Intelligent monitoring system and intelligent monitoring method for power equipment

Abstract

The invention discloses an intelligent monitoring system and method for power equipment, and the system comprises an infrared imaging module which is used for obtaining temperature distribution data corresponding to the power equipment, and transmitting the temperature distribution data to an edge calculation module; the edge calculation module is used for determining temperature characteristics of the power equipment based on the temperature distribution data, performing equipment state analysis on the power equipment based on the temperature characteristics to obtain equipment state analysis data and sending the equipment state analysis data to the data communication module; the data communication module is used for encrypting the equipment state analysis data to obtain equipment state encrypted data and uploading the equipment state encrypted data to the monitoring management platform based on wireless communication; and the monitoring management platform performs state display and / or fault early warning of the power equipment based on the equipment state encrypted data. The problems of response lag, data island and high labor cost of a traditional manual inspection monitoring method are solved, early recognition and timely early warning of faults are realized, and the operation safety and maintenance efficiency of equipment are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment monitoring, and in particular to an intelligent monitoring system and an intelligent monitoring method for power equipment. Background Art

[0002] The operating status of power equipment, especially key facilities such as transformers and distribution cabinets, directly affects the safety and stability of the power system. Traditional monitoring methods mostly rely on regular manual inspections and single monitoring methods, such as temperature measurement or visual inspection. These methods have the following shortcomings:

[0003] Delayed response: When there are many gaps between devices, regular inspections by operation and maintenance personnel alone cannot detect abnormal conditions of the equipment in a timely manner.

[0004] Data silos: Data from different monitoring methods are in different formats, making it difficult to integrate and comprehensively assess the health status of the equipment.

[0005] High labor costs: When there are a large number of devices, manual inspection work is arduous and prone to omissions. Summary of the invention

[0006] The present invention provides an intelligent monitoring system and an intelligent monitoring method for electric power equipment, which realize early identification and timely warning of faults by real-time monitoring and analysis of the temperature and appearance characteristics of electric power equipment, thereby improving the operating safety and maintenance efficiency of electric power equipment.

[0007] According to one aspect of the present invention, there is provided an intelligent monitoring system for electric power equipment, comprising: an infrared imaging module, an edge computing module, a data communication module and a monitoring management platform, wherein:

[0008] The infrared imaging module is used to obtain temperature distribution data corresponding to the power equipment and send the temperature distribution data to the edge computing module;

[0009] The edge computing module is used to determine the temperature characteristics of the power equipment based on the temperature distribution data, perform equipment status analysis on the power equipment based on the temperature characteristics, obtain equipment status analysis data, and send the equipment status analysis data to the data communication module;

[0010] The data communication module is used to encrypt the device status analysis data to obtain device status encrypted data, and upload the device status encrypted data to the monitoring management platform based on wireless communication;

[0011] The monitoring and management platform is used to display the status of the power equipment and / or provide fault warning based on the encrypted data of the equipment status.

[0012] In a possible implementation, the infrared imaging module includes: an infrared camera and an image preprocessing submodule, wherein:

[0013] The infrared camera is installed at a key position of the power equipment to capture the infrared thermal image of the surface of the power equipment in real time and send the infrared thermal image to the image preprocessing submodule;

[0014] The image preprocessing submodule is used to process the infrared thermal image based on mean filtering and histogram equalization to obtain a preprocessed image, and use the preprocessed image as the temperature distribution data.

[0015] In a possible implementation, the edge computing module includes: an edge computing unit, a data fusion unit, and a data processing unit, wherein:

[0016] The edge computing unit is used to extract temperature features according to the temperature distribution data to obtain the temperature features, and perform anomaly detection based on the temperature features and anomaly thresholds to obtain anomaly detection results;

[0017] The data fusion unit is used to perform fusion analysis based on the temperature characteristics and associated monitoring data to generate a comprehensive equipment status report;

[0018] The data processing unit is used to send the abnormality detection result and the device status report as the device status analysis data to the data communication module.

[0019] In a possible implementation manner, the data fusion unit is specifically configured to:

[0020] The temperature characteristics and associated monitoring data are input into a machine learning model to obtain the comprehensive equipment status report.

[0021] In a possible implementation, the data communication module includes: a data encryption submodule and a wireless communication submodule, wherein:

[0022] The data encryption submodule is used to encrypt the device status analysis data based on the AES encryption algorithm to obtain the device status encrypted data;

[0023] The wireless communication submodule is used to upload the encrypted data of the device status to the monitoring management platform via Wi-Fi or LoRa.

[0024] In a possible implementation, the monitoring management platform includes: a data decryption and processing submodule, a display submodule and an alarm notification submodule, wherein:

[0025] The data decryption and processing submodule is used to decrypt and analyze the encrypted data of the equipment status to determine the temperature distribution diagram, status information and historical data corresponding to the power equipment;

[0026] The display submodule is used to display the temperature distribution diagram, status information and historical data;

[0027] The alarm notification submodule is used to automatically send an early warning notification when the temperature of the power equipment is abnormal or a fault characteristic occurs. According to another aspect of the present invention, a method for intelligent monitoring of power equipment is provided, comprising:

[0028] Acquire temperature distribution data corresponding to the power equipment through the infrared imaging module, and send the temperature distribution data to the edge computing module;

[0029] Based on the temperature distribution data, determining the temperature characteristics of the power equipment through the edge computing module, performing device status analysis on the power equipment based on the temperature characteristics to obtain device status analysis data, and sending the device status analysis data to the data communication module;

[0030] Encrypting the device status analysis data through the data communication module to obtain device status encrypted data, and uploading the device status encrypted data to the monitoring management platform based on wireless communication;

[0031] Based on the encrypted data of the equipment status, the status of the power equipment and / or fault warning are displayed through the monitoring and management platform.

[0032] In a possible implementation, the step of obtaining temperature distribution data corresponding to the power equipment through an infrared imaging module includes:

[0033] By installing an infrared camera at a key position of the power equipment, an infrared thermal image of the surface of the power equipment is captured in real time, and the infrared thermal image is sent to an image preprocessing submodule;

[0034] Based on mean filtering and histogram equalization, the infrared thermal image is processed by an image preprocessing submodule to obtain a preprocessed image, and the preprocessed image is used as the temperature distribution data.

[0035] In a possible implementation, based on the temperature distribution data, determining the temperature characteristics of the power equipment through the edge computing module, and performing equipment status analysis on the power equipment based on the temperature characteristics to obtain equipment status analysis data includes:

[0036] According to the temperature distribution data, the edge computing unit performs temperature feature extraction to obtain the temperature feature, and performs anomaly detection based on the temperature feature and an abnormality threshold to obtain an abnormality detection result;

[0037] Based on the temperature characteristics and the associated monitoring data, a fusion analysis is performed by the data fusion unit to generate a comprehensive equipment status report;

[0038] The abnormality detection result and the device status report are used as the device status analysis data through a data processing unit.

[0039] In a possible implementation, the data fusion unit performs fusion analysis based on the temperature characteristics and the associated monitoring data to generate a comprehensive equipment status report, including:

[0040] The temperature characteristics and associated monitoring data are input into a machine learning model to obtain the comprehensive equipment status report.

[0041] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0042] at least one processor;

[0043] and a memory communicatively connected to the at least one processor; wherein,

[0044] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the intelligent monitoring method for electric power equipment described in any embodiment of the present invention.

[0045] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the intelligent monitoring method for electric power equipment described in any embodiment of the present invention when executed.

[0046] The technical solution of the embodiment of the present invention provides an intelligent monitoring system and monitoring method for electric equipment, the system comprising: an infrared imaging module, used to obtain temperature distribution data corresponding to the electric equipment, and send the temperature distribution data to an edge computing module; an edge computing module, used to determine the temperature characteristics of the electric equipment based on the temperature distribution data, and perform equipment status analysis on the electric equipment based on the temperature characteristics to obtain equipment status analysis data, and send the equipment status analysis data to a data communication module; a data communication module, used to encrypt the equipment status analysis data to obtain equipment status encrypted data, and upload the equipment status encrypted data to a monitoring management platform based on wireless communication; a monitoring management platform, used to display the status of the electric equipment and / or provide fault warning based on the equipment status encrypted data. The technical solution of the present invention combines infrared imaging technology with edge computing, infrared imaging can capture the temperature distribution of the equipment surface in real time, and edge computing can perform data processing near the equipment, and realize early identification and timely warning of faults by real-time monitoring and analysis of the temperature and appearance characteristics of the electric equipment, thereby improving the operation safety and maintenance efficiency of the electric equipment, and solving the technical problems that traditional monitoring methods rely on regular manual inspections and a single monitoring method, and have delayed response, data islands, and high labor costs.

[0047] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0049] Figure 1 A schematic diagram of the structure of an intelligent monitoring system for electric power equipment provided in Embodiment 1 of the present invention;

[0050] Figure 2 A flowchart of a method for intelligent monitoring of electric power equipment provided in Embodiment 2 of the present invention;

[0051] Figure 3 This is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0052] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0053] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0054] Embodiment 1

[0055] Figure 1 This is a schematic diagram of the structure of an intelligent monitoring system for power equipment provided in the first embodiment of the present invention. The system includes an infrared imaging module 110, an edge computing module 120, a data communication module 130 and a monitoring management platform 140, wherein:

[0056] The infrared imaging module is used to obtain temperature distribution data corresponding to the power equipment and send the temperature distribution data to the edge computing module;

[0057] The edge computing module is used to determine the temperature characteristics of the power equipment based on the temperature distribution data, perform equipment status analysis on the power equipment based on the temperature characteristics, obtain equipment status analysis data, and send the equipment status analysis data to the data communication module;

[0058] The data communication module is used to encrypt the device status analysis data to obtain device status encrypted data, and upload the device status encrypted data to the monitoring management platform based on wireless communication;

[0059] The monitoring and management platform is used to display the status of the power equipment and / or provide fault warning based on the encrypted data of the equipment status.

[0060] Specifically, the infrared imaging module can use infrared imaging technology to capture the temperature distribution data of power equipment. Infrared imaging can detect infrared radiation emitted from the surface of an object and convert it into a visible image, thereby revealing the temperature difference of the equipment. Among them, the temperature distribution data is usually represented in the form of an image or a data set, which contains the temperature information of each part of the power equipment.

[0061] The edge computing module can receive the temperature distribution data transmitted by the infrared imaging module, and process and analyze it. Edge computing can make the calculation, storage and application of data closer to the source of the data, thereby reducing data transmission delays and improving processing efficiency. Based on the temperature distribution data, the edge computing module can determine the temperature characteristics of the power equipment, such as the highest temperature, temperature gradient, abnormal hot spots, etc. Then, these temperature characteristics are used to analyze the status of the power equipment to determine whether the equipment is operating normally or has potential faults.

[0062] The data communication module can encrypt the device status analysis data generated by the edge computing module, obtain the encrypted device status data, and upload it to the monitoring management platform via wireless communication to ensure the security and privacy of the data during transmission. The encrypted device status data refers to the encrypted device status analysis data.

[0063] The monitoring and management platform can receive the encrypted data of the equipment status uploaded by the data communication module and decrypt it to obtain the original equipment status analysis data. Then, the status of the power equipment is displayed based on this data, such as the temperature distribution, health status and other information of the equipment are intuitively displayed in the form of charts and reports. At the same time, if there is a potential fault or abnormal state of the equipment, the monitoring and management platform can also issue a fault warning and notify relevant personnel to handle it in time.

[0064] In one possible implementation, the infrared imaging module includes: an infrared camera and an image preprocessing submodule, wherein the infrared camera is installed at a key position of the power equipment, captures the infrared thermal image of the surface of the power equipment in real time, and sends the infrared thermal image to the image preprocessing submodule; the image preprocessing submodule is used to process the infrared thermal image based on mean filtering and histogram equalization to obtain a preprocessed image, and use the preprocessed image as the temperature distribution data.

[0065] Among them, multiple infrared cameras can be set up in the substation to cover all key power equipment (such as transformers, distribution cabinets, etc.). Each infrared camera is connected to an edge computing unit, which is responsible for real-time processing of the data captured by the camera.

[0066] Specifically, the infrared camera can be installed in key parts of the power equipment, for example, places where the temperature changes significantly or is prone to failure, such as transformers, switchgear, cable joints, etc. The infrared camera captures the infrared thermal image of the surface of the power equipment in real time. The infrared thermal image can reflect the temperature distribution on the surface of the equipment, for example, different colors or gray values ​​represent different temperature areas. Then, the infrared camera sends the captured infrared thermal image to the image preprocessing submodule for further processing. The infrared camera collects infrared thermal imaging data on the surface of the equipment regularly (for example, every 1 second).

[0067] In order to improve the clarity and readability of the image, the infrared thermal image transmitted by the infrared camera can be received and preprocessed, including mean filtering and histogram equalization. The mean filtering calculates the average value of the pixel values ​​in the neighborhood around each pixel in the image to replace the value of the pixel, effectively removing the noise in the image and making the temperature distribution clearer. The histogram equalization adjusts the grayscale histogram of the image to enhance the contrast of the image, making the temperature difference more significant in the image.

[0068] In one possible implementation, the edge computing module includes: an edge computing unit, a data fusion unit and a data processing unit, wherein the edge computing unit is used to extract temperature features according to the temperature distribution data to obtain the temperature features, and perform anomaly detection based on the temperature features and the anomaly threshold to obtain anomaly detection results; the data fusion unit is used to perform fusion analysis based on the temperature features and associated monitoring data to generate a comprehensive equipment status report; the data processing unit is used to send the anomaly detection results and the equipment status report as the equipment status analysis data to the data communication module.

[0069] The abnormal threshold value may be set according to the normal operating temperature range of the power equipment, historical data or empirical values.

[0070] Specifically, the edge computing unit can extract temperature features based on temperature distribution data, and perform anomaly detection based on the extracted temperature features and the preset anomaly threshold. If the temperature feature exceeds the anomaly threshold, it is judged as abnormal and an anomaly detection result is generated. In addition, the data fusion unit can perform fusion analysis based on temperature features and other related monitoring data, such as ambient temperature, humidity, etc., evaluate the overall status of the power equipment, and generate a comprehensive equipment status report. Among them, the equipment status report can include information such as the health status of the equipment, potential failure points, and remaining life prediction.

[0071] The data processing unit can receive the anomaly detection results from the edge computing unit and the equipment status report from the data fusion unit, integrate them into equipment status analysis data, and send the equipment status analysis data to the data communication module for encryption and uploading to the monitoring management platform.

[0072] In a possible implementation, the data fusion unit is specifically used to: input the temperature characteristics and related monitoring data into a machine learning model to obtain the comprehensive equipment status report.

[0073] Specifically, a suitable machine learning model can be selected according to the type of power equipment and the characteristics of the monitoring data. Preferably, a recurrent neural network is used. Then, the machine learning model is trained using the historical temperature characteristics and associated monitoring data so that it can accurately predict the status of the power equipment based on the input temperature characteristics and associated monitoring data. After the training is completed, the temperature characteristics and associated monitoring data can be input into the trained machine learning model, and a comprehensive equipment status report can be generated based on the output of the model.

[0074] In one possible implementation, the data communication module includes: a data encryption submodule and a wireless communication submodule, wherein the data encryption submodule is used to encrypt the device status analysis data based on the AES encryption algorithm to obtain the device status encrypted data; the wireless communication submodule is used to upload the device status encrypted data to the monitoring and management platform via Wi-Fi or LoRa.

[0075] Specifically, the data encryption submodule can encrypt the device status analysis data based on the AES (Advanced Encryption Standard) encryption algorithm to generate device status encrypted data, and use data encryption technology to ensure the security and integrity of the data transmission process. Then, the wireless communication submodule can upload the device status encrypted data to the monitoring management platform through wireless communication technology. Among them, the wireless communication technology can be a wireless communication method of Wi-Fi or LoRa.

[0076] In a possible implementation, the monitoring management platform includes: a data decryption and processing submodule, a display submodule and an alarm notification submodule, wherein the data decryption and processing submodule is used to decrypt and analyze the encrypted data of the equipment status to determine the temperature distribution diagram, status information and historical data corresponding to the power equipment;

[0077] The display submodule is used to display the temperature distribution diagram, status information and historical data; the alarm notification submodule is used to automatically send an early warning notification when the temperature of the power equipment is abnormal or a fault characteristic occurs.

[0078] Specifically, the data decryption and processing submodule uses the same AES encryption algorithm and key as the data encryption submodule to decrypt the encrypted device status data and restore it to the original device status analysis data. Then, the decrypted device status analysis data is further processed and analyzed, including extracting the temperature distribution map, status information, and comparing it with historical data. Furthermore, the processed temperature distribution map, status information, and historical data are output for use by the display submodule and the alarm notification submodule.

[0079] The display submodule can receive the temperature distribution diagram, status information and historical data output by the data decryption and processing submodule, and then display these data, such as using visualization tools such as charts and curves. It can also provide a user interaction interface. Maintenance personnel can access the monitoring management platform through a PC or mobile device to view the equipment status and historical monitoring data in real time, allowing users to query, filter and export data.

[0080] Among them, displaying the temperature distribution diagram means displaying the temperature distribution on the surface of the power equipment, which is convenient for users to intuitively understand the thermal status of the equipment. Displaying the status information means displaying the current status of the power equipment, such as normal operation, abnormality, failure, etc., as well as specific status descriptions and parameters. Displaying historical data means displaying the historical temperature data and status change records of the power equipment, which is convenient for users to analyze the operation trends and potential problems of the equipment.

[0081] In addition, the alarm notification submodule can perform anomaly detection by setting thresholds and rules. When abnormal temperature or fault characteristics of power equipment are detected, the alarm mechanism is automatically triggered to send early warning notifications to relevant personnel or systems so that timely measures can be taken to deal with abnormalities or faults. For example, emails, text messages or push notifications are sent to designated operation and maintenance personnel or managers, or alarm information is displayed on the user interface of the monitoring and management platform, such as pop-up windows. The effective effect of this is that the monitoring and management platform can comprehensively and real-time monitor the status of power equipment, provide visual data display and convenient query functions, and issue early warning notifications in time when abnormalities or faults occur in the equipment, providing strong support for the operation and management of power equipment.

[0082] The present invention provides a method for early identification and timely warning of faults by real-time monitoring of the temperature and appearance of the equipment. The system not only improves the monitoring efficiency and accuracy of power equipment, but also reduces the workload of manual inspections, and has broad application prospects and market value.

[0083] The technical solution of the embodiment of the present invention provides an intelligent monitoring system and monitoring method for electric equipment, the system comprising: an infrared imaging module, used to obtain temperature distribution data corresponding to the electric equipment, and send the temperature distribution data to an edge computing module; an edge computing module, used to determine the temperature characteristics of the electric equipment based on the temperature distribution data, and perform equipment status analysis on the electric equipment based on the temperature characteristics to obtain equipment status analysis data, and send the equipment status analysis data to a data communication module; a data communication module, used to encrypt the equipment status analysis data to obtain equipment status encrypted data, and upload the equipment status encrypted data to a monitoring management platform based on wireless communication; a monitoring management platform, used to display the status of the electric equipment and / or provide fault warning based on the equipment status encrypted data. The technical solution of the present invention combines infrared imaging technology with edge computing, infrared imaging can capture the temperature distribution of the equipment surface in real time, and edge computing can perform data processing near the equipment, and realize early identification and timely warning of faults by real-time monitoring and analysis of the temperature and appearance characteristics of the electric equipment, thereby improving the operation safety and maintenance efficiency of the electric equipment, and solving the technical problems that traditional monitoring methods rely on regular manual inspections and a single monitoring method, and have delayed response, data islands, and high labor costs.

[0084] Embodiment 2

[0085] Figure 2 This is a flow chart of a method for intelligent monitoring of electric power equipment provided in the second embodiment of the present invention. This embodiment can be applied to monitor the safe operation of electric power equipment. The method can be executed by an intelligent monitoring system for electric power equipment, which can be implemented in the form of hardware and / or software. Figure 2 As shown, the method specifically comprises the following steps:

[0086] S210. Acquire temperature distribution data corresponding to the power equipment through the infrared imaging module, and send the temperature distribution data to the edge computing module.

[0087] Specifically, the temperature distribution data of the power equipment is captured through the infrared imaging module. Infrared imaging can detect the infrared radiation emitted by the surface of an object and convert it into a visible image, thereby revealing the temperature difference of the equipment. Among them, the temperature distribution data is usually represented in the form of an image or a data set, which contains the temperature information of each part of the power equipment.

[0088] In an embodiment of the present invention, the temperature distribution data corresponding to the power equipment is obtained through the infrared imaging module, including: capturing the infrared thermal image of the surface of the power equipment in real time through an infrared camera installed at a key position of the power equipment, and sending the infrared thermal image to an image preprocessing submodule; based on mean filtering and histogram equalization, the infrared thermal image is processed through the image preprocessing submodule to obtain a preprocessed image, and the preprocessed image is used as the temperature distribution data.

[0089] Specifically, the infrared camera can be installed at key parts of the power equipment, for example, places where the temperature changes significantly or is prone to failure, such as transformers, switchgear, cable joints, etc. The infrared camera captures the infrared thermal image of the surface of the power equipment in real time. The infrared thermal image can reflect the temperature distribution on the surface of the equipment, for example, different temperature areas are represented by different colors or gray values. Then, the infrared camera sends the captured infrared thermal image to the image preprocessing submodule for further processing.

[0090] In order to improve the clarity and readability of the image, the infrared thermal image transmitted by the infrared camera can be received and preprocessed, including mean filtering and histogram equalization. The mean filtering calculates the average value of the pixel values ​​in the neighborhood around each pixel in the image to replace the value of the pixel, effectively removing the noise in the image and making the temperature distribution clearer. The histogram equalization adjusts the grayscale histogram of the image to enhance the contrast of the image, making the temperature difference more significant in the image.

[0091] S220. Based on the temperature distribution data, determine the temperature characteristics of the power equipment through the edge computing module, perform equipment status analysis on the power equipment based on the temperature characteristics, obtain equipment status analysis data, and send the equipment status analysis data to the data communication module.

[0092] Specifically, the edge computing module receives the temperature distribution data from the infrared imaging module, processes and analyzes it, and edge computing can make the calculation, storage and application of data closer to the source of the data, thereby reducing data transmission delays and improving processing efficiency. Based on the temperature distribution data, the edge computing module can determine the temperature characteristics of the power equipment, such as the highest temperature, temperature gradient, abnormal hot spots, etc. Then, these temperature characteristics are used to analyze the status of the power equipment to determine whether the equipment is operating normally or has potential faults.

[0093] In an embodiment of the present invention, based on the temperature distribution data, the temperature characteristics of the power equipment are determined by the edge computing module, and the power equipment is subjected to equipment status analysis based on the temperature characteristics to obtain equipment status analysis data, including: according to the temperature distribution data, temperature characteristics are extracted by an edge computing unit to obtain the temperature characteristics, and anomaly detection is performed based on the temperature characteristics and anomaly thresholds to obtain anomaly detection results; based on the temperature characteristics and associated monitoring data, fusion analysis is performed by the data fusion unit to generate a comprehensive equipment status report; and the anomaly detection results and the equipment status report are used as the equipment status analysis data by a data processing unit.

[0094] The abnormal threshold value may be set according to the normal operating temperature range of the power equipment, historical data or empirical values.

[0095] Specifically, the edge computing unit can extract temperature features based on temperature distribution data, and perform anomaly detection based on the extracted temperature features and the preset anomaly threshold. If the temperature feature exceeds the anomaly threshold, it is judged as abnormal and an anomaly detection result is generated. In addition, the data fusion unit can perform fusion analysis based on temperature features and other related monitoring data, such as ambient temperature, humidity, etc., evaluate the overall status of the power equipment, and generate a comprehensive equipment status report. Among them, the equipment status report can include information such as the health status of the equipment, potential failure points, and remaining life prediction.

[0096] In an embodiment of the present invention, based on the temperature characteristics and the associated monitoring data, a fusion analysis is performed by the data fusion unit to generate a comprehensive equipment status report, including: inputting the temperature characteristics and the associated monitoring data into a machine learning model to obtain the comprehensive equipment status report.

[0097] Specifically, a suitable machine learning model can be selected according to the type of power equipment and the characteristics of the monitoring data. Preferably, a recurrent neural network is used. Then, the machine learning model is trained using the historical temperature characteristics and associated monitoring data so that it can accurately predict the status of the power equipment based on the input temperature characteristics and associated monitoring data. After the training is completed, the temperature characteristics and associated monitoring data can be input into the trained machine learning model, and a comprehensive equipment status report can be generated based on the output of the model.

[0098] S230. Encrypt the device status analysis data through the data communication module to obtain device status encrypted data, and upload the device status encrypted data to a monitoring management platform based on wireless communication.

[0099] The device status encrypted data refers to the device status analysis data that has been encrypted.

[0100] Specifically, the device status analysis data generated by the edge computing module can be encrypted through the data communication module to obtain the device status encrypted data, and uploaded to the monitoring management platform through wireless communication to ensure the security and privacy of the data during transmission.

[0101] S240. Based on the encrypted data of the equipment status, the status of the power equipment and / or fault warning are displayed through the monitoring and management platform.

[0102] Among them, the monitoring and management platform can receive the encrypted data of the equipment status uploaded by the data communication module, and decrypt it to obtain the original equipment status analysis data. Then, based on this data, the status of the power equipment is displayed, such as the temperature distribution, health status and other information of the equipment are intuitively displayed in the form of charts and reports. At the same time, if there is a potential fault or abnormal state of the equipment, the monitoring and management platform can also issue a fault warning and notify relevant personnel in time to handle it.

[0103] Through the above technical solution, the present invention can achieve the following expected effects:

[0104] Real-time monitoring: Infrared imaging technology can capture temperature changes on the surface of equipment in real time, ensuring instant understanding of equipment status.

[0105] Fast response: The edge computing module can process data in real time near the device, reduce data transmission delays, and improve fault response speed.

[0106] Intelligent analysis: Through data fusion and machine learning algorithms, the system can automatically identify potential faults and provide accurate fault diagnosis and prediction.

[0107] Improved maintenance efficiency: By identifying faults in advance, reducing equipment downtime and maintenance costs, and improving the overall operating efficiency of power equipment.

[0108] The technical solution of the embodiment of the present invention provides an intelligent monitoring method for power equipment, including: obtaining temperature distribution data corresponding to the power equipment through an infrared imaging module, and sending the temperature distribution data to an edge computing module. Based on the temperature distribution data, the edge computing module determines the temperature characteristics of the power equipment, and performs equipment status analysis on the power equipment based on the temperature characteristics to obtain equipment status analysis data, and sends the equipment status analysis data to the data communication module. The data communication module encrypts the equipment status analysis data to obtain equipment status encrypted data, and uploads the equipment status encrypted data to a monitoring and management platform based on wireless communication. Based on the equipment status encrypted data, the monitoring and management platform performs status display and / or fault warning of the power equipment. The technical solution of the present invention combines infrared imaging technology with edge computing. Infrared imaging can capture the temperature distribution of the surface of the equipment in real time, while edge computing can perform data processing near the equipment. By real-time monitoring and analysis of the temperature and appearance characteristics of the power equipment, early identification and timely warning of faults are achieved, and the operation safety and maintenance efficiency of the power equipment are improved, which solves the technical problems that traditional monitoring methods rely on regular manual inspections and a single monitoring method, and there are delayed response, data islands, and high labor costs.

[0109] Embodiment 3

[0110] Figure 3 A schematic diagram of the structure of an electronic device provided for Embodiment 3 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0111] like Figure 3As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0112] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0113] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a method for intelligent monitoring of power equipment.

[0114] In some embodiments, a method for intelligent monitoring of electric power equipment may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for intelligent monitoring of electric power equipment described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform a method for intelligent monitoring of electric power equipment in any other appropriate manner (e.g., by means of firmware).

[0115] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0116] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0117] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0118] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0119] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0120] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0121] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0122] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent monitoring system for electric power equipment, characterized in that: include: Infrared imaging module, edge computing module, data communication module and monitoring management platform, among which, The infrared imaging module is used to obtain temperature distribution data corresponding to the power equipment and send the temperature distribution data to the edge computing module; The edge computing module is used to determine the temperature characteristics of the power equipment based on the temperature distribution data, perform equipment status analysis on the power equipment based on the temperature characteristics, obtain equipment status analysis data, and send the equipment status analysis data to the data communication module; The data communication module is used to encrypt the device status analysis data to obtain device status encrypted data, and upload the device status encrypted data to the monitoring management platform based on wireless communication; The monitoring and management platform is used to display the status of the power equipment and / or provide fault warning based on the encrypted data of the equipment status.

2. The system according to claim 1, characterized in that The infrared imaging module includes: an infrared camera and an image preprocessing submodule, wherein: The infrared camera is installed at a key position of the power equipment to capture the infrared thermal image of the surface of the power equipment in real time and send the infrared thermal image to the image preprocessing submodule; The image preprocessing submodule is used to process the infrared thermal image based on mean filtering and histogram equalization to obtain a preprocessed image, and use the preprocessed image as the temperature distribution data.

3. The system according to claim 1, characterized in that The edge computing module includes: an edge computing unit, a data fusion unit and a data processing unit, wherein: The edge computing unit is used to extract temperature features according to the temperature distribution data to obtain the temperature features, and perform anomaly detection based on the temperature features and anomaly thresholds to obtain anomaly detection results; The data fusion unit is used to perform fusion analysis based on the temperature characteristics and associated monitoring data to generate a comprehensive equipment status report; The data processing unit is used to send the abnormality detection result and the device status report as the device status analysis data to the data communication module.

4. The system according to claim 3, characterized in that The data fusion unit is specifically used for: The temperature characteristics and associated monitoring data are input into a machine learning model to obtain the comprehensive equipment status report.

5. The system according to claim 1, characterized in that The data communication module includes: a data encryption submodule and a wireless communication submodule, wherein: The data encryption submodule is used to encrypt the device status analysis data based on the AES encryption algorithm to obtain the device status encrypted data; The wireless communication submodule is used to upload the encrypted data of the device status to the monitoring management platform via Wi-Fi or LoRa.

6. The system according to claim 1, characterized in that The monitoring management platform includes: a data decryption and processing submodule, a display submodule and an alarm notification submodule, wherein: The data decryption and processing submodule is used to decrypt and analyze the encrypted data of the equipment status to determine the temperature distribution diagram, status information and historical data corresponding to the power equipment; The display submodule is used to display the temperature distribution diagram, status information and historical data; The alarm notification submodule is used to automatically send an early warning notification when the temperature of the power equipment is abnormal or a fault characteristic occurs.

7. A method for intelligent monitoring of electric power equipment, characterized in that: include: Acquire temperature distribution data corresponding to the power equipment through the infrared imaging module, and send the temperature distribution data to the edge computing module; Based on the temperature distribution data, determining the temperature characteristics of the power equipment through the edge computing module, performing device status analysis on the power equipment based on the temperature characteristics to obtain device status analysis data, and sending the device status analysis data to the data communication module; Encrypting the device status analysis data through the data communication module to obtain device status encrypted data, and uploading the device status encrypted data to the monitoring management platform based on wireless communication; Based on the encrypted data of the equipment status, the status of the power equipment and / or fault warning are displayed through the monitoring and management platform.

8. The method according to claim 7, characterized in that The method of obtaining temperature distribution data corresponding to the power equipment through the infrared imaging module includes: By installing an infrared camera at a key position of the power equipment, an infrared thermal image of the surface of the power equipment is captured in real time, and the infrared thermal image is sent to an image preprocessing submodule; Based on mean filtering and histogram equalization, the infrared thermal image is processed by an image preprocessing submodule to obtain a preprocessed image, and the preprocessed image is used as the temperature distribution data.

9. The method according to claim 7, characterized in that: The step of determining the temperature characteristics of the power equipment through the edge computing module based on the temperature distribution data, and performing equipment status analysis on the power equipment based on the temperature characteristics to obtain equipment status analysis data includes: According to the temperature distribution data, the edge computing unit performs temperature feature extraction to obtain the temperature feature, and performs anomaly detection based on the temperature feature and an abnormality threshold to obtain an abnormality detection result; Based on the temperature characteristics and the associated monitoring data, a fusion analysis is performed by the data fusion unit to generate a comprehensive equipment status report; The abnormality detection result and the device status report are used as the device status analysis data through a data processing unit.

10. The method according to claim 9, characterized in that The data fusion unit performs fusion analysis based on the temperature characteristics and the associated monitoring data to generate a comprehensive equipment status report, including: The temperature characteristics and associated monitoring data are input into a machine learning model to obtain the comprehensive equipment status report.

Images