Plasma control system test platform, test method and storage medium

Abstract

The invention discloses a plasma control system test platform, a test method and a storage medium, and relates to the technical field of test systems. The system specifically comprises a client which is provided with a task submission module and an interactive visualization module; the server and the task uploading module are used for receiving tasks uploaded by the client, analyzing the tasks and then sending the analyzed tasks to the task queue scheduler, and the task queue scheduler performs queue jumping or queuing on the uploaded tasks according to priorities; the multi-mode executor is connected to the PCS and the PCS-VP, the multi-mode executor obtains a queue head task of the task queue, and according to a task mode, the PCS process is started to execute the task or the PCS and the PCS-VP processes are started at the same time to execute the task; and after the task is executed, the data analysis module obtains original execution data, processes the data and feeds back the processed data to the client interactive visualization module. The invention aims to realize full-process dynamic interaction between a plasma control system and a master control system and meet complex requirements of modern experimental tests.

Description

Technical Field

[0001] The present invention relates to the technical field of testing systems, and in particular to a plasma control system testing platform, a testing method and a storage medium. Background Art

[0002] In fusion reactions, plasma control systems play a vital role. Their main task is to ensure the stability of fusion reactions by precisely controlling plasma parameters (such as temperature, density, and magnetic field). However, the high temperature, high energy, and complexity of plasma make the stability and reliability of its control system the decisive factors for the success or failure of fusion experiments. Therefore, how to improve the testing and verification efficiency of plasma control systems and ensure their reliability in actual experiments is a major topic in current fusion experimental research.

[0003] At present, traditional fusion experimental test systems often rely on manual operations for testing and verification. In this process, testers need to manually modify the test configuration files and execute a series of test processes one by one. This manual operation method is not only cumbersome and time-consuming, but also easily affected by human factors, resulting in errors and uncertainties in the test process, which in turn affects the accuracy and reliability of the test results. In addition, traditional testing methods usually lack the support of automated testing tools, rely on a single test mode, and cannot build a full-process dynamic interaction between the plasma control system and the master control system, and cannot monitor and adjust the interactive behavior of the system in real time. This limitation makes real-time feedback and adjustment during the test process difficult, and cannot fully explore and solve potential system problems, greatly limiting the comprehensiveness and real-time nature of the test.

[0004] Therefore, how to achieve full-process dynamic interaction between the plasma control system and the master control system to meet the complex needs of modern experimental testing has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The main purpose of the present invention is to provide a plasma control system test platform, a test method and a storage medium, aiming to realize the full-process dynamic interaction between the plasma control system and the master control system, and meet the complex needs of modern experimental testing.

[0006] In order to achieve the above object, the present invention provides a plasma control system test platform, comprising: The client is provided with a task submission module and an interactive visualization module, wherein the task submission module is used to support single task form configuration and / or batch task file upload; The server is provided with a task upload module, a task queue scheduler, a multimodal executor, and a data analysis module; the task upload module is used to receive tasks uploaded by the client, and send the tasks to the task queue scheduler after parsing, and the task queue scheduler cuts in or queues the uploaded tasks according to the priority; the multimodal executor is connected to the PCS and PCS-VP, and the multimodal executor obtains the head task of the task queue, and according to the task mode, starts the PCS process to execute the task or starts the PCS and PCS-VP processes to execute the task at the same time; after the task is executed, the data analysis module obtains the original execution data, and feeds back the data to the client interactive visualization module after processing.

[0007] In one embodiment of the present application, queueing or queuing the uploaded tasks according to the priority includes: The task queue scheduler obtains the task priority and determines whether the current priority is a privileged task. If it is a privileged task, it checks whether there are unfinished privileged tasks in the current queue. If there are unfinished privileged tasks, the new privileged task is inserted after the most recent privileged task. If there are no unfinished privileged tasks, the new privileged task is inserted at the head of the queue. If it is not a privileged task, the task will be inserted at the end of the queue. After the task is executed, the task at the head of the queue will be deleted and the database status field will be updated.

[0008] In one embodiment of the present application, the task modes include: scene playback mode and simulation test mode; When the multi-modal actuator determines that the mode is the scene playback mode, modify the PCS configuration file to mode, start the PCS process, call the analog central control system module to generate a hardware trigger signal, and the signal outputs a high-level pulse through the NII / O card; When the multi-mode actuator determines that the mode is the simulation test mode, modify the PCS configuration file to mode, start the PCS and PCS-VP processes; transmit the control signal to PCS-VP through the shared memory, receive the analog acquisition signal and transmit it back to PCS to form a closed loop.

[0009] In one embodiment of the present application, the data is processed and fed back to the client interactive visualization module, including: The data analysis module reads the experimental gun data and the historical reference gun data from the database storing the original execution data, identifies the flat-top segments in the experimental gun data and the historical reference gun data, performs flat-top segment waveform analysis and boundary offset Euclidean distance calculation, stores the intermediate results as target format files, records the path in the database test gun table, and feeds back the analysis results to the client's interactive visualization module, which displays visualization charts.

[0010] In an embodiment of the present application, the client is further provided with a document generation module. The document generation module obtains the path of the visualization chart displayed by the interactive visualization module, the analysis result summary, and the custom annotation, and calls a general large language model to integrate the visualization chart, the analysis result summary, and the custom annotation to generate a structured document.

[0011] In an embodiment of the present application, the server is further provided with a status monitor module. The status monitor module subscribes to the PCS health information published by the open source distributed control system framework, integrates the running status of the platform itself, and pushes the integrated status data to the client through WebSocket to trigger real-time refreshing of the client interface.

[0012] In an embodiment of the present application, the client is provided with an identity authentication module, and the server is provided with an identity verification module. The identity verification module receives the identity data of the identity authentication module. When the identity data is for new user registration, it stores the identity data and feedbacks the registration result; when the identity data is historical data, it compares the identity data with its own database and distributes corresponding permissions.

[0013] In an embodiment of the present application, the permissions include: administrator, core developer, and ordinary developer.

[0014] The present application also discloses a method for testing a plasma control system, including the following steps: S1. The user submits a single-task form configuration and / or a batch task file through the client. S2. The server verifies the permissions and schedules the task to the queue. S3. The multimodal actuator dynamically adjusts the PCS operating parameters according to the task configuration. S4. The status monitor collects the PCS health data in real time and pushes it to the client. S5. The document generation module processes the test results to generate a visualization chart and an automated report.

[0015] The present application also discloses a computer-readable storage medium storing a computer program, and when the program is executed by a processor, the steps of the above-mentioned method are implemented.

[0016] By adopting the above technical solutions, the plasma control system test platform of the present invention can efficiently manage and execute the test tasks of the plasma control system by integrating multiple functions such as task submission, queue scheduling, task execution, and data analysis. Through clear functional division and close cooperation between the client and the server, users can conveniently submit tasks and view the test results in real time. At the same time, the system can reasonably schedule according to the priority and type of tasks, thereby improving the test efficiency and resource utilization rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention is described in detail below with reference to specific embodiments and accompanying drawings, wherein: Figure 1 A schematic diagram of the system structure of the first embodiment of the present invention; Figure 2 It is a schematic diagram of the process structure of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the following specific embodiments are only used to explain the present invention and do not constitute a limitation to the present invention.

[0019] like Figure 1 As shown, in order to achieve the above-mentioned purpose, the present invention proposes a plasma control system test platform, comprising: The client is provided with a task submission module and an interactive visualization module, wherein the task submission module is used to support single task form configuration and / or batch task file upload; The server is provided with a task upload module, a task queue scheduler, a multimodal executor, and a data analysis module; the task upload module is used to receive tasks uploaded by the client, and send the tasks to the task queue scheduler after parsing, and the task queue scheduler inserts or queues the uploaded tasks according to the priority; the multimodal executor is connected to PCS and PCS-VP (plasma control system virtual platform), and the multimodal executor obtains the head task of the task queue, and according to the task mode, starts the PCS process to execute the task or starts the PCS and PCS-VP processes to execute the task at the same time; after the task is executed, the data analysis module obtains the original execution data, and feeds back the data to the client interactive visualization module after processing.

[0020] Specifically, the task submission module supports two ways of uploading tasks. The first way is single-task form configuration, where users fill in task-related parameters such as test type and test mode through the client interface. The second way is batch task file upload, where users select a file containing multiple task configurations, and the client will perform format verification on the file to ensure that the file content conforms to the specified format. If the file format meets the requirements, the client will parse it into JSON format and upload it to the task upload module on the server.

[0021] The interactive visualization module receives the data processed by the data analysis module and displays it graphically. The display content includes but is not limited to the execution status of the test task and the task results. Users can view the task execution process and its results in real time in this module, and zoom in, zoom out or select specific data for detailed analysis through interactive operations.

[0022] The server includes a task upload module, a task queue scheduler, a multi-modal executor, and a data analysis module.

[0023] The task upload module receives single task or batch task files uploaded from the client and parses them. For single task form configuration, the task upload module parses the form content into JSON format data; for batch task file upload, the task upload module parses the file content and converts it into JSON format data, and then transmits the parsed task data to the task queue scheduler.

[0024] The task queue scheduler manages the task queue according to the priority of the task. The priority of the task is set by the client when uploading the task, which can be divided into high priority and normal priority. The task queue scheduler sorts the tasks according to the priority and decides whether to insert the task into the queue according to the priority of the task. If there is a high priority task, the task queue scheduler will insert the task at the head of the queue, and if it is a normal task, it will be inserted at the end of the queue.

[0025] The multimodal executor is used to start and manage the task execution process of the plasma control system PCS and PCS-VP. The multimodal executor obtains the head task of the task queue and decides whether to start only the PCS process to execute the task, or to start both the PCS process and the PCS-VP process to execute the task according to the task mode. If the task mode is a scene playback test, only the PCS process is started; if the task mode is a simulation test, the PCS process and the PCS-VP process are started at the same time. During the execution process, the coordination and data exchange between PCS and PCS-VP are completed through specific interfaces to ensure the synchronization and accuracy of task execution.

[0026] After the task is executed, the data analysis module will obtain the original execution data from the PCS or PCS-VP process. The data analysis module processes the obtained data, including but not limited to data cleaning, calculation analysis, result evaluation, etc. The processed data will be sent to the client's interactive visualization module through the feedback mechanism for users to view and analyze.

[0027] By adopting the above technical solution, the plasma control system test platform of the present invention can efficiently manage and execute the test tasks of the plasma control system by integrating multiple functions such as task submission, queue scheduling, task execution and data analysis. Through clear functional division and close collaboration between the client and the server, users can conveniently submit tasks and view test results in real time. At the same time, the system can reasonably schedule tasks according to their priority and type, thereby improving the efficiency of testing and resource utilization.

[0028] In one embodiment of the present application, queueing or queuing the uploaded tasks according to the priority includes: The task queue scheduler obtains the task priority and determines whether the current priority is a privileged task. If it is a privileged task, it checks whether there are unfinished privileged tasks in the current queue. If there are unfinished privileged tasks, the new privileged task is inserted after the most recent privileged task. If there are no unfinished privileged tasks, the new privileged task is inserted at the head of the queue. If it is not a privileged task, the task will be inserted at the end of the queue. After the task is executed, the task at the head of the queue will be deleted and the database status field will be updated.

[0029] Specifically, the task queue scheduler first obtains the priority of the task, which is set by the client when submitting the task. The priority is divided into two categories: "privileged tasks" and "non-privileged tasks". Privileged tasks represent urgent or high-priority test tasks, while non-privileged tasks are regular tasks with lower processing priorities.

[0030] The task queue scheduler determines whether the task is a privileged task based on the task priority identifier. If the current task is a privileged task, it enters the queue-jumping process of the privileged task; if the current task is not a privileged task, it enters the regular task processing process.

[0031] When the task queue scheduler determines that the current task is a privileged task, it first needs to query whether there are any unfinished privileged tasks in the task queue. Each task in the task queue will record its execution status (such as "to be executed", "executing", "completed", etc.). Unfinished privileged tasks are tasks whose status is not "completed".

[0032] If there are unfinished privileged tasks in the task queue, the task queue scheduler will insert the newly submitted privileged task after the last unfinished privileged task in the sequential queue. This operation ensures that privileged tasks are executed in the order they are submitted, avoiding conflicts between different privileged tasks. If there are no unfinished privileged tasks in the queue, the new privileged task will be directly inserted at the head of the queue to ensure that it is executed before other tasks.

[0033] If the current task is a non-privileged task, the task queue scheduler inserts it to the end of the task queue. This ensures that regular tasks are executed in the order they are submitted, but will not take precedence over privileged tasks. When the task at the head of the queue is completed, the task queue scheduler removes it from the queue and updates the task status field in the database. The update operation of the status field includes marking the task status as "completed" and recording the execution time or other relevant information of the task. The operation of updating the database ensures the synchronization of the task execution history and the system status.

[0034] By adopting the above technical solution, the task queue scheduler can reasonably schedule tasks according to their priorities, privileged tasks can be executed first, and regular tasks are queued for execution. This scheduling method can not only ensure that urgent tasks are handled in a timely manner, but also reasonably allocate system resources, improve the efficiency of task execution and the responsiveness of the system. Through the update of task status and reasonable queue management, the system can maintain a good task execution order and transparency of the operating status, providing reliable support for subsequent data analysis and system optimization.

[0035] In one embodiment of the present application, the task modes include: scene playback mode and simulation test mode; When the multi-modal actuator determines that the mode is the scene playback mode, modify the PCS configuration file to mode, start the PCS process, call the analog central control system module to generate a hardware trigger signal, and the signal outputs a high-level pulse through the NII / O card; When the multi-mode actuator determines that the mode is the simulation test mode, modify the PCS configuration file to mode, start the PCS and PCS-VP processes; transmit the control signal to PCS-VP through the shared memory, receive the analog acquisition signal and transmit it back to PCS to form a closed loop.

[0036] Specifically, the multi-modal executor determines the execution mode of the task according to the mode of the first task in the task queue. The task mode includes a scene playback mode and a simulation test mode.

[0037] After the multimodal executor obtains a task, it first identifies the mode of the task and selects different execution methods according to the mode.

[0038] If the task mode is determined to be the scene playback mode, you first need to modify the PCS configuration file. The configuration file modification process includes setting the PCS operation mode to " ", in this mode, PCS will run historical data playback without real-time control. After the configuration file is modified, the multi-modal actuator starts the PCS process. In this mode, PCS will process the historical data according to the playback to simulate the process of historical experiments. In order to simulate the dynamic changes of historical scenes, the multi-modal actuator calls the simulation central control system module to generate a hardware trigger signal. The hardware trigger signal is generated by The card outputs a high level pulse signal. In this way, the control signal can interact correctly between the PCS and the hardware.

[0039] If the task mode is simulation test mode, the multi-mode actuator will first modify the PCS configuration file and set its operation mode to " ". In this mode, PCS and PCS-VP will work together for simulation control and simulation acquisition. After the configuration file is modified, the multimodal actuator starts the PCS process and the PCS-VP process at the same time. PCS is responsible for the generation of control signals, while PCS-VP is responsible for simulating the response of plasma. In order to achieve real-time transmission of control signals, the multimodal actuator transmits the control signals generated by the PCS process to PCS-VP through shared memory. The shared memory mechanism ensures that the data exchange between PCS and PCS-VP is timely and stable. After PCS-VP simulates the acquisition signal, the simulated acquisition signal is transmitted back to PCS to form a control closed loop. In this way, PCS can adjust the system according to the feedback signal of PCS-VP to achieve closed-loop control of the test task.

[0040] What comes to mind is: The system will be affected by a variety of disturbance factors in actual operation. Random noise, offset error and drift error are set to deal with disturbance factors in the system. It is used to study the anti-interference ability of the control system and its tolerance to signal errors.

[0041] In this application, an error injection module is designed. The error injection module includes three types of errors to simulate the operation of PCS under different abnormal conditions, namely random noise, offset error and drift error. Among them, random noise corresponds to unpredictable random fluctuations in the measurement signal, which is usually caused by thermal noise or environmental electromagnetic interference. Offset error corresponds to the constant deviation between the measured value and the true value, which is often caused by inaccurate sensor calibration or hardware aging. Drift error corresponds to the gradual deviation of the measurement system from the true value over time, which is usually caused by temperature changes or component aging.

[0042] In the random noise test, high-frequency random fluctuations are simulated by multiplying the signal by a random gain coefficient. The expression of the signal is: ; in, is the original signal, is the amplitude range of the random gain coefficient, is a random noise signal with a mean of 0 and a variance of 1. The random noise test is used to evaluate the stability and anti-interference ability of the system under high-frequency random fluctuations.

[0043] The offset error test is performed by adding a fixed offset value to the signal. , its signal model is:

[0044] in, is the original signal, is a constant offset value used to simulate measurement deviations caused by sensor calibration errors or hardware aging. This test is used to verify the control accuracy and error compensation capabilities of the system under constant deviation conditions.

[0045] The drift error test is performed by introducing an offset that increases gradually over time. , the mathematical model of the signal is: ; in, is the original signal, is a function that grows linearly with time and is usually expressed as: ; in, is the drift rate, and t is the time. The drift error test is used to simulate the situation where the measurement system gradually deviates from the true value during long-term operation. The focus is on studying the system's ability to track gradual changes in signals, as well as its adaptability and robustness in long-term operation. Through the above three types of error tests, the performance of Lingshu PCS under different abnormal working conditions can be evaluated, providing a basis for the optimal design of the system.

[0046] The error injection test is mainly divided into two modes: anti-interference ability test and control ability test.

[0047] During the anti-interference ability test, PCS-VP reads historical discharge data from the database, converts the historical discharge data into 288 electromagnetic measurement signals through the ToRFM module, adds disturbances through the error injection module, and transmits them back to the RT node in the PCS through the RFMout module. The user can set the threshold and judge the anti-interference ability of the algorithm by comparing the difference between the algorithm output after injection and before injection.

[0048] Control capability test: a closed control loop is formed between PCS and PCS-VP, the actual plasma is replaced by a simulation model, control signals are input to PCS-VP, and PCS-VP outputs analog acquisition signals. The error injection module is used to modify the signal and intensity of the error injection, which can help users test the control capability of Lingshu PCS under abnormal conditions.

[0049] In the actual operation of plasma, it will be affected by a variety of abnormal factors, which will lead to the occurrence of plasma rupture, and the rupture phenomenon may cause serious consequences such as device damage. Therefore, an abnormal handling mechanism is introduced in PCS. In order to facilitate abnormal handling, an abnormal test unit is set up.

[0050] Define PCS abnormal time: The plasma current anomaly is when the deviation between the measured plasma current and the target current exceeds a threshold.

[0051] A vertical displacement event is when the displacement growth rate of the plasma in the vertical direction exceeds a threshold.

[0052] The rupture prediction is that the system predicts that the plasma has a high probability of rupture.

[0053] The poloidal field coil current abnormality means that the deviation between the poloidal field coil current and the target current exceeds the allowable range.

[0054] Poloidal field coil overcurrent means that the current in the poloidal field coil exceeds the set maximum allowable value.

[0055] Power failure is to detect whether there is power abnormality or interruption through power signal.

[0056] The electromagnetic diagnostic signal is abnormal. The signal from the electromagnetic self-diagnosis system is abnormal.

[0057] The RMP coil current abnormality means that the actual current of the RMP coil deviates too much from the target current.

[0058] RMP coil overcurrent means the current in the RMP coil exceeds the maximum set limit.

[0059] The first wall hot spot warning is when the surface temperature of the first wall component exceeds the warning threshold.

[0060] The first wall hot spot fault is when the surface temperature of the first wall component exceeds the fault threshold.

[0061] When the signal anomaly test unit in the present application works, its principle is the same as that of the anti-interference ability test and the control ability test, and it only needs to replace the error injection module in the anti-interference ability test and the control ability test with the signal anomaly test module to work. As described above, it will not be repeated here.

[0062] With the above technical solution, the multi-modal actuator can flexibly switch the execution mode according to different task modes. In the scene playback mode, the system can accurately simulate the historical experimental process and trigger the hardware signal to ensure the accuracy of the playback; in the simulation test mode, PCS and PCS-VP can work together to simulate the plasma response process through the interaction of control signals and simulation signals to ensure the comprehensiveness and reliability of the test. Through the precise control of the task mode, the platform can effectively support a variety of complex test requirements and improve the efficiency and accuracy of the test.

[0063] In one embodiment of the present application, the data is processed and fed back to the client interactive visualization module, including: The data analysis module reads the experimental gun data and the historical reference gun data from the database storing the original execution data, identifies the flat-top segments in the experimental gun data and the historical reference gun data, performs flat-top segment waveform analysis and boundary offset Euclidean distance calculation, stores the intermediate results as target format files, records the path in the database test gun table, and feeds back the analysis results to the client's interactive visualization module, which displays visualization charts.

[0064] Specifically, the data analysis module first reads the experimental gun data and historical reference gun data from the database storing the original execution data. The experimental gun data refers to the data in the currently executed test task, while the historical reference gun data is the data used for comparison and evaluation. The data analysis module selects to read relevant data from the test gun table in the database as needed.

[0065] After reading the experimental shot data and historical reference shot data, the data analysis module will process these data and identify the flat-top segment. The flat-top segment is a specific time period in the plasma discharge process. The data analysis module detects and marks these data through specific algorithms (such as signal analysis, waveform matching, etc.) to identify the start and end time of the flat-top segment.

[0066] After the flat-top segment is identified, the data analysis module will perform waveform analysis on the data of the flat-top segment. The purpose of this step is to compare the waveform characteristics in the experimental shot data with the historical reference shot data and analyze their performance in the flat-top segment. The data analysis module will calculate the shape of the waveform, amplitude change, and other related features, and quantify these features to form the analysis results.

[0067] The data analysis module also calculates the boundary offset between the experimental gun and the historical reference gun. To this end, the data analysis module uses the Euclidean distance algorithm to compare the boundary positions of the experimental gun data and the historical reference gun data in the flat top section and calculate the offset between them. The calculation result is used to evaluate the deviation of the experimental data and the stability of the test task.

[0068] The analysis method is: Identify the start time of the flat top segment and end time , these times mark the flat-top section of the plasma, and this part of the data will be used for subsequent offset calculations.

[0069] For each time slice of the flat top segment For processing, the time slice range is from arrive Each time slice Corresponding to a set of boundary point data.

[0070] For each time slice , extract the reference boundary point set The set of boundary points after the error is introduced .

[0071] : indicates that the reference boundary is in the time slice The set of boundary points on , where each boundary point is represented by the coordinates express, is the number of reference boundary points. Indicates the coordinate value of the reference boundary point on the x-axis, Indicates the coordinate value of the reference boundary point on the y-axis.

[0072] : indicates that the boundary with error is in the time slice A set of boundary points on , where each boundary point is represented by coordinates express, is the number of error boundary points. Indicates the coordinate value of the error boundary point on the x-axis, Indicates the coordinate value of the error boundary point on the y-axis.

[0073] For the reference boundary and the boundary after the error is introduced, the Euclidean distance between each pair of points is calculated.

[0074] For the reference boundary point , select the closest point from the set of boundary points after the error is introduced .

[0075] For each pair of matched reference boundary points and error boundary points, calculate the Euclidean distance between them , :

[0076] in, It is the reference point and error points The Euclidean distance between .

[0077] For time slices , calculate the average offset after all reference boundary points are matched with the error boundary points : ; in, It's a time slice The average offset in is the set of reference boundary points The number of boundary points.

[0078] After completing the flat-top waveform analysis and boundary offset Euclidean distance calculation, the data analysis module stores the intermediate calculation results in the form of a target format file. These results include waveform analysis data, boundary offset data, and other related data. The storage path will be recorded in the test shot table of the database for subsequent query and access.

[0079] After completing the data processing, the data analysis module passes the analysis results to the client's interactive visualization module through a feedback mechanism. The feedback data includes waveform analysis results, boundary offset analysis results, etc. The client generates corresponding visualization charts based on these data. The interactive visualization module can dynamically display these charts and support users to interact with the data (such as zooming in, zooming out, viewing detailed data, etc.).

[0080] In the interactive visualization module of the client, users will be able to view charts generated based on the data analysis results. Charts can include flat-top waveforms, boundary offset graphs, etc., showing information such as time changes in data, feature comparisons, and boundary changes. Through interactive operations, users can select different experimental and reference gun data for comparative analysis, which is convenient for real-time evaluation of experimental results and making adjustments.

[0081] With the above technical solution, the data analysis module can accurately identify the flat-top segment and perform waveform analysis and boundary offset calculation by automatically processing and analyzing the experimental gun data and historical reference gun data. By storing and feeding back the analysis results to the client's interactive visualization module, users can view charts and data analysis results in real time. This visual display not only enhances the data analysis capabilities of the test platform, but also improves the user's intuitive perception of data changes during task execution, which helps to further optimize the test process and experimental design.

[0082] In one embodiment of the present application, the client is also provided with a document generation module, which obtains the path of the interactive visualization module to display the visualization chart, the analysis result summary, and the custom annotations, and calls the general large language model to integrate the visualization chart, the analysis result summary, and the custom annotations to generate a structured document.

[0083] Specifically, the document generation module first obtains the path of the visualization chart displayed by the interactive visualization module. The path points to the chart file viewed by the user on the client, which displays the analysis results of the test task, such as the flat-top waveform chart, the boundary offset chart, etc. The document generation module obtains the path information of these charts by interacting with the interface of the interactive visualization module.

[0084] After obtaining the path to the visualization chart, the document generation module also needs to obtain the analysis result summary corresponding to the chart. These summaries are brief summaries of the output of the data analysis module, including an overview of the data analysis results, evaluation conclusions, and key findings. The analysis result summary provides the necessary background information for the content of the document, allowing users to quickly understand the key points of the analysis results.

[0085] In addition to the analysis result summary and chart path, the document generation module also needs to obtain the user's customized comments on the client side. These comments include the user's explanation of the test process, personal insights into data analysis, or special concerns about the results. Customized comments provide personalized explanations and background information for users, making the final generated document more comprehensive and in line with user needs.

[0086] The document generation module integrates the acquired content using a general large language model (such as the deepseek series model). The large language model first converts the path of the visualization chart, the summary of the analysis results, and the custom annotations into structured content, and then integrates these contents into a structured document in a certain logical order. The document generation process includes a detailed description of the analysis results, an explanation of the chart, and the organization and integration of user-defined annotations.

[0087] The content after integration of the general large language model will be converted into a structured document. The structured document includes components such as titles, chapters, charts, text descriptions and comments, and the format is standardized and easy for users to understand and further use. The document generation module ensures that the document content is clear and formatted, and embeds charts and analysis results into the document in an appropriate manner for easy viewing and archiving by users.

[0088] The generated structured documents will be stored on the server, and the client can download the documents through the corresponding download interface. The documents can be saved in PDF, Word or other common formats, and users can download, store or print them as needed.

[0089] Using the above technical solution, the document generation module can automatically integrate the charts, data analysis result summaries and user-defined annotations displayed by the interactive visualization module into structured documents. This process not only reduces the workload of manual document writing, but also improves the efficiency and accuracy of document generation. Through the powerful integration capabilities of the general large language model, the generated document content has high quality and can meet the needs of users in test result archiving, report generation and other aspects. This automated document generation method improves the user experience, allowing the test platform to not only provide real-time data analysis, but also provide users with efficient document output support.

[0090] In one embodiment of the present application, the server is also provided with a status monitor module, which subscribes to the PCS health information published by the open source distributed control system framework, integrates the platform's own operating status, pushes the integrated status data to the client via WebSocket, and triggers real-time refresh of the client interface.

[0091] Specifically, the status monitor module first subscribes to and obtains the health information of the PCS (plasma control system) through the open source distributed control system framework. The open source distributed control system framework will regularly publish the health status data of the PCS, including but not limited to the system's operating status, equipment health, connection status, etc. The status monitor module will receive the health data of the PCS through the framework interface to ensure that the latest system health status is obtained in real time.

[0092] In addition to subscribing to PCS health information, the status monitor module also needs to integrate the platform's own operating status. These status data include but are not limited to the server's CPU usage, memory usage, disk space, network connection status, etc. The status monitor module will regularly check and collect the platform's own operating data and integrate it with the PCS health information. The integrated data can fully reflect the health status of the system and platform, ensuring the comprehensiveness and accuracy of monitoring.

[0093] After integrating the PCS health information and the platform operation status, the status monitor module pushes the integrated status data to the client through WebSocket technology. WebSocket is a two-way communication protocol that allows the server and the client to establish a persistent connection, so that data can be pushed to the client in real time when the server status changes. The status monitor module uses WebSocket to push real-time data such as the health information and operation status of the platform and PCS to the client, ensuring that users can see the system operation status in real time in the client interface.

[0094] After the client receives the pushed status data through WebSocket, it triggers a real-time refresh of the interface. The client's interactive interface updates the display content based on the latest status data received. For example, the client may display different warning or prompt information based on the system health status, or dynamically display the usage of system resources. This allows users to instantly understand the system's operating status, discover potential system problems in a timely manner, and improve the system's maintainability and responsiveness.

[0095] With the above technical solution, the status monitor module can obtain PCS health information and the platform's own operating status in real time, and efficiently push this data to the client through WebSocket technology, triggering real-time refresh of the interface. This real-time status monitoring method not only improves the platform's monitoring capabilities, but also effectively helps users understand the system status in a timely manner, discover problems in advance and deal with them. Through real-time feedback of system health data, users can maintain full control of the platform status during the test process, improving the reliability and maintenance efficiency of the system.

[0096] In one embodiment of the present application, the client is provided with an identity authentication module, and the server is provided with an identity verification module. The identity verification module receives the identity data of the identity authentication module. When the identity data is for a new user registration, the identity data is stored and the registration result is fed back. When the identity data is historical data, the identity data is compared with its own database and corresponding permissions are distributed.

[0097] Specifically, the client is equipped with an identity authentication module. When the user authenticates the user on the client, he confirms his identity by entering the user name, password and other identity data. The identity authentication module will first check the credential data entered by the user. When the identity data entered by the user has not been registered in the system, the identity authentication module will determine that the data is a new user registration. The system will guide the user into the registration process and require the user to provide necessary personal information (such as user name, password, email, etc.). When the identity data entered by the user matches the user already existing in the system, the identity authentication module determines that the identity data is historical data and continues to process the login verification.

[0098] The server is equipped with an identity verification module, which receives identity data transmitted from the client identity verification module. The identity verification module performs corresponding operations based on different identity data: If the identity data transmitted by the identity authentication module is for a new user registration, the identity verification module will receive the identity data and store it in the server's database. All user information is stored using encryption technology to ensure data security. Once the user is successfully registered, the identity verification module will create the new user's account information and store its username, password and other related data to ensure the uniqueness and security of the user's identity in the system. After the storage process is completed, the identity verification module will feedback the registration results to the client, including whether the registration is successful and related prompts. If the registration fails, the client will prompt the user to check the input information and resubmit.

[0099] If the identity data transmitted by the identity authentication module is historical user data, the identity verification module will compare the transmitted identity data with the existing user data in its own database. The comparison includes whether the user name and password match. If the comparison is successful, it means that the identity authentication is passed. The identity verification module will distribute corresponding permissions based on the user's role and permission information. These permissions determine the user's scope of operation in the system (such as administrator, core developer, ordinary developer, etc.). After the permissions are assigned, the identity verification module will transmit the corresponding permission information back to the client, and the client will control the user's operation interface and function access based on the permissions.

[0100] With the above technical solution, the identity authentication and verification module can effectively manage the user's identity and permissions. When a new user registers, the system can safely and conveniently store user data and feedback the registration results; when a historical user logs in, the system quickly verifies the user's identity and assigns corresponding permissions based on the role by comparing the identity data with the database. This mechanism not only improves the system's security and user experience, but also ensures the rationality of permission allocation and the stable operation of the system. At the same time, the user identity management and verification process complies with the best practices of data protection and ensures the security of user information.

[0101] In one embodiment of the present application, the permissions include: administrator, core developer, and ordinary developer.

[0102] Specifically, administrators can add, delete, and modify user information, and assign or adjust user roles. Administrators can create new user accounts, modify the permissions of existing users, or delete user accounts that are no longer needed. Administrators can view, modify, and delete all test tasks. Administrators can manually start, pause, or terminate test tasks, and view the execution results of all tasks. Administrators can adjust the system configuration, such as platform parameter settings, test mode definitions, etc. These operations ensure that the platform can be flexibly configured according to actual needs.

[0103] Core developers can create, modify, and delete test tasks related to themselves. Core developers can execute and schedule test tasks, and view the execution status and test results of tasks. Core developers have the right to jump in the task queue, and can insert the test tasks they submit into the priority position of the task queue to ensure that urgent tasks are processed first.

[0104] Ordinary developers can submit test tasks through the client, but cannot modify other tasks in the task queue. Ordinary developers can only submit and view tasks related to themselves, and cannot jump the queue or modify the priority of tasks. Ordinary developers can view the execution status and results of tasks submitted by themselves, but cannot view the test task data of other users.

[0105] By adopting the above technical solution, the permission management system can ensure that users of different roles obtain corresponding operation permissions according to their responsibilities. Administrators can fully control the system, core developers can flexibly manage test tasks and jump the queue in emergency situations, while ordinary developers can only perform basic operations such as task submission and status viewing. Through precise permission allocation and control, the system can effectively protect the security of user data, ensure the standardization of operations and the stable operation of the system. At the same time, this permission management mechanism enables the platform to flexibly adapt to different user needs and improve the maintainability and scalability of the system.

[0106] like Figure 2 As shown, the present application also discloses a plasma control system testing method, comprising the following steps: S1. The user submits a single task form configuration and / or batch task file through the client; S2. The server verifies permissions and schedules tasks to the queue; S3. The multi-modal actuator dynamically adjusts the PCS operating parameters according to the task configuration; S4. The status monitor collects PCS health data in real time and pushes it to the client; S5. The document generation module processes the test results and generates visual charts and automated reports.

[0107] Specifically, users manually fill in various parameters of the test task through a graphical interface, such as test type, test mode, required equipment, etc. After completing the filling, the client packages these configuration parameters into a JSON format data file and submits it to the server. Users can also choose to upload task configuration files in batches. Each line in the file defines a complete set of test task configurations. The client will perform format verification on these files to ensure that the task format meets the requirements, and convert each task configuration item into JSON format and upload it to the server for processing.

[0108] After receiving the task data submitted by the client, the identity verification module on the server side first verifies the identity of the submitting user. Based on the user's role in the system (such as administrator, core developer, or ordinary developer), the identity verification module determines whether the user has the authority to submit tasks and perform related operations. After the identity verification is passed, the task upload module will parse the task data and transmit it to the task queue scheduler. The task queue scheduler will determine the insertion position of the task in the queue based on the priority of the task (set by the user when submitting). If the task is a privileged task, it may be inserted to the head of the queue, while regular tasks are queued in the order of submission.

[0109] The multi-mode executor obtains the task to be executed from the task queue and reads the specific configuration of the task. According to the configuration of the task, the multi-mode executor will dynamically adjust the operating parameters of the PCS (plasma control system). These parameters may include test mode, hardware configuration, simulation control parameters, etc. If the task is configured as scene playback mode, the executor will adjust the PCS configuration file to mode, start the PCS process to replay historical experimental data; if the task is configured as simulation test mode, the executor will adjust the PCS configuration file to mode, and start the PCS and PCS-VP processes for simulation testing and data collection.

[0110] The status monitor module on the server side obtains the health status of the PCS in real time by subscribing to the PCS health information published by the open source distributed control system framework. This data includes system operation status, hardware health status, connection status, etc. Once the health data is collected, the status monitor integrates this information and pushes it to the client via WebSocket. The client will receive the real-time updated PCS health data and refresh the interface. Users can view the system status in real time on the client interface to ensure the stability of the test.

[0111] After the test task is completed, the document generation module will process the generated test results, including obtaining experimental data and analysis result summaries from the database. The document generation module generates relevant visualization charts based on the analysis results, such as flat-top segment waveform charts, boundary offset charts, etc. The charts will show the time changes of the test data, key performance indicators, etc. By calling the general large language model, the document generation module will automatically generate a test report based on the test results and analysis summary. The report includes a description of the test process, result analysis, chart display, etc., and the report format is a structured document, which is convenient for users to view, archive and share.

[0112] By adopting the above technical solutions, the plasma control system test method can fully cover all aspects from task submission, authority verification, task execution, status monitoring to result processing. By dynamically adjusting the PCS operating parameters, the system can flexibly respond to different test requirements; through real-time health data collection and push, users can grasp the system status in real time to ensure the stability and reliability of the test; the document generation module can greatly improve work efficiency and reduce manual operation errors by automatically generating test reports and visual charts. The implementation of this test method makes the test process more efficient and accurate, and provides powerful tool support for developers.

[0113] The present application also discloses a computer-readable storage medium storing a computer program, which implements the steps of the above method when executed by a processor.

[0114] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A plasma control system test platform, characterized in that: include: The client is provided with a task submission module and an interactive visualization module, wherein the task submission module is used to support single task form configuration and / or batch task file upload; The server is provided with a task upload module, a task queue scheduler, a multi-modal executor, and a data analysis module; the task upload module is used to receive tasks uploaded by the client, and send the tasks to the task queue scheduler after parsing, and the task queue scheduler queues or queues the uploaded tasks according to the priority; The multimodal executor is connected to the PCS and the PCS-VP. The multimodal executor obtains the head task of the task queue and starts the PCS process to execute the task or starts the PCS and PCS-VP processes to execute the task at the same time according to the task mode. After the task is executed, the data analysis module obtains the original execution data, processes the data, and feeds it back to the client interactive visualization module.

2. The plasma control system test platform according to claim 1, characterized in that: The uploaded tasks are queued or inserted into a queue according to their priority, including: The task queue scheduler obtains the task priority and determines whether the current priority is a privileged task. If it is a privileged task, it checks whether there are unfinished privileged tasks in the current queue. If there are unfinished privileged tasks, the new privileged task is inserted after the most recent privileged task. If there are no unfinished privileged tasks, the new privileged task is inserted at the head of the queue. If it is not a privileged task, the task will be inserted at the end of the queue. After the task is executed, the task at the head of the queue will be deleted and the database status field will be updated.

3. The plasma control system test platform according to claim 1, characterized in that: The task modes include: scene playback mode and simulation test mode; When the multi-modal actuator determines that the mode is the scene playback mode, modify the PCS configuration file to mode, start the PCS process, call the analog central control system module to generate a hardware trigger signal, and the signal outputs a high-level pulse through the NII / O card; When the multi-mode actuator determines that the mode is the simulation test mode, modify the PCS configuration file to mode, start the PCS and PCS-VP processes; transmit the control signal to PCS-VP through the shared memory, receive the analog acquisition signal and transmit it back to PCS to form a closed loop.

4. The plasma control system test platform according to claim 1, characterized in that: After data processing, it is fed back to the client interactive visualization module, including: The data analysis module reads the experimental gun data and the historical reference gun data from the database storing the original execution data, identifies the flat-top segments in the experimental gun data and the historical reference gun data, performs flat-top segment waveform analysis and boundary offset Euclidean distance calculation, stores the intermediate results as target format files, records the path in the database test gun table, and feeds back the analysis results to the client's interactive visualization module, which displays visualization charts.

5. The plasma control system test platform according to claim 4, characterized in that: The client is also provided with a document generation module, which obtains the path of the interactive visualization module to display the visualization chart, the analysis result summary, and the custom annotations, calls the general large language model to integrate the visualization chart, the analysis result summary, and the custom annotations to generate a structured document.

6. The plasma control system test platform according to claim 1, characterized in that: The server is also provided with a status monitor module, which subscribes to the PCS health information released by the open source distributed control system framework, integrates the platform's own operating status, pushes the integrated status data to the client via WebSocket, and triggers the client interface to refresh in real time.

7. The plasma control system test platform according to claim 1, characterized in that: The client is provided with an identity authentication module, and the server is provided with an identity verification module. The identity verification module receives the identity data of the identity authentication module. When the identity data is for a new user registration, the identity data is stored and the registration result is fed back; when the identity data is historical data, the identity data is compared with its own database and corresponding permissions are distributed.

8. The plasma control system test platform according to claim 7, characterized in that: The permissions include: administrator, core developer and general developer.

9. A plasma control system testing method, characterized in that: The following steps are involved: S1. The user submits a single task form configuration and / or batch task file through the client; S2. The server verifies permissions and schedules tasks to the queue; S3. The multi-modal actuator dynamically adjusts the PCS operating parameters according to the task configuration; S4. The status monitor collects PCS health data in real time and pushes it to the client; S5. The document generation module processes the test results and generates visual charts and automated reports.

10. A computer-readable storage medium storing a computer program, characterized in that: When the program is executed by a processor, the steps of the method according to claim 9 are implemented.

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