent analysis and evaluation system for testing and detecting an electrochemical energy storage system, and belongs to the technical field of electrochemical energy storage equipment detection. Background Art

[0002] Electrochemical energy storage devices can store electrical energy in the form of chemical energy. Configuring electrochemical energy storage in the power grid can effectively solve the problem of uneven peak and valley loads in the power grid. Electrochemical energy storage devices are affected by materials, and there are great problems with safety and stability. Therefore, it is necessary to test the electrochemical energy storage devices and obtain their actual operating parameters. The electrochemical energy storage devices are managed through operating parameters.

[0003] There are many types of electrochemical energy storage system inspections, including appearance inspection, initial charge and discharge energy test, overload charge and discharge performance test, high temperature charge and discharge performance test, storage performance test, overcharge test, overload test, extrusion test, adiabatic temperature rise test and dozens of other types of inspections. Moreover, for different types of electrochemical energy storage systems, different types of inspection contents are also different. Therefore, the requirements for inspectors to conduct test inspections on electrochemical energy storage systems are extremely high. During the inspection, errors in the operation method and sequence may lead to errors in the inspection data at the least, or even cause major safety accidents at the worst.

[0004] Most of the existing technologies use specific equipment to detect a certain type of electrochemical energy storage system. For example, the Chinese invention patent application with publication number CN117708084A discloses an automatic detection and report generation architecture for electrochemical energy storage equipment based on data streams. This architecture can only detect a few detection items. This disclosure cannot help inspectors detect multiple detection items for multiple different types of electrochemical energy storage devices. Summary of the invention

[0005] In order to overcome the above problems, the present invention provides an electrochemical energy storage system test detection intelligent analysis and evaluation system.

[0006] The technical solution of the present invention is as follows:

[0007] In a first aspect, an electrochemical energy storage system test detection intelligent analysis and evaluation system includes a registered user database, a test case database, a platform project database, a test case database, a test equipment database, a registered equipment database and a test procedure database;

[0008] The registered user database stores registered user data and can authorize registered users to use the platform project database;

[0009] The platform project database is communicatively connected with the registered user database, the test case database and the test equipment database;

[0010] The test case database stores the call information of each case, and can obtain the evaluation of the device to be tested in each test item according to the input test results;

[0011] The test equipment database is used to obtain test information of the test equipment;

[0012] The registered device database is used to store the registered device data and generate the device code and test item code of the registered device, and the registered device database is communicatively connected with the test procedure database; the registered device data includes the characteristic information and detection information of the device, the characteristic information includes the device ID, device model and device name, and the detection information includes the previous detection results;

[0013] The test procedure database is used to store the test procedures applied to various types of equipment;

[0014] The platform project database can predict possible faults of the device to be tested based on the current test result and previous test results of the device to be tested.

[0015] Furthermore, the registered device database generates a device code of the registered device according to the feature information of the registered device, and the device code includes at least one of a QR code device code and an RFID device code; after the device code is produced, it is set on the registered device.

[0016] Furthermore, the test procedure includes the name, ID, index and test order of the test items;

[0017] The registered device database generates the test item code according to the feature information of the registered device and the test procedure, wherein the test item code includes at least one of a QR code device code and an RFID device code; after the test item code is produced, it is set on the registered device;

[0018] When generating test item codes, test items are selected through test procedures.

[0019] Furthermore, the registered device data includes non-characteristic information of the device, and the non-characteristic information is the device parameters required in various test items.

[0020] Furthermore, the call information includes a test experiment ID, a function call index, an experiment name, initialization parameters of each calculation example, a test threshold of each calculation example, and an error threshold of each calculation example.

[0021] Furthermore, it also includes a reading device, which is used to read the device code and test item code of the device to be tested;

[0022] The test device database obtains the data of the device to be tested from the registered device database according to the device code and the test item code of the device to be tested;

[0023] The registered device database obtains the registered device data corresponding to the device to be tested according to the device code, obtains the test procedures corresponding to the device to be tested from the test procedure database according to the test item code, and transmits the registered device data and the test procedures as the data of the device to be tested to the test device database;

[0024] The test device database records the status of the device to be tested, and the status of the device to be tested includes suspended, testing, and completed testing;

[0025] The data of the device to be tested, the state of the device to be tested and the time of the state change are transmitted to the platform project database.

[0026] Furthermore, the platform project database obtains the data of the device to be tested, the state of the device to be tested and the time of the state change through the test device database, and selects the test project according to the data of the device to be tested;

[0027] The platform project database displays the test sequence according to the test procedures, so that the test personnel can perform the test according to the test and obtain the relevant data of the equipment to be tested;

[0028] The platform project database transmits relevant data of the device to be tested to the test case database;

[0029] The test case database processes the relevant data of the device to be tested through the corresponding call information, obtains the evaluation of the device to be tested in the test project, and transmits it to the platform project database.

[0030] Furthermore, the platform project database updates the status of the device to be tested and the time of the status change according to the progress status of the test project, and shares the status of the device to be tested and the time of the status change with the test device database.

[0031] Furthermore, the platform project database can predict possible faults of the device to be tested based on the current test results and previous test results of the device to be tested, specifically:

[0032] Obtain the most recent m test results and fault conditions of the same model as the device to be tested, and prepare training samples based on the previous test results and fault conditions. The training samples are multidimensional time series data, as follows:

[0033]

[0034] Among them, a mn is the nth parameter value of the mth detection;

[0035] Constructing an electrochemical energy storage fault prediction model, wherein the electrochemical energy storage fault prediction model includes an input layer, an LSTM layer, a Dropout layer, an LSTM layer, a Dropout layer, a fully connected layer, and an output layer connected in sequence;

[0036] The LSTM layer includes 128 hidden layers;

[0037] The activation ratio of the Dropout layer is 0.2-0.5;

[0038] The electrochemical energy storage fault prediction model is trained using a cross entropy loss function;

[0039] The electrochemical energy storage fault prediction model is trained by the training samples to obtain a trained electrochemical energy storage fault prediction model;

[0040] The previous test results and fault conditions of the device to be tested are obtained, and the most recent m test results and fault conditions of the device to be tested are made into time series data, and the fault condition of the device to be tested is predicted by the electrochemical energy storage fault prediction model.

[0041] In a second aspect, an electrochemical energy storage system test detection intelligent analysis and evaluation device includes a terminal, a barcode printer and a server, wherein the terminal and the barcode printer are respectively connected to the server for communication;

[0042] The terminal includes a client platform and a scanning device, and the scanning device is communicatively connected with the client platform;

[0043] The server is deployed with the electrochemical energy storage system test detection intelligent analysis and evaluation system as claimed in claim 9;

[0044] The registered user database of the server authorizes the verified client platform to use the platform project database;

[0045] The client platform enters the characteristic information and non-characteristic information of the device through the registered device database;

[0046] The registered device database generates a device code and a test item code according to the feature information of the registered device and the test procedure;

[0047] The barcode printer is used to print the device code and the test item code, and the device code and the test item code are pasted on the registered device of Duiyin;

[0048] After the scanning device scans the device code of the registered device, the registered device database transmits the corresponding registered device data to the test device database, and the test device database provides the registered device data to the platform project database and displays it through the client platform;

[0049] The scanning device scans the test item code, and the client platform selects the test item.

[0050] The present invention has the following beneficial effects:

[0051] The evaluation system can guide inspectors to perform different tests on different types and models of equipment and record the test data. Inspectors can select the test items of each device as needed, thereby generating different test item codes. Based on the device code and test item code, the system can provide inspectors with the test sequence and call information of various tests for them to test the equipment. At the same time, the test case database can evaluate the test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a schematic diagram of the modules of the present invention.

[0053] Figure 2 Test sequence for partial detection. DETAILED DESCRIPTION

[0054] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0055] First, refer to Figure 1 , an electrochemical energy storage system test detection intelligent analysis and evaluation system, including a registered user database, a test case database, a platform project database, a test case database, a test equipment database, a registered equipment database and a test procedure database;

[0056] The registered user database stores registered user data and can authorize registered users to use the platform project database;

[0057] The platform project database is communicatively connected with the registered user database, the test case database and the test equipment database;

[0058] The test case database stores the call information of each case, and can obtain the evaluation of the device to be tested in each test item according to the input test results;

[0059] The test equipment database is used to obtain test information of the test equipment;

[0060] The registered device database is used to store the registered device data and generate the device code and test item code of the registered device, and the registered device database is communicatively connected with the test procedure database; the registered device data includes the characteristic information and detection information of the device, the characteristic information includes the device ID, device model and device name, and the detection information includes the previous detection results;

[0061] The test procedure database is used to store the test procedures applied to various types of equipment;

[0062] The platform project database can predict possible faults of the device to be tested based on the current test result and previous test results of the device to be tested.

[0063] In one embodiment of the present invention, the registered device database generates a device code of the registered device based on the feature information of the registered device, and the device code includes at least one of a QR code device code and an RFID device code; after the device code is produced, it is set on the registered device.

[0064] Different devices have different test items, and different devices have different operating procedures for the same test items. Devices of the same model can also set the test type according to their own characteristics and record historical test data. The device code generated based on the feature information can uniquely identify a device and better manage the device.

[0065] In one embodiment of the present invention, the test procedure includes the name, ID, index and test order of the test item.

[0066] The test procedures are used to guide testers to test the equipment. Figure 2 This is the test order for some test items.

[0067] The registered device database generates the test item code according to the feature information of the registered device and the test procedure, wherein the test item code includes at least one of a QR code device code and an RFID device code; after the test item code is produced, it is set on the registered device;

[0068] When generating test item codes, test items are selected through test procedures.

[0069] If you select appearance inspection, initial charge and discharge energy test, overload charge and discharge performance test, and high temperature charge and discharge performance test, you can get the test procedures for these test items by scanning the test item code.

[0070] In one implementation of the present invention, the registered device data includes non-characteristic information of the device, and the non-characteristic information is device parameters required in various test items.

[0071] In one embodiment of the present invention, the call information includes a test experiment ID, a function call index, an experiment name, initialization parameters of each calculation example, a test threshold of each calculation example, and an error threshold of each calculation example.

[0072] The call information is used to set the detection parameters when detecting each project.

[0073] In one embodiment of the present invention, it also includes a reading device, which is used to read the device code and the test item code of the device to be tested;

[0074] The test device database obtains the data of the device to be tested from the registered device database according to the device code and the test item code of the device to be tested;

[0075] The registered device database obtains the registered device data corresponding to the device to be tested according to the device code, obtains the test procedures corresponding to the device to be tested from the test procedure database according to the test item code, and transmits the registered device data and the test procedures as the data of the device to be tested to the test device database;

[0076] The test device database records the status of the device to be tested, and the status of the device to be tested includes suspended, testing, and completed testing;

[0077] The data of the device to be tested, the state of the device to be tested and the time of the state change are transmitted to the platform project database.

[0078] In one embodiment of the present invention, the platform project database obtains the data of the device to be tested, the state of the device to be tested and the time of the state change through the test device database, and selects the test project according to the data of the device to be tested;

[0079] The platform project database displays the test sequence according to the test procedures, so that the test personnel can perform the test according to the test and obtain the relevant data of the equipment to be tested;

[0080] The platform project database transmits relevant data of the device to be tested to the test case database;

[0081] The test case database processes the relevant data of the device to be tested through the corresponding call information, obtains the evaluation of the device to be tested in the test project, and transmits it to the platform project database.

[0082] In one embodiment of the present invention, the platform project database updates the status of the device to be tested and the time of the status change according to the progress status of the test project, and shares the status of the device to be tested and the time of the status change with the test device database.

[0083] In one embodiment of the present invention, the platform project database can predict possible faults of the device to be tested based on the current test result and previous test results of the device to be tested, specifically:

[0084] Obtain the most recent m test results and fault conditions of the same model as the device to be tested, and prepare training samples based on the previous test results and fault conditions. The training samples are multidimensional time series data, as follows:

[0085]

[0086] Among them, a mn is the nth parameter value of the mth detection;

[0087] Constructing an electrochemical energy storage fault prediction model, wherein the electrochemical energy storage fault prediction model includes an input layer, an LSTM layer, a Dropout layer, an LSTM layer, a Dropout layer, a fully connected layer, and an output layer connected in sequence;

[0088] The LSTM layer includes 128 hidden layers;

[0089] The activation ratio of the Dropout layer is 0.2-0.5;

[0090] The electrochemical energy storage fault prediction model is trained using a cross entropy loss function;

[0091] The electrochemical energy storage fault prediction model is trained by the training samples to obtain a trained electrochemical energy storage fault prediction model;

[0092] The previous test results and fault conditions of the device to be tested are obtained, and the most recent m test results and fault conditions of the device to be tested are made into time series data, and the fault condition of the device to be tested is predicted by the electrochemical energy storage fault prediction model.

[0093] The first layer of LSTM is used to capture long-term dependencies, and setting a larger number of hidden layers can improve accuracy;

[0094] The second LSTM layer is used to enhance the model’s capabilities, and the Dropout layer is used to prevent overfitting;

[0095] The fully connected layer acts as a classifier.

[0096] In a second aspect, an electrochemical energy storage system test detection intelligent analysis and evaluation device includes a terminal, a barcode printer and a server, wherein the terminal and the barcode printer are respectively connected to the server for communication;

[0097] The terminal includes a client platform and a scanning device, and the scanning device is communicatively connected with the client platform;

[0098] The server is deployed with the electrochemical energy storage system test detection intelligent analysis and evaluation system as claimed in claim 9;

[0099] The registered user database of the server authorizes the verified client platform to use the platform project database;

[0100] The client platform enters the characteristic information and non-characteristic information of the device through the registered device database;

[0101] The registered device database generates a device code and a test item code according to the feature information of the registered device and the test procedure;

[0102] The barcode printer is used to print the device code and the test item code, and the device code and the test item code are pasted on the registered device of Duiyin;

[0103] After the scanning device scans the device code of the registered device, the registered device database transmits the corresponding registered device data to the test device database, and the test device database provides the registered device data to the platform project database and displays it through the client platform;

[0104] The scanning device scans the test item code, and the client platform selects the test item.

[0105] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure made using the contents of the present invention's specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An electrochemical energy storage system test detection intelligent analysis and evaluation system, characterized in that: Including registered user database, test case database, platform project database, test case database, test equipment database, registered equipment database and test procedure database; The registered user database stores registered user data and can authorize registered users to use the platform project database; The platform project database is communicatively connected with the registered user database, the test case database and the test equipment database; The test case database stores the call information of each case, and can obtain the evaluation of the device to be tested in each test item according to the input test results; The test equipment database is used to obtain test information of the test equipment; The registered device database is used to store the registered device data and generate the device code and test item code of the registered device, and the registered device database is communicatively connected with the test procedure database; the registered device data includes the characteristic information and detection information of the device, the characteristic information includes the device ID, device model and device name, and the detection information includes the previous detection results; The test procedure database is used to store the test procedures applied to various types of equipment; The platform project database can predict possible faults of the device to be tested based on the current test result and previous test results of the device to be tested.

2. According to claim 1, the electrochemical energy storage system test detection intelligent analysis and evaluation system is characterized in that: The registered device database generates a device code of the registered device according to the feature information of the registered device, and the device code includes at least one of a two-dimensional code device code and an RFID device code; after the device code is produced, it is set on the registered device.

3. According to claim 2, the electrochemical energy storage system test detection intelligent analysis and evaluation system is characterized in that: The test procedure includes the name, ID, index and test order of the test items; The registered device database generates the test item code according to the feature information of the registered device and the test procedure, wherein the test item code includes at least one of a QR code device code and an RFID device code; after the test item code is produced, it is set on the registered device; When generating test item codes, test items are selected through test procedures.

4. According to claim 3, the electrochemical energy storage system test detection intelligent analysis and evaluation system is characterized in that: The registered device data includes non-characteristic information of the device, and the non-characteristic information is the device parameters required in various test items.

5. According to claim 4, the electrochemical energy storage system test detection intelligent analysis and evaluation system is characterized in that: The call information includes a test ID, a function call index, a test name, initialization parameters of each calculation example, a test threshold of each calculation example, and an error threshold of each calculation example.

6. The electrochemical energy storage system test detection intelligent analysis and evaluation system according to claim 5 is characterized in that: It also includes a reading device, which is used to read the device code and test item code of the device to be tested; The test device database obtains the data of the device to be tested from the registered device database according to the device code and the test item code of the device to be tested; The registered device database obtains the registered device data corresponding to the device to be tested according to the device code, obtains the test procedures corresponding to the device to be tested from the test procedure database according to the test item code, and transmits the registered device data and the test procedures as the data of the device to be tested to the test device database; The test device database records the status of the device to be tested, and the status of the device to be tested includes suspended, testing, and completed testing; The data of the device to be tested, the state of the device to be tested and the time of the state change are transmitted to the platform project database.

7. The electrochemical energy storage system test detection intelligent analysis and evaluation system according to claim 6 is characterized in that: The platform project database obtains the data of the device to be tested, the state of the device to be tested and the time of the state change through the test device database, and selects the test project according to the data of the device to be tested; The platform project database displays the test sequence according to the test procedures, so that the test personnel can perform the test according to the test and obtain the relevant data of the equipment to be tested; The platform project database transmits relevant data of the device to be tested to the test case database; The test case database processes the relevant data of the device to be tested through the corresponding call information, obtains the evaluation of the device to be tested in the test project, and transmits it to the platform project database.

8. The electrochemical energy storage system test detection intelligent analysis and evaluation system according to claim 7, characterized in that: The platform project database updates the status of the device to be tested and the time of the status change according to the progress status of the test project, and shares the status of the device to be tested and the time of the status change with the test device database.

9. The electrochemical energy storage system test detection intelligent analysis and evaluation system according to claim 8, characterized in that: The platform project database can predict possible faults of the device to be tested based on the current test results and previous test results of the device to be tested, specifically: Obtain the most recent m test results and fault conditions of the same model as the device to be tested, and prepare training samples based on the previous test results and fault conditions. The training samples are multidimensional time series data, as follows: Among them, a mn is the nth parameter value of the mth detection; Constructing an electrochemical energy storage fault prediction model, wherein the electrochemical energy storage fault prediction model includes an input layer, an LSTM layer, a Dropout layer, an LSTM layer, a Dropout layer, a fully connected layer, and an output layer connected in sequence; The LSTM layer includes 128 hidden layers; The activation ratio of the Dropout layer is 0.2-0.5; The electrochemical energy storage fault prediction model is trained using a cross entropy loss function; The electrochemical energy storage fault prediction model is trained by the training samples to obtain a trained electrochemical energy storage fault prediction model; The previous test results and fault conditions of the device to be tested are obtained, and the most recent m test results and fault conditions of the device to be tested are made into time series data, and the fault condition of the device to be tested is predicted by the electrochemical energy storage fault prediction model.

10. An intelligent analysis and evaluation device for testing and detecting an electrochemical energy storage system, characterized in that: It includes a terminal, a barcode printer and a server, wherein the terminal and the barcode printer are respectively connected to the server for communication; The terminal includes a client platform and a scanning device, and the scanning device is communicatively connected with the client platform; The server is deployed with the electrochemical energy storage system test detection intelligent analysis and evaluation system as claimed in claim 9; The registered user database of the server authorizes the verified client platform to use the platform project database; The client platform enters the characteristic information and non-characteristic information of the device through the registered device database; The registered device database generates a device code and a test item code according to the feature information of the registered device and the test procedure; The barcode printer is used to print the device code and the test item code, and the device code and the test item code are pasted on the registered device of Duiyin; After the scanning device scans the device code of the registered device, the registered device database transmits the corresponding registered device data to the test device database, and the test device database provides the registered device data to the platform project database and displays it through the client platform; The scanning device scans the test item code, and the client platform selects the test item.

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