A multi-fault collaborative remote control system and method for power equipment

Abstract

This invention discloses a collaborative remote control system and method for multiple faults in power equipment, relating to the field of remote control technology. The system includes: a remote control terminal connected to a power operation system; data acquisition from multiple power devices via multiple edge nodes to obtain multiple device operation datasets; fault identification of the multiple device operation datasets to obtain fault operation data; integrated fault analysis of the first fault operation data and the second fault operation data to output integrated fault information; and control of the first and second faulted devices by the remote control terminal based on the integrated fault information. This invention solves the technical problem of low processing efficiency caused by the lack of correlation analysis and collaborative mechanisms in the prior art for handling multiple faults in power equipment, achieving collaborative remote processing of multiple faulted power equipment and improving the correlation and efficiency of power equipment fault handling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of remote control, and particularly relates to a multi-fault cooperative remote control system and method of power equipment. BACKGROUND

[0002] In a large-scale power network, the number of power equipment is large and the distribution is wide, and the occurrence of faults has randomness and uncertainty. In the past, when the power equipment appeared faults, often due to incomplete information collection, inaccurate fault diagnosis, and at the same time, for the near neighbor fault equipment with correlation, the traditional method is difficult to quickly and accurately identify and analyze the mutual relationship, cannot realize effective integrated control, and causes poor control effect.

[0003] The prior art has the technical problem of low processing efficiency due to lack of correlation analysis and cooperative mechanism for multi-fault processing of power equipment. SUMMARY

[0004] The present application provides a multi-fault cooperative remote control system and method of power equipment, which is used to solve the technical problem of low processing efficiency due to lack of correlation analysis and cooperative mechanism for multi-fault processing of power equipment in the prior art.

[0005] In view of the above problems, the present application provides a multi-fault cooperative remote control system and method of power equipment.

[0006] In a first aspect of the present application, a multi-fault cooperative remote control system of power equipment, the system comprises:

[0007] The remote control terminal is connected with a power operation system, and the power operation system includes a plurality of power equipment, wherein the plurality of power equipment includes a plurality of edge nodes; an operation data set acquisition module is configured to acquire a plurality of device operation data sets by collecting data of the plurality of power equipment according to the plurality of edge nodes; a fault operation data acquisition module is configured to acquire a first fault device and first fault operation data corresponding to the first fault device by identifying faults of the plurality of device operation data sets; an integrated fault information output module is configured to, if the remote control terminal receives the first fault device and the first fault operation data at the same time, receive a second fault device and second fault operation data corresponding to the second fault device, perform integrated fault analysis on the first fault operation data and the second fault operation data, and output integrated fault information, wherein the second fault device is a near-neighbor fault device of the first fault device; and a device control module is configured to control the first fault device and the second fault device according to the integrated fault information by the remote control terminal.

[0008] In a second aspect of the present application, a multi-fault cooperative remote control method of power equipment is provided, and the method includes:

[0009] The remote control terminal is connected with a power operation system, and the power operation system includes a plurality of power equipment, wherein the plurality of power equipment includes a plurality of edge nodes; an operation data set acquisition module is configured to acquire a plurality of device operation data sets by collecting data of the plurality of power equipment according to the plurality of edge nodes; a fault operation data acquisition module is configured to acquire a first fault device and first fault operation data corresponding to the first fault device by identifying faults of the plurality of device operation data sets; an integrated fault information output module is configured to, if the remote control terminal receives the first fault device and the first fault operation data at the same time, receive a second fault device and second fault operation data corresponding to the second fault device, perform integrated fault analysis on the first fault operation data and the second fault operation data, and output integrated fault information, wherein the second fault device is a near-neighbor fault device of the first fault device; and a device control module is configured to control the first fault device and the second fault device according to the integrated fault information by the remote control terminal.

[0010] The one or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0011] A remote control terminal connects to the power operation system and collects data from multiple power devices via multiple edge nodes, acquiring multiple device operation datasets. It then identifies faults in these datasets, obtaining a first faulty device and its corresponding first fault operation data. If the remote control terminal receives a second faulty device and its corresponding second fault operation data simultaneously, it performs integrated fault analysis on both datasets, outputting integrated fault information. Based on this integrated fault information, the remote control terminal controls both the first and second faulty devices. This achieves the technical effect of enabling collaborative remote processing of multiple faulty power devices, improving the correlation and efficiency of power device fault handling. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the structure of a multi-fault collaborative remote control system for power equipment provided in an embodiment of this application;

[0014] Figure 2 This is a flowchart illustrating a multi-fault collaborative remote control method for power equipment provided in an embodiment of this application.

[0015] Explanation of reference numerals in the attached diagram: Remote control terminal connection module 10, running dataset acquisition module 20, fault running data acquisition module 30, integrated fault information output module 40, and equipment control module 50. Detailed Implementation

[0016] This application provides a collaborative remote control system and method for multiple faults in power equipment, which addresses the technical problem of low processing efficiency caused by the lack of correlation analysis and collaborative mechanisms in the handling of multiple faults in power equipment in the prior art.

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] Example 1, as Figure 1As shown, this application provides a multi-fault collaborative remote control system for power equipment, the system comprising:

[0019] The remote control terminal connection module 10 is used to connect the remote control terminal to the power operation system, which includes multiple power devices, including multiple edge nodes.

[0020] Specifically, the main function of the remote control terminal connection module 10 is to establish a communication link between the remote control terminal and the power operation system. Through this module, the remote control terminal can interact with the power operation system and transmit commands. The power operation system consists of multiple power devices, each performing different functions to ensure the normal supply and operation of power. Among these devices are multiple edge nodes, which are devices distributed at the edge of the power system. These edge nodes can collect and process local power data in real time and upload this data to the central control system. They can also receive commands from the central control system to control the local power devices. This allows the remote control terminal to connect to the power operation system, thereby enabling remote monitoring of the power devices, real-time acquisition of their operating status and data, and improved control efficiency.

[0021] Run the dataset acquisition module 20, which is used to collect data from the multiple power devices based on the multiple edge nodes and acquire multiple device operation datasets.

[0022] Specifically, the operational dataset acquisition module 20 is a crucial component of the system responsible for collecting operational data from power equipment. Its main function is to utilize multiple edge nodes to collect real-time data from various power devices. These edge nodes are distributed throughout the power system, enabling them to access and acquire operational data from the equipment. These edge nodes can collect various types of data, such as parameters like voltage, current, power, temperature, and humidity, as well as the equipment's operating status and fault information. Through the collaborative work of multiple edge nodes, comprehensive and timely operational data from multiple power devices can be obtained. This data is then integrated to form multiple operational datasets. Each dataset contains detailed operational information for a specific power device over a given period. For example, an operational dataset might contain hourly voltage and current data for a transformer throughout the day, along with information on whether it experienced any faults during that period. This method of acquiring operational datasets provides essential foundational data for subsequent fault diagnosis, data analysis, and decision-making, helping the system better monitor and manage the operational status of power equipment and improve control efficiency.

[0023] The fault operation data acquisition module 30 is used to identify faults in the multiple device operation datasets and acquire a first faulty device and the first faulty operation data corresponding to the first faulty device.

[0024] Specifically, the fault operation data acquisition module 30 is responsible for identifying fault information from multiple equipment operation datasets. Its working principle involves in-depth analysis and processing of multiple equipment operation datasets collected from multiple edge nodes. This module receives a large amount of equipment operation data provided by the operation dataset acquisition module 20. This data includes various operating parameters of each power device at different times, such as voltage, current, power, temperature, and frequency. The module uses a fault identification algorithm based on neural networks. Neural networks are machine learning algorithms that can automatically extract features and patterns from large amounts of data, and perform classification and prediction. In power equipment fault identification, neural networks can be used to analyze equipment operation data to identify fault patterns. During the identification process, the module closely monitors abnormal patterns and trends in the data. If it detects sudden fluctuations, abnormal peaks, or continuous deviations from the normal range in the operating data of a certain device, it determines that the device is faulty. Once the first faulty device is identified, the module quickly extracts all fault operation data related to that device. This data includes the specific time of the fault, changes in the device's operating parameters before and after the fault, characteristic manifestations of the fault (such as abnormal noises, smoke, etc.), and other relevant information. By acquiring this detailed operational data of the first fault, the system can more accurately understand the nature and severity of the fault, providing strong support for subsequent fault diagnosis, analysis and handling, thereby enabling timely and effective measures to repair faulty equipment and improve control efficiency.

[0025] An integrated fault information output module 40 is used to perform integrated fault analysis on the first fault operation data and the second fault operation data when the remote control terminal receives the first fault device and the first fault operation data, and outputs integrated fault information, wherein the second fault device is a neighboring fault device of the first fault device.

[0026] Specifically, the integrated fault information output module 40 is a crucial module in this system for comprehensively analyzing fault information. This module activates when the remote control terminal simultaneously receives data from the first faulty device and its corresponding first fault operation data, as well as data from the second faulty device and its corresponding second fault operation data. Here, the second faulty device is defined as a neighboring faulty device of the first faulty device, meaning they are relatively close in location within the power system or have a functional connection. For example, they might be adjacent devices in the same substation or adjacent devices on the power transmission path. After receiving this data, the module performs integrated fault analysis on the first and second fault operation data. This analysis process includes comprehensive consideration of the fault time, fault type, and fault severity of the two faulty devices. For example, it analyzes whether the two faults occurred simultaneously, whether they were caused by the same reason, or whether one fault would affect the development of the other. Through this integrated fault analysis, the module can output integrated fault information, including a comprehensive assessment of the two faulty devices, such as their impact on the overall power system operation, whether simultaneous maintenance or other measures are needed, etc. By comprehensively analyzing the fault operation data of nearby faulty equipment, more comprehensive and accurate fault information is provided, which helps to improve the efficiency and reliability of fault handling.

[0027] The device control module 50 is used by the remote control terminal to control the first faulty device and the second faulty device according to the integrated fault information.

[0028] Specifically, the equipment control module 50 is a key component in the entire system responsible for the actual control of faulty equipment. When the remote control terminal receives integrated fault information, the equipment control module 50 determines the control measures to be taken for the first and second faulty devices based on this information. The equipment control module 50 parses the integrated fault information to understand the specific situation of the faulty devices, including the type, severity, and impact on the system, and formulates corresponding control strategies based on this information. For example, if the integrated fault information indicates that the first faulty device is a generator experiencing an overload fault, and the second faulty device is a related power distribution device experiencing a short circuit fault, the equipment control module 50 will take the following control measures: immediately stop the generator's operation to avoid further damage; simultaneously, disconnect the power distribution device to prevent the short circuit fault from escalating its impact. Furthermore, the equipment control module 50 can also adjust the operating status of other related equipment based on the integrated fault information to ensure the stable operation of the power system. For example, it can adjust the output power of other generators to compensate for the power shortage caused by the shutdown of the faulty generator. When implementing control measures, the equipment control module 50 communicates with the remote control terminal and sends control commands to the corresponding devices. These devices will perform corresponding operations according to instructions, such as stopping, disconnecting, and adjusting parameters. Through the device control module 50, the remote control terminal can control the faulty equipment in a timely and effective manner.

[0029] In one possible implementation, the integrated fault information output module 40 further includes:

[0030] If the remote control terminal receives the first faulty device and the first fault operation data, the second faulty device and the second fault operation data corresponding to the second faulty device, and simultaneously receives the third faulty device and the third fault operation data corresponding to the third faulty device, it performs integrated fault analysis on the first fault operation data, the second fault operation data and the three fault operation data, and outputs integrated fault information; wherein, the third faulty device is a neighboring faulty device of the first faulty device or the second faulty device.

[0031] Specifically, during power system operation, when a remote control terminal simultaneously receives data from a first faulty device and its corresponding first fault operation data, a second faulty device and its corresponding second fault operation data, and then receives data from a third faulty device and its corresponding third fault operation data, the remote control terminal will activate the integrated fault analysis function. The remote control terminal will conduct in-depth analysis of the first, second, and third fault operation data, carefully studying various parameters within these data, including the time of the fault occurrence, the specific symptoms of the faulty device, and changes in the operating status of related equipment. Simultaneously, considering that the third faulty device is a neighboring device to the first or second faulty device, the terminal will pay particular attention to their spatial relationships and functional connections. By comprehensively considering these factors, the remote control terminal can perform a comprehensive integrated fault analysis and output detailed integrated fault information. This information includes individual analysis results for each faulty device, a description of the connections between faulty devices, and a comprehensive assessment of the entire fault event. Such integrated fault information helps to more accurately understand the nature and scope of the fault, thereby enabling the development of more effective repair and response strategies to ensure the stable operation of the power system.

[0032] In one possible implementation, the integrated fault information output module 40 further includes:

[0033] If the remote control terminal receives the first faulty device and the first fault operation data at the same time as receiving the second faulty device and the second fault operation data corresponding to the second faulty device, it performs independent fault analysis on the first fault operation data and the second fault operation data respectively, and outputs the first fault information and the second fault information; wherein, the second faulty device is a non-nearby faulty device of the first faulty device.

[0034] Specifically, during power system operation, when a remote control terminal receives a first faulty device and its corresponding first fault operation data, if it also receives a second faulty device and its corresponding second fault operation data simultaneously, and the second faulty device is not a neighboring device of the first faulty device, the remote control terminal will perform the following operations: independently analyze the first and second fault operation data. For the first fault operation data, the terminal will study in detail the various parameters and indicators to determine the fault type, severity, and possible causes of the first faulty device. Similarly, a similar analysis will be performed on the second fault operation data to obtain relevant fault information for the second faulty device. After completing the independent fault analysis, the remote control terminal will output first and second fault information. The first fault information will include detailed analysis results about the first faulty device, such as a specific description of the fault, the possible scope of impact, and suggested handling measures. The second fault information will correspondingly include relevant information about the second faulty device. In this way, even if the first and second faulty devices are not spatially adjacent, the remote control terminal can process and analyze their faults separately, providing accurate basis for subsequent fault repair and system maintenance.

[0035] In one possible implementation, the integrated fault information output module 40 further includes:

[0036] The connection relationships between the multiple power devices in the power operation system are analyzed to obtain a power operation network, wherein each network node in the power operation network is composed of various power devices; based on the power operation network, a first adjacency matrix corresponding to the first faulty device is obtained, wherein the first adjacency matrix is ​​identified by elements 0 and 1; based on the first adjacency matrix, the second faulty device is judged. If the return value is 0, the second faulty device is a non-nearest neighbor faulty device of the first faulty device; if the return value is 1, the second faulty device is a near neighbor faulty device of the first faulty device.

[0037] Specifically, in a power system, obtaining the power operation network first requires a comprehensive and in-depth analysis of the connections between various power devices. This involves collecting detailed information about the power devices, including their type (e.g., transformers, circuit breakers, generators), location, specifications, and physical and communication connections. The connections are then clearly defined, clarifying the direct or indirect connections between each power device and other devices. This includes connections via transmission lines, busbars, communication lines, etc. Each individual power device is designated as a node in the power operation network; for example, a specific transformer, generator, or circuit breaker is defined as a node. Through this comprehensive analysis, a power operation network is constructed, in which each power device is considered an independent network node.

[0038] Once the established power operation network is in place, the next step to more accurately study the connectivity of the first faulty device within this network is to obtain its corresponding first adjacency matrix. The power operation network can be viewed as a complex graph, where each power device is a node. Obtaining the first adjacency matrix specifically involves determining the connectivity of the device marked as the first faulty device with all other device nodes. In practice, each device in the network except the first faulty device is checked sequentially. If the first faulty device has a direct connection path with any other device, a 1 is entered in the corresponding position in the first adjacency matrix; otherwise, a 0 is entered. The first adjacency matrix obtained in this way, composed only of simple and intuitive 0s and 1s, clearly reflects the direct connectivity of the first faulty device within the entire power operation network. This provides crucial and fundamental information for subsequent in-depth analysis of the fault's impact range, propagation path, and the development of corresponding repair strategies.

[0039] The algorithm searches for the position corresponding to the second faulty device in the first adjacency matrix. If the return value at this position is 0, it means that there is no direct connection between the second and first faulty devices, thus determining that the second faulty device is a non-nearest neighbor of the first faulty device. Conversely, if the return value is 1, it indicates that there is a direct connection between the second and first faulty devices, making the second faulty device a near neighbor of the first faulty device. This method of determining the proximity relationship between faulty devices through the values ​​of the adjacency matrix quickly identifies nearby faulty devices, helps to concentrate resources on processing them, avoids unnecessary attention to non-nearest faulty devices, and thus improves the overall efficiency of fault handling.

[0040] In one possible implementation, the device control module 50 further includes:

[0041] Based on the integrated fault information, the control task is decomposed to obtain the first control task corresponding to the first faulty device and the second control task corresponding to the second faulty device.

[0042] Identify the first edge device and the second edge device corresponding to the first faulty device and the second faulty device, respectively; send the first control task and the second control task to the first edge device and the second edge device, and have the first edge device and the second edge device control the first faulty device and the second faulty device.

[0043] Specifically, once integrated fault information is available, it is analyzed and decomposed in depth. Integrated fault information typically contains complex details and relevant parameters about multiple faulty devices. By studying this information, the required control measures and operations for each faulty device are identified. For the first faulty device, based on its fault type, severity, and system environment, specific and clear control tasks are extracted from the overall control requirements; this is the first control task. Similarly, for the second faulty device, a similar approach is used, comprehensively considering its various fault characteristics and system requirements to extract appropriate control tasks; this is the second control task. For example, if the first faulty device is an overloaded motor, the first control task might be to reduce its load or adjust its operating frequency; while if the second faulty device is a controller with excessively high temperatures, the second control task might be to start the cooling fan or reduce its operating power. This precise decomposition of control tasks provides clear guidance and direction for subsequent targeted solutions to the problems of each faulty device.

[0044] In power systems, once the first and second faulty devices are identified, corresponding edge devices are determined based on a series of rules and information. First, the physical connections and logical control relationships between devices are understood using the power system architecture diagram and device connection table. For the first faulty device, candidate edge devices with control functions are selected from its directly connected devices. These candidates include intelligent controllers, monitoring and control terminals, and protection devices. Then, based on the type of the first faulty device, the specific manifestation of the fault, and the required control operations, the functions and permissions of these candidate edge devices are further evaluated. For example, if the first faulty device is a high-voltage circuit breaker that cannot open or close normally, then a specific monitoring and control terminal that can directly send control signals to operate the circuit breaker will be identified as the first edge device. The same method is used to determine the second edge device corresponding to the second faulty device. The characteristics and control requirements of the second faulty device are comprehensively considered, and the devices with control capabilities directly connected to it are screened and evaluated. For example, if the second faulty device is a power capacitor bank experiencing a compensation problem, then a reactive power compensation controller that can adjust the switching status of the capacitor bank may be identified as the second edge device. During the selection process, factors such as the device's communication capabilities, real-time response performance, and compatibility with the entire system are also considered to ensure that the identified edge devices can accurately, promptly, and effectively control and manage the faulty device. Through this comprehensive and meticulous analysis and screening, the first edge device for the first faulty device can be accurately located, and the second edge device for the second faulty device can be located, providing strong support for subsequent fault handling and system recovery.

[0045] After the control tasks are broken down and the corresponding edge devices for the faulty devices are identified, the system enters the control task distribution and execution phase. The system accurately transmits the first control task for the first faulty device to the first edge device and the second control task for the second faulty device to the second edge device through specific communication channels and protocols. These communication channels include wired networks (such as Ethernet) and wireless networks (such as Wi-Fi or dedicated wireless communication frequency bands). The communication protocols ensure the integrity, accuracy, and timeliness of the control task information. Upon receiving the first control task, the first edge device performs corresponding operations on the first faulty device according to its own control logic and functions. For example, if the first control task is to adjust the operating parameters of the first faulty device, the first edge device will send control commands to change its voltage, current, or frequency. Similarly, upon receiving the second control task, the second edge device will immediately take corresponding control actions on the second faulty device. Throughout the process, the first and second edge devices act as direct executors, precisely controlling the first and second faulty devices according to the received control tasks to eliminate faults, restore normal equipment operation, or stabilize the system.

[0046] In one possible implementation, the integrated fault information output module 40 further includes:

[0047] The first fault operation data and the second fault operation data are analyzed to obtain first fault information and second fault information; the first fault operation data and the second fault operation data are fused to output fused fault operation data; third fault information is obtained based on the fused fault operation data; integrated fault analysis is performed using the first fault information, the second fault information and the third fault information to output integrated fault information.

[0048] Specifically, when dealing with first-fault and second-fault operating data, in-depth analysis is conducted on the various parameters contained therein to obtain corresponding fault information. For first-fault operating data: fault type, through an overall assessment of the equipment's operating status and specific fault characteristic identifiers, the approximate category of the fault is determined, such as short circuit, open circuit, or overload; fault time, accurately recording the moment the fault occurred, which is crucial for tracing the sequence of fault occurrences and their correlation with other events; voltage fluctuation amplitude, if the voltage fluctuation amplitude is too large and exceeds the normal fluctuation range, it may indicate power supply problems, circuit component failure, or sudden load changes; current change rate, a rapid current change rate may indicate a short circuit in the circuit or component damage, while a slow, continuous change may be related to equipment aging or a gradually increasing load; temperature change rate, a significant temperature rise may be due to overload, poor heat dissipation, or localized overheating caused by an internal short circuit in a component. Vibration frequency: Abnormal vibration frequency may indicate wear, imbalance, or loosening of mechanical components. Fault cause: Considering the above parameters, the equipment's operating environment, and service life, the root cause of the potential fault can be deduced. For example, if there are large voltage fluctuations, rapid current changes, and a sharp temperature rise, and the fault type is a short circuit, the possible cause is the breakdown of a critical component. The same analytical method is used for the second fault operating data. Through detailed analysis of the first and second fault operating data, accurate information about both faults can be obtained, providing strong support for subsequent fault handling and prevention.

[0049] The specific parameters and their value ranges contained in the first and second fault operation data are clearly defined. Assuming the first fault operation data includes parameters such as voltage, current, and equipment temperature, while the second fault operation data includes parameters such as power, frequency, and humidity, a corresponding weight is assigned to each parameter. This weighting can be based on various factors, such as the parameter's importance to fault diagnosis, its influence in historical data, or expert judgment. Each parameter is then weighted according to its assigned weight. Performing this weighted calculation on all data sampling points yields a series of fused values. These fused values ​​together constitute the fused fault operation data. This data fusion method comprehensively considers fault operation data from different sources, providing a more complete reflection of the equipment's fault status.

[0050] After obtaining the fused fault operation data, a moving average method is used. This assumes the fused fault operation data includes parameters such as equipment vibration amplitude, temperature, and operating speed, and that this data is collected chronologically. First, an appropriate moving average window size is selected, such as 5 data points. Then, for vibration amplitude data, the average of each data point and its four preceding data points is calculated sequentially, resulting in a series of moving averages. The trend of these moving averages is observed. If a previously relatively stable moving average suddenly begins to rise continuously and exceeds the normal fluctuation range, this indicates a new fault. For example, for temperature data, if the moving average initially rises slowly but then begins to rise sharply at a certain point, it means that a new problem has occurred in the equipment's heat dissipation system, leading to an uncontrolled temperature increase. By comprehensively analyzing the abnormal changes in the moving averages of parameters such as vibration amplitude, temperature, and operating speed, previously undetected third-party fault information can be obtained, such as the gradual failure of a critical component, new wear or lubrication problems, etc.

[0051] During integrated fault analysis, information on the first, second, and third faults is summarized and organized. This information includes detailed details such as the specific location of the fault, its manifestation, the time sequence of occurrence, and its impact on equipment performance. Then, a correlation analysis is performed on this information to examine whether there are causal relationships, mutual influences, or joint causes leading to more severe system failures among the different faults. For example, the first fault might be the damage to a component, the second fault might be the resulting abnormality in related system parameters, and the third fault might be a secondary failure of other components caused by the combined effect of the first two faults. Next, the severity of each fault is comprehensively assessed. This involves a quantitative or qualitative evaluation of the impact on equipment safety, production efficiency, maintenance costs, and other aspects. Based on this, a fault model is established using a decision tree algorithm, suitable for fault diagnosis and analysis. A large dataset containing information on the first, second, and third faults, along with corresponding actual fault results, is collected. This data includes parameters such as equipment temperature, pressure, vibration, and current, as well as the final fault type (e.g., short circuit, open circuit, wear). This data is then used to train the decision tree model. The decision tree automatically generates a series of judgment rules based on the characteristics and categories of this data, forming a tree-like structure. For example, in a fault model for electrical equipment, if the temperature exceeds a certain threshold, the decision tree will continue to judge whether the current is also abnormal along the "overheating" branch. If so, it will be judged as a serious fault; otherwise, it is a minor problem. When new fault information is input, the decision tree will reason and judge according to the previously learned rules, ultimately outputting the predicted fault result. Finally, the output integrated fault information includes a comprehensive description of the entire fault situation, clearly identifying major and minor faults, indicating the interrelationships between faults, assessing the overall impact of the fault on the system, proposing possible fault propagation paths and potential risk points, and providing corresponding maintenance suggestions and preventative measures.

[0052] In one possible implementation, the integrated fault information output module 40 further includes:

[0053] If the remote control terminal receives the first faulty device and the first fault operation data, it predicts the first response time; based on the first response time, events that receive the faulty device and the fault operation data within the first response time period are determined to be simultaneous events.

[0054] Specifically, when the remote control terminal receives the first faulty device and its corresponding first fault operation data, it immediately initiates a response time prediction mechanism. This prediction process comprehensively considers various factors, such as the type and complexity of the fault, the processing time of similar historical faults, and the current system load and available resources. The predicted first response time becomes a crucial time reference. Subsequently, if the remote control terminal continues to receive new faulty devices and their corresponding fault operation data, the system will uniformly classify fault events received within the first response time as occurring simultaneously. For example, suppose the first response time is predicted to be 30 minutes. If a second faulty device and its data are received within 10 minutes of the first faulty device and data, and a third faulty device and its data are received at 25 minutes, then the events of the second and third faulty devices will be considered to have occurred simultaneously with the first faulty device. This determination method is significant because, from a fault diagnosis perspective, simultaneously occurring faults are related, which helps in a more comprehensive analysis of the fault's cause. In practical applications, this determination method can adapt to complex and ever-changing power equipment fault scenarios. For example, during peak power grid periods, multiple devices may fail in succession. Through such judgment and handling, information can be quickly integrated to make accurate and efficient response decisions.

[0055] Example 2, based on the same inventive concept as the multi-fault collaborative remote control system for power equipment in the foregoing examples, such as... Figure 2 As shown, this application provides a method for multi-fault collaborative remote control of power equipment. The method and system embodiments in this application are based on the same inventive concept. The method includes:

[0056] Step S100: The remote control terminal connects to the power operation system, which includes multiple power devices, including multiple edge nodes.

[0057] Step S200: Collect data from the multiple power devices based on the multiple edge nodes to obtain multiple device operation datasets.

[0058] Step S300: By performing fault identification on the multiple device operation datasets, obtain the first faulty device and the first faulty operation data corresponding to the first faulty device.

[0059] Step S400: If the remote control terminal receives the first faulty device and the first faulty operation data at the same time, it also receives the second faulty device and the second faulty operation data corresponding to the second faulty device, performs integrated fault analysis on the first faulty operation data and the second faulty operation data, and outputs integrated fault information, wherein the second faulty device is a neighboring faulty device of the first faulty device.

[0060] Step S500: The remote control terminal controls the first faulty device and the second faulty device according to the integrated fault information.

[0061] Furthermore, step S400 also includes:

[0062] If the remote control terminal receives the first faulty device and the first fault operation data, the second faulty device and the second fault operation data corresponding to the second faulty device, and simultaneously receives the third faulty device and the third fault operation data corresponding to the third faulty device, it performs integrated fault analysis on the first fault operation data, the second fault operation data and the three fault operation data, and outputs integrated fault information; wherein, the third faulty device is a neighboring faulty device of the first faulty device or the second faulty device.

[0063] Furthermore, step S400 also includes:

[0064] If the remote control terminal receives the first faulty device and the first fault operation data at the same time as receiving the second faulty device and the second fault operation data corresponding to the second faulty device, it performs independent fault analysis on the first fault operation data and the second fault operation data respectively, and outputs the first fault information and the second fault information; wherein, the second faulty device is a non-nearby faulty device of the first faulty device.

[0065] Furthermore, step S400 also includes:

[0066] The connection relationships between the multiple power devices in the power operation system are analyzed to obtain a power operation network, wherein each network node in the power operation network is composed of various power devices; based on the power operation network, a first adjacency matrix corresponding to the first faulty device is obtained, wherein the first adjacency matrix is ​​identified by elements 0 and 1; based on the first adjacency matrix, the second faulty device is judged. If the return value is 0, the second faulty device is a non-nearest neighbor faulty device of the first faulty device; if the return value is 1, the second faulty device is a near neighbor faulty device of the first faulty device.

[0067] Furthermore, step S500 also includes:

[0068] Based on the integrated fault information, the control task is decomposed to obtain the first control task corresponding to the first faulty device and the second control task corresponding to the second faulty device; the first edge device and the second edge device corresponding to the first faulty device and the second faulty device are determined respectively; the first control task and the second control task are sent to the first edge device and the second edge device, and the first edge device and the second edge device control the first faulty device and the second faulty device.

[0069] Furthermore, step S400 also includes:

[0070] The first fault operation data and the second fault operation data are analyzed to obtain first fault information and second fault information; the first fault operation data and the second fault operation data are fused to output fused fault operation data; third fault information is obtained based on the fused fault operation data; integrated fault analysis is performed using the first fault information, the second fault information and the third fault information to output integrated fault information.

[0071] Furthermore, step S400 also includes:

[0072] If the remote control terminal receives the first faulty device and the first fault operation data, it predicts the first response time; based on the first response time, events that receive the faulty device and the fault operation data within the first response time period are determined to be simultaneous events.

[0073] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0074] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0075] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A multi-fault coordinated remote control system of power equipment, characterized in that, The system comprises: A remote control terminal connection module, which is used for connecting a remote control terminal with a power operation system, the power operation system comprising a plurality of power equipment, wherein the plurality of power equipment comprises a plurality of edge nodes; An operation data set acquisition module, which is used for collecting data of the plurality of power equipment according to the plurality of edge nodes, and acquiring a plurality of device operation data sets; A fault operation data acquisition module, which is used for acquiring a first fault device and first fault operation data corresponding to the first fault device by identifying faults from the plurality of device operation data sets; An integrated fault information output module, which is used for, if the remote control terminal receives the first fault device and the first fault operation data at the same time, receiving a second fault device and second fault operation data corresponding to the second fault device, performing integrated fault analysis on the first fault operation data and the second fault operation data, and outputting integrated fault information, wherein the second fault device is a near-neighbor fault device of the first fault device; A device control module, which is used for the remote control terminal to control the first fault device and the second fault device according to the integrated fault information, comprising: Performing control task decomposition according to the integrated fault information, acquiring a first control task corresponding to the first fault device and a second control task corresponding to the second fault device; Determining first edge equipment and second edge equipment corresponding to the first fault device and the second fault device, respectively; Downloading the first control task and the second control task to the first edge equipment and the second edge equipment, and controlling the first fault device and the second fault device by the first edge equipment and the second edge equipment; The integrated fault analysis on the first fault operation data and the second fault operation data to output integrated fault information comprises: Analyzing the first fault operation data and the second fault operation data to acquire first fault information and second fault information; Performing data fusion on the first fault operation data and the second fault operation data to output fused fault operation data; Acquiring third fault information according to the fused fault operation data; Performing integrated fault analysis on the first fault information, the second fault information, and the third fault information to output integrated fault information; If the remote control terminal receives the first fault device and the first fault operation data, predicting a first response time length; Taking the first response time length as a condition, determining an event of receiving a fault device and fault operation data within the first response time length as a simultaneous event; The integrated fault information output module further comprises: In the integrated fault analysis, the first fault information, the second fault information and the third fault information are summarized and arranged, and the fault information includes the specific position of the fault occurrence, the fault manifestation, the time sequence of the fault occurrence, and the influence degree on the equipment performance; The correlation analysis is performed on the fault information to check whether there is a causal relationship, mutual influence or common cause of more serious system failure between different faults; The fault model is established by a decision tree algorithm, a large amount of data set containing the first fault information, the second fault information and the third fault information and the corresponding actual fault result is collected, the decision tree model is trained using the data set, and the decision tree automatically generates a series of judgment rules according to the characteristics and categories of the data in the data set; When new fault information is input, the decision tree makes inference and judgment according to the rules learned before, and outputs the prediction result of the fault; The output integrated fault information includes a comprehensive description of the entire fault situation, clear major faults and minor faults, points out the mutual relationship between the faults, evaluates the overall influence of the faults on the system, proposes possible fault propagation paths and potential risk points, and gives corresponding maintenance suggestions and preventive measures.

2. The system of claim 1, wherein, If the remote control terminal receives the first fault device and the first fault running data, and the second fault device and the second fault running data corresponding to the second fault device at the same time, receives the third fault device and the third fault running data corresponding to the third fault device, performs integrated fault analysis on the first fault running data, the second fault running data and the third fault running data, and outputs integrated fault information; Wherein, the third fault device is a near neighbor fault device of the first fault device or the second fault device.

3. The system of claim 1, wherein, If the remote control terminal receives the first fault device and the first fault running data at the same time, receives the second fault device and the second fault running data corresponding to the second fault device, respectively performs independent fault analysis on the first fault running data and the second fault running data, and outputs first fault information and second fault information; Wherein, the second fault device is a non near neighbor fault device of the first fault device.

4. The system of claim 1, wherein, Judging whether the second fault device is a near neighbor fault device of the first fault device includes: Analyzing the connection relationship between the plurality of power devices in the power operation system to obtain a power operation network, wherein each network node in the power operation network is composed of each power device; According to the power operation network, a first adjacency matrix corresponding to the first fault device is obtained, wherein the first adjacency matrix is identified by elements 0 and 1; According to the first adjacency matrix, the second fault device is judged, if the return value is 0, the second fault device is a non near neighbor fault device of the first fault device, if the return value is 1, the second fault device is a near neighbor fault device of the first fault device.

5. A method of coordinated remote control of multiple faults of an electric power device, characterized by, The method is realized based on the system of any one of claims 1-4, comprising: A remote control terminal is connected with a power operation system, the power operation system comprising a plurality of power equipment, wherein the plurality of power equipment comprises a plurality of edge nodes; According to the plurality of edge nodes, data collection is performed on the plurality of power equipment to obtain a plurality of device operation data sets; Through fault identification on the plurality of device operation data sets, a first fault device and first fault operation data corresponding to the first fault device are obtained; If the remote control terminal receives the first fault device and the first fault operation data at the same time, receives a second fault device and second fault operation data corresponding to the second fault device, performs integrated fault analysis on the first fault operation data and the second fault operation data, and outputs integrated fault information, wherein the second fault device is a near-neighbor fault device of the first fault device; The remote control terminal controls the first fault device and the second fault device according to the integrated fault information.

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