Transformer data monitoring method and device, computer equipment and storage medium
By conducting status analysis and fault diagnosis of the items to be detected by the transformer, the operating status level and abnormal diagnosis results are determined, the problem of excessive transformer data is solved, and the communication pressure and energy consumption of cloud servers is reduced.
Patent Information
- Application Number
- CN202510454070.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-11
- Publication Date
- 2025-08-12
AI Technical Summary
The amount of data reported by the transformer to the cloud server is too large, resulting in a large amount of transmission resources and an increase in system energy consumption.
By obtaining the operation data of the transformer to be detected, performing status analysis and fault diagnosis, determining the operating status level and abnormal diagnosis results, and feedback monitoring results to the cloud server to reduce the amount of data uploads.
It reduces the communication pressure of cloud servers and the occupation pressure of transmission resources, and reduces system energy consumption.
Smart Images
Figure CN120470359A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of power safety technology, and in particular to a transformer data monitoring method, device, computer equipment, and storage medium. Background Art
[0002] To ensure the continuous and stable operation of the transformer, the cloud server needs to obtain and monitor the transformer's operating data in real time to ensure real-time monitoring of the transformer's fault conditions.
[0003] However, since the amount of data reported by the transformer to the cloud server is too large, including but not limited to pictures and videos; therefore, the amount of data reported each time can reach tens of megabytes, resulting in a large amount of transmission resources being occupied, and the transmission process will consume a lot of system energy. Summary of the Invention
[0004] Based on this, it is necessary to provide a transformer data monitoring method, device, computer equipment and storage medium that can prevent a large amount of transmission resources from being occupied in order to address the above technical problems.
[0005] In a first aspect, the present application provides a transformer data monitoring method. The method comprises:
[0006] Obtaining operating data of the transformer corresponding to at least one item to be tested;
[0007] Performing status analysis on each of the items to be detected based on the operating data to determine the operating status level corresponding to each of the items to be detected;
[0008] Performing fault diagnosis on each of the items to be detected according to the operating status level corresponding to each of the items to be detected and the operating data, to obtain an abnormality diagnosis result for each of the items to be detected;
[0009] According to the operating status level corresponding to each of the items to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal according to the monitoring results.
[0010] In one embodiment, performing status analysis on each of the items to be detected based on the operating data to determine the operating status level corresponding to each of the items to be detected includes:
[0011] For each of the items to be detected, obtaining a data value range corresponding to each candidate status level corresponding to the item to be detected;
[0012] The operating status level corresponding to the item to be detected is determined according to the data value range and the operating data corresponding to the item to be detected.
[0013] In one embodiment, determining the operating status level corresponding to the item to be detected based on the data value range and the operating data corresponding to the item to be detected includes:
[0014] Processing the operating data corresponding to the item to be detected to obtain target data;
[0015] The candidate state level whose data value range includes the target data is used as the running state level corresponding to the item to be detected.
[0016] In one embodiment, processing the operating data corresponding to the item to be detected to obtain target data includes:
[0017] Cleaning the operating data corresponding to the item to be detected to obtain cleaned operating data;
[0018] The cleaned operating data is subjected to data scoring processing to obtain target data.
[0019] In one embodiment, the performing of fault diagnosis on each of the items to be detected based on the operating status level corresponding to each of the items to be detected and the operating data to obtain an abnormality diagnosis result for each of the items to be detected includes:
[0020] For each of the items to be detected, determining the fault diagnosis accuracy of the item to be detected according to the operating status level;
[0021] Fault diagnosis is performed on each of the items to be detected according to the fault diagnosis accuracy and the operating data to obtain an abnormality diagnosis result of the item to be detected.
[0022] In one embodiment, the performing fault diagnosis on each of the items to be detected based on the operating status level corresponding to each of the items to be detected and the operating data to obtain an abnormality diagnosis result of the item to be detected includes:
[0023] Performing fault diagnosis on each of the items to be detected according to the operating status level corresponding to each of the items to be detected and the operating data to obtain the cause of the fault of the item to be detected;
[0024] Determine the corresponding treatment suggestions for the fault cause;
[0025] The fault cause and the treatment suggestion are used as the abnormality diagnosis result of the item to be detected.
[0026] In a second aspect, the present application also provides a transformer data monitoring device. The device comprises:
[0027] An acquisition module, configured to acquire operating data of the transformer corresponding to at least one item to be detected;
[0028] a determination module, configured to perform status analysis on each of the items to be detected based on the operation data, and determine an operation status level corresponding to each of the items to be detected;
[0029] a diagnosis module, configured to perform fault diagnosis on each of the items to be detected based on the operating status level corresponding to each of the items to be detected and the operating data, and obtain an abnormality diagnosis result for each of the items to be detected;
[0030] The feedback module is used to feed back the transformer monitoring results to the cloud server based on the operating status level corresponding to each of the items to be detected and the abnormal diagnosis results of each item to be detected, so that the cloud server can send adjustment instructions for the transformer to the user terminal based on the monitoring results.
[0031] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are performed:
[0032] Obtaining operating data of the transformer corresponding to at least one item to be tested;
[0033] Performing status analysis on each of the items to be detected based on the operating data to determine the operating status level corresponding to each of the items to be detected;
[0034] Performing fault diagnosis on each of the items to be detected according to the operating status level corresponding to each of the items to be detected and the operating data, to obtain an abnormality diagnosis result for each of the items to be detected;
[0035] According to the operating status level corresponding to each of the items to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal according to the monitoring results.
[0036] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:
[0037] Obtaining operating data of the transformer corresponding to at least one item to be tested;
[0038] Performing status analysis on each of the items to be detected based on the operating data to determine the operating status level corresponding to each of the items to be detected;
[0039] Performing fault diagnosis on each of the items to be detected according to the operating status level corresponding to each of the items to be detected and the operating data, to obtain an abnormality diagnosis result for each of the items to be detected;
[0040] According to the operating status level corresponding to each of the items to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal according to the monitoring results.
[0041] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps:
[0042] Obtaining operating data of the transformer corresponding to at least one item to be tested;
[0043] Performing status analysis on each of the items to be detected based on the operating data to determine the operating status level corresponding to each of the items to be detected;
[0044] Performing fault diagnosis on each of the items to be detected according to the operating status level corresponding to each of the items to be detected and the operating data, to obtain an abnormality diagnosis result for each of the items to be detected;
[0045] According to the operating status level corresponding to each of the items to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal according to the monitoring results.
[0046] The above transformer data monitoring method, device, computer equipment and storage medium perform status analysis on each item to be detected by using the operating data of at least one item to be detected corresponding to the transformer, determine the operating status level corresponding to each item to be detected, and perform fault diagnosis on each item to be detected based on the operating status level and operating data corresponding to each item to be detected, and obtain abnormal diagnosis results for each item to be detected; further, based on the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends an adjustment instruction for the transformer to the user terminal based on the monitoring results. According to the above content, the present application determines the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected by using the operating data of at least one item to be detected corresponding to the transformer, and further, based on the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server; by determining the operating status level and abnormal diagnosis results of the item to be detected, the amount of data uploaded to the cloud server is reduced, the communication pressure on the cloud server is reduced, the pressure on the use of transmission resources is alleviated, and the system energy consumption required for the transmission process is reduced. BRIEF DESCRIPTION OF THE DRAWINGS
[0047] Figure 1 An application environment diagram of a transformer data monitoring method provided in an embodiment of the present application;
[0048] Figure 2 A flowchart of a first transformer data monitoring method provided in an embodiment of the present application;
[0049] Figure 3 A flow chart of a second transformer data monitoring method provided in an embodiment of the present application;
[0050] Figure 4 A schematic flow chart of a third transformer data monitoring method provided in an embodiment of the present application;
[0051] Figure 5 A schematic flow chart of a fourth transformer data monitoring method provided in an embodiment of the present application;
[0052] Figure 6 A schematic diagram of the software architecture corresponding to a transformer data monitoring method provided in an embodiment of the present application;
[0053] Figure 7 A schematic diagram of the hardware architecture corresponding to a transformer data monitoring method provided in an embodiment of the present application;
[0054] Figure 8 A structural block diagram of a transformer data monitoring device provided in an embodiment of the present application;
[0055] Figure 9 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION
[0056] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.
[0057] The transformer data monitoring method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be integrated on server 104, or placed on a cloud or other network server. Status analysis is performed on each item to be detected based on the operating data of at least one item to be detected corresponding to the transformer, and the operating status level corresponding to each item to be detected is determined. Fault diagnosis is then performed on each item to be detected based on the operating status level and operating data corresponding to each item to be detected, obtaining abnormality diagnosis results for each item to be detected. Furthermore, based on the operating status level corresponding to each item to be detected and the abnormality diagnosis results for each item to be detected, transformer monitoring results are fed back to a cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal based on the monitoring results. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart car devices, etc. Portable wearable devices can include smart watches, smart bracelets, head-mounted devices, etc. Server 104 can be implemented as a standalone server or a server cluster consisting of multiple servers.
[0058] In one embodiment, Figure 2 As shown, a transformer data monitoring method is provided, which is applied to Figure 1 Taking the terminal 102 in FIG. 1 as an example, the method includes the following steps:
[0059] S201: Obtain operating data of a transformer corresponding to at least one item to be detected.
[0060] It should be noted that the items to be tested may include but are not limited to: partial discharge items, core grounding items, bushing dielectric loss items, vibration items, soundprint items, oil chromatography items and analog items; the operating data may include but are not limited to: partial discharge data, core grounding data, bushing dielectric loss data, vibration data, soundprint data, oil chromatography data, oil temperature data, oil level data and load data, etc.
[0061] To further explain, the partial discharge quantity data is associated with the partial discharge quantity item, the core grounding data is associated with the core grounding item, the bushing dielectric loss data is associated with the bushing dielectric loss item, the vibration data is associated with the vibration item, the soundprint data is associated with the soundprint item, the oil chromatography data is associated with the oil chromatography item, and the oil temperature data, oil level data and load data are associated with the analog quantity item.
[0062] In one embodiment of the present application, when it is necessary to obtain operating data corresponding to a transformer, at least one front-end sensor may be pre-set at a collection point corresponding to each item to be detected of the transformer, and then, by obtaining return data from the front-end sensor, the operation of obtaining operating data corresponding to at least one item to be detected of the transformer may be achieved; wherein, the front-end sensor may include but is not limited to: a partial discharge sensor, a vibration sensor, a voiceprint sensor, an oil chromatography online monitoring device, a load sensor, an end-screen sensor, etc., and the sensor type of the front-end sensor is not limited here.
[0063] S202: Analyze the status of each item to be detected based on the operation data to determine the operation status level corresponding to each item to be detected.
[0064] Among them, the higher the operating status level, the better the operating status of the transformer. When performing fault diagnosis on each item to be detected later, the fault diagnosis accuracy can be determined according to the operating status level, and the operating status level is inversely proportional to the fault diagnosis accuracy.
[0065] That is, if the operating status level of a certain item to be detected is higher, the operating status of the item to be detected of the transformer is better, therefore, the probability of failure of the item to be detected is lower, and the fault diagnosis accuracy of the item to be detected is lower.
[0066] It should be noted that when it is necessary to determine the operating status level corresponding to each item to be detected, the following contents may be included: for each item to be detected, obtain the data value range corresponding to each candidate status level corresponding to the item to be detected; then, determine the operating status level corresponding to the item to be detected based on the data value range and the operating data corresponding to the item to be detected.
[0067] S203 , performing fault diagnosis on each item to be detected according to the operation status level and operation data corresponding to each item to be detected, and obtaining an abnormality diagnosis result of each item to be detected.
[0068] It should be noted that when it is necessary to perform fault diagnosis on each item to be detected based on the operating status level and operating data corresponding to each item to be detected, the following contents may be included: for each item to be detected, the fault diagnosis accuracy for the item to be detected is determined according to the operating status level; then, fault diagnosis is performed on each item to be detected based on the fault diagnosis accuracy and operating data to obtain abnormal diagnosis results for the item to be detected.
[0069] S204, based on the operating status level corresponding to each item to be detected and the abnormal diagnosis result of each item to be detected, the transformer monitoring result is fed back to the cloud server, so that the cloud server sends an adjustment instruction for the transformer to the user terminal according to the monitoring result.
[0070] In one embodiment of the present application, when it is necessary to feed back the transformer monitoring results to the cloud server based on the operating status level corresponding to each item to be detected and the abnormal diagnosis result of each item to be detected, the operating status level corresponding to each item to be detected and the abnormal diagnosis result of each item to be detected can be used as the monitoring result, and then the transformer monitoring results are fed back to the cloud server.
[0071] Further explanation: in order to further reduce the amount of data sent to the cloud server, when the transformer monitoring results are fed back to the cloud server based on the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, it is possible to verify whether there are any abnormalities in the abnormal diagnosis results of each item to be detected. If there are any abnormalities, the abnormal data in the operating data will be located, and the items to be detected and the abnormal data with abnormal conditions will be used as the monitoring results fed back to the cloud server.
[0072] The above transformer data monitoring method performs status analysis on each item to be detected by using the operating data of at least one item to be detected corresponding to the transformer, determines the operating status level corresponding to each item to be detected, and performs fault diagnosis on each item to be detected based on the operating status level and operating data corresponding to each item to be detected, thereby obtaining abnormal diagnosis results for each item to be detected; further, according to the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends an adjustment instruction for the transformer to the user terminal based on the monitoring results. According to the above content, the present application determines the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected by using the operating data of at least one item to be detected corresponding to the transformer, further, according to the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server; by determining the operating status level and abnormal diagnosis results of the item to be detected, the amount of data uploaded to the cloud server is reduced, the communication pressure on the cloud server is reduced, the pressure on the occupation of transmission resources is alleviated, and the system energy consumption required for the transmission process is reduced.
[0073] In one embodiment, if Figure 3 As shown, when it is necessary to perform status analysis on each item to be detected based on the operating data and determine the corresponding operating status level of each item to be detected, the following may be specifically included:
[0074] S301 : For each item to be detected, obtain a data value range corresponding to each candidate state level corresponding to the item to be detected.
[0075] It should be noted that, based on the historical experience and actual conditions of the operation and maintenance personnel, candidate value ranges corresponding to each candidate status level of the transformer to be detected of different types and in different application scenarios can be constructed; furthermore, when it is necessary to obtain the data value range corresponding to each candidate status level corresponding to the item to be detected, the data value range corresponding to each candidate status level corresponding to the item to be detected can be determined in combination with the actual type of the transformer and the actual application scenario.
[0076] In one embodiment of the present application, the application relationship between the candidate value range and different types and different application scenarios can be obtained in advance. After determining the actual type and actual application scenario of the transformer, a reference value range with the same type and application scenario as the actual type and actual application scenario of the transformer is selected from the candidate value range, and the reference value range is used as the data value range corresponding to each candidate status level corresponding to the item to be detected.
[0077] S302: Determine the operating status level corresponding to the item to be detected based on the data value range and the operating data corresponding to the item to be detected.
[0078] It should be noted that when it is necessary to determine the operating status level corresponding to the item to be detected based on the data value range and the operating data corresponding to the item to be detected, it may specifically include the following contents: processing the operating data corresponding to the item to be detected to obtain target data; and then, taking the candidate status level whose data value range includes the target data as the operating status level corresponding to the item to be detected.
[0079] To further illustrate, when it is necessary to process the operating data corresponding to the inspection item to obtain target data, the following contents may be included: performing data cleaning on the operating data corresponding to the inspection item to obtain cleaned operating data; performing data scoring processing on the cleaned operating data to obtain target data.
[0080] Among them, when performing data cleaning on the operating data corresponding to the test items, it may include but is not limited to: missing value processing, duplicate data removal, anomaly and noise processing, format and content standardization, and logical error correction.
[0081] The above-mentioned transformer data monitoring method obtains the data value range corresponding to each candidate status level corresponding to the item to be detected, and then determines the operating status level corresponding to the item to be detected based on the data value range and the operating data corresponding to the item to be detected, thereby ensuring the accurate acquisition of the operating status level corresponding to the item to be detected, providing a judgment basis for the subsequent determination of the abnormal diagnosis results of each item to be detected, and limiting the diagnostic accuracy of the subsequent fault diagnosis of each item to be detected.
[0082] In one embodiment, if Figure 4 As shown, when it is necessary to perform fault diagnosis on each item to be detected based on the operating status level and operating data corresponding to each item to be detected, and obtain abnormal diagnosis results for each item to be detected, the following contents may be specifically included:
[0083] S401 : For each item to be detected, determine the fault diagnosis accuracy of the item to be detected according to the operating status level.
[0084] It should be noted that a mapping relationship between different candidate state levels and different candidate diagnostic accuracies may be predefined, and then, based on the mapping relationship and the operating state level, the fault diagnosis accuracy for the item to be detected may be determined.
[0085] In one embodiment of the present application, when it is necessary to determine the fault diagnosis accuracy for the item to be detected, a reference state level that is the same as the operating state level can be determined from the candidate state levels in the mapping relationship, and the candidate diagnostic accuracy corresponding to the reference state level in the mapping relationship can be used as the fault diagnosis accuracy for the item to be detected.
[0086] S402 , performing fault diagnosis on each item to be detected based on the fault diagnosis accuracy and the operation data, and obtaining abnormality diagnosis results of the item to be detected.
[0087] It should be noted that when it is necessary to perform fault diagnosis on each item to be detected based on the fault diagnosis accuracy and operating data, the following may be specifically included: perform fault diagnosis on each item to be detected based on the operating status level and operating data corresponding to each item to be detected to obtain the cause of the fault of the item to be detected; determine the corresponding processing suggestions for the cause of the fault; and use the cause of the fault and the processing suggestions as the abnormal diagnosis results of the item to be detected.
[0088] The above-mentioned transformer data monitoring method determines the fault diagnosis accuracy for the items to be detected, so as to realize fault diagnosis of each item to be detected based on the fault diagnosis accuracy and operating data. By determining the operating status level and abnormal diagnosis results of the items to be detected, the amount of data uploaded to the cloud server is reduced, the communication pressure on the cloud server is reduced, the pressure on the occupation of transmission resources is alleviated, and the system energy consumption required for the transmission process is reduced.
[0089] In one embodiment, if Figure 5 As shown in the figure, when it is necessary to feed back transformer monitoring results to the cloud server, the following contents may be included:
[0090] S501: Obtain operating data of a transformer corresponding to at least one item to be detected.
[0091] S502 : For each item to be detected, obtain a data value range corresponding to each candidate state level corresponding to the item to be detected.
[0092] S503: Clean the operation data corresponding to the item to be detected to obtain cleaned operation data.
[0093] S504: Perform data scoring processing on the cleaned operating data to obtain target data.
[0094] S505: The candidate state level whose data value range includes the target data is used as the operation state level corresponding to the item to be detected.
[0095] S506 , for each item to be detected, determine the fault diagnosis accuracy of the item to be detected according to the operating status level.
[0096] S507 , performing fault diagnosis on each item to be detected according to the operation status level and operation data corresponding to each item to be detected, and obtaining the cause of the fault of the item to be detected.
[0097] S508: Determine the handling suggestions corresponding to the fault cause.
[0098] S509: The fault cause and treatment suggestion are used as the abnormality diagnosis result of the item to be detected.
[0099] S510, based on the operating status level corresponding to each item to be detected and the abnormal diagnosis result of each item to be detected, the transformer monitoring result is fed back to the cloud server, so that the cloud server sends an adjustment instruction for the transformer to the user terminal according to the monitoring result.
[0100] In one embodiment of the present application, after the cloud server sends an adjustment instruction for the transformer to the user terminal based on the monitoring results, the user terminal can view abnormal data and issue inspection tasks based on the adjustment quality, and can issue abnormal alarms to the operation and maintenance personnel to ensure rapid processing of abnormal problems.
[0101] In one embodiment of the present application, the software structure corresponding to the transformer data monitoring method can be as follows: Figure 6 As shown, the device software architecture includes management APP, data center, fault diagnosis, network center, and substation inspection management functions.
[0102] Management App: Each of the 11 front-end sensors, including ultrasonic partial discharge, ultra-high frequency partial discharge, high frequency partial discharge, iron core, casing, vibration, soundprint, oil chromatography, oil temperature, oil level, and load, has an app responsible for collecting sensor data and communicating with the data center via MQTT. The iron core, oil temperature, oil level, load, and dielectric loss apps manage communication and alarm threshold settings, while the oil chromatography, partial discharge, vibration, and soundprint apps manage communication and model parameter settings.
[0103] Data Center: The data center inputs collected data, performs pre-processing and secondary processing, and outputs the cleaned data to the fault diagnosis app for computation of capacity parameters, oil temperature, oil level, and load digital quantities. Pre-processing functions include analog-to-digital conversion of oil temperature, oil level, and load current, calculation of end-screen dielectric loss, and wavelet calculation of local vibration and soundprint. Secondary processing functions include computation of partial discharge PSO-SVM models, vibration and soundprint SVM models, and calculation of three oil chromatogram ratios. The final output is a cleaned partial discharge PDRD spectrum, a vibration energy distribution spectrum, a soundprint spectrum, a three-ratio oil chromatogram spectrum, and end-screen dielectric loss coefficients.
[0104] Fault Diagnosis App: This app loads an LSTM-based fault diagnosis model on the edge, feeds cleaned data into the model, and outputs diagnostic results for transformer fault categories. Furthermore, the app loads an edge optimization algorithm, sets up a local sample library, and leverages comprehensive collected data to continuously optimize the accuracy of the fault diagnosis model for the specific transformer being monitored.
[0105] Network Center: Manages power IoT services and uses a communication processing unit based on an encryption chip to securely transmit data between the integrated processing unit, station backend, and cloud side.
[0106] Substation Inspection App: This app communicates and manages services with the substation inspection mobile terminal. It supports Wi-Fi direct connection, using the transmission protocol of the station's Wi-Fi coverage to send data to the mobile operation and maintenance assistant app, which then issues inspection and maintenance instructions. The app receives and processes this data via TCP / IP, enabling rapid alerting between the edge and the user, improving operation and maintenance efficiency.
[0107] In one embodiment of the present application, the hardware architecture corresponding to the transformer data monitoring method can be as follows: Figure 7 As shown, it includes a data acquisition unit, a data processing unit, a storage unit, a communication unit, and an edge computing unit.
[0108] Data Acquisition Unit: The sensor data acquisition unit is equipped with 11 management apps for data collection. High-precision, high-sampling-rate circuitry and multi-channel synchronous acquisition circuitry ensure accurate partial discharge data. It supports multiple communication protocols, including RS485, 4-20mA, LoRa, and Wapi, as well as fiber optic, Ethernet, and high-speed serial communications. The device integrates and collects data from 11 typical transformer characteristics.
[0109] Data processing unit: This unit performs data cleaning, processing, and feature extraction. Equipped with a 1.5GHz CPU, it features multiple filtering and feature extraction algorithms. The data filtering algorithm removes noise from collected data, improving data accuracy. The feature extraction algorithm extracts characteristic parameters closely related to the transformer's operating status from the raw data. The vibration algorithm extracts energy distribution maps as input features for the SVM algorithm, and the partial discharge algorithm extracts PRPD statistical features as input features.
[0110] The edge computing unit primarily loads a transformer fault diagnosis model based on the LVSM algorithm. This model, trained on a large amount of historical data and known fault cases, intelligently diagnoses the transformer's current operating status, determining the presence of potential faults, and the type and severity of the fault. Edge fault diagnosis is accomplished by tailoring the fault monitoring model from the cloud to the edge. The NPU-based AI computing circuit builds a training library based on the historical fault database.
[0111] Communication Unit: Supports multiple communication protocols, including RS485, LoRa, Wapi, IEC61850, Wi-Fi, and 4G. It supports data exchange between edge intelligent terminals and the cloud, as well as other smart devices. It reports diagnostic results, abnormal data, and remote monitoring to the cloud, and receives cloud-side control commands, model updates, and remote terminal configuration and management. It uses a data encryption chip and the AES encryption algorithm to encrypt uploaded and downloaded data.
[0112] Storage unit: Stores raw data, cleaned data, algorithm models, and diagnostic results. This unit's core function is ultra-long-term storage. It uses large-capacity storage media and incorporates redundancy mechanisms to ensure data is not lost in the event of network failures or data transmission interruptions, providing a basis for subsequent data backtracking and analysis. The storage unit also incorporates redundant backup functionality to prevent data loss during power outages and ensure secure and reliable storage of raw data.
[0113] The power management unit (PMU) provides a stable power supply for the entire edge intelligent device. It accepts multiple power inputs, primarily 220V, and uses a solar backup power supply panel. It also features self-monitoring and switching capabilities.
[0114] The above transformer data monitoring method performs status analysis on each item to be detected by using the operating data of at least one item to be detected corresponding to the transformer, determines the operating status level corresponding to each item to be detected, and performs fault diagnosis on each item to be detected based on the operating status level and operating data corresponding to each item to be detected, thereby obtaining abnormal diagnosis results for each item to be detected; further, according to the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends an adjustment instruction for the transformer to the user terminal based on the monitoring results. According to the above content, the present application determines the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected by using the operating data of at least one item to be detected corresponding to the transformer, further, according to the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server; by determining the operating status level and abnormal diagnosis results of the item to be detected, the amount of data uploaded to the cloud server is reduced, the communication pressure on the cloud server is reduced, the pressure on the occupation of transmission resources is alleviated, and the system energy consumption required for the transmission process is reduced.
[0115] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.
[0116] Based on the same inventive concept, embodiments of the present application also provide a transformer data monitoring device for implementing the aforementioned transformer data monitoring method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations in one or more of the following embodiments of the transformer data monitoring device can be found in the above-described limitations of the transformer data monitoring method and will not be further elaborated here.
[0117] In one embodiment, Figure 8 As shown, a transformer data monitoring device is provided, comprising: an acquisition module 10, a determination module 20, a diagnosis module 30 and a feedback module 40, wherein:
[0118] The acquisition module 10 is used to acquire operating data of the transformer corresponding to at least one item to be detected.
[0119] The determination module 20 is used to perform status analysis on each item to be detected based on the operation data, and determine the operation status level corresponding to each item to be detected.
[0120] The diagnosis module 30 is used to perform fault diagnosis on each item to be detected according to the operation status level and operation data corresponding to each item to be detected, and obtain abnormal diagnosis results of each item to be detected.
[0121] The feedback module 40 is used to feed back the transformer monitoring results to the cloud server based on the operating status level corresponding to each item to be detected and the abnormal diagnosis result of each item to be detected, so that the cloud server can send adjustment instructions for the transformer to the user terminal based on the monitoring results.
[0122] In one embodiment, for each item to be detected, a data value range corresponding to each candidate state level corresponding to the item to be detected is obtained;
[0123] Determine the operating status level of the item to be tested based on the data value range and the operating data corresponding to the item to be tested.
[0124] In one embodiment, data processing is performed on the operating data corresponding to the item to be detected to obtain target data;
[0125] The candidate state level whose data value range includes the target data is used as the operating state level corresponding to the item to be detected.
[0126] In one embodiment, data cleaning is performed on the operating data corresponding to the item to be detected to obtain cleaned operating data;
[0127] Perform data scoring processing on the cleaned operating data to obtain target data.
[0128] In one embodiment, for each item to be detected, the fault diagnosis accuracy for the item to be detected is determined according to the operating status level;
[0129] Perform fault diagnosis on each item to be tested based on the fault diagnosis accuracy and operation data to obtain abnormal diagnosis results of the item to be tested.
[0130] In one embodiment, fault diagnosis is performed on each item to be detected based on the operating status level and operating data corresponding to each item to be detected to obtain the cause of the fault of the item to be detected;
[0131] Determine the corresponding treatment suggestions for the cause of the fault;
[0132] The cause of the fault and the treatment suggestions are taken as the abnormal diagnosis results of the item to be tested.
[0133] The above-mentioned transformer data monitoring device performs status analysis on each item to be detected by using the operating data of at least one item to be detected corresponding to the transformer, determines the operating status level corresponding to each item to be detected, and performs fault diagnosis on each item to be detected based on the operating status level and operating data corresponding to each item to be detected, thereby obtaining abnormal diagnosis results for each item to be detected; further, based on the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends an adjustment instruction for the transformer to the user terminal based on the monitoring results. According to the above content, the present application determines the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected by using the operating data of at least one item to be detected corresponding to the transformer, and further, based on the operating status level corresponding to each item to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server; by determining the operating status level and abnormal diagnosis results of the item to be detected, the amount of data uploaded to the cloud server is reduced, the communication pressure on the cloud server is reduced, the pressure on the use of transmission resources is alleviated, and the system energy consumption required for the transmission process is reduced.
[0134] Each module in the aforementioned transformer data monitoring device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.
[0135] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 9 As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, while the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication, which can be achieved via Wi-Fi, mobile cellular networks, NFC (near-field communication), or other technologies. When executed by the processor, the computer program implements a transformer data monitoring method. The display unit of the computer device is used to produce a visual image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.
[0136] Those skilled in the art will understand that Figure 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.
[0137] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:
[0138] Obtaining operating data of the transformer corresponding to at least one item to be tested;
[0139] Analyze the status of each item to be tested based on the operating data and determine the corresponding operating status level of each item to be tested;
[0140] Perform fault diagnosis on each item to be detected based on the corresponding operating status level and operating data of each item to be detected, and obtain abnormal diagnosis results of each item to be detected;
[0141] According to the operating status level corresponding to each item to be detected and the abnormal diagnosis result of each item to be detected, the transformer monitoring result is fed back to the cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal according to the monitoring results.
[0142] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0143] For each item to be detected, obtain the data value range corresponding to each candidate status level corresponding to the item to be detected;
[0144] Determine the operating status level of the item to be tested based on the data value range and the operating data corresponding to the item to be tested.
[0145] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0146] Process the operating data corresponding to the test item to obtain target data;
[0147] The candidate state level whose data value range includes the target data is used as the operating state level corresponding to the item to be detected.
[0148] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0149] Clean the operating data corresponding to the test item to obtain cleaned operating data;
[0150] Perform data scoring processing on the cleaned operating data to obtain target data.
[0151] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0152] For each item to be tested, determine the fault diagnosis accuracy for the item to be tested according to the operating status level;
[0153] Perform fault diagnosis on each item to be tested based on the fault diagnosis accuracy and operation data to obtain abnormal diagnosis results of the item to be tested.
[0154] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:
[0155] Perform fault diagnosis on each item to be tested based on its corresponding operating status level and operating data to obtain the cause of the fault;
[0156] Determine the corresponding treatment suggestions for the cause of the fault;
[0157] The cause of the fault and the treatment suggestions are taken as the abnormal diagnosis results of the item to be tested.
[0158] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:
[0159] Obtaining operating data of the transformer corresponding to at least one item to be tested;
[0160] Analyze the status of each item to be tested based on the operating data and determine the corresponding operating status level of each item to be tested;
[0161] Perform fault diagnosis on each item to be detected based on the corresponding operating status level and operating data of each item to be detected, and obtain abnormal diagnosis results of each item to be detected;
[0162] According to the operating status level corresponding to each item to be detected and the abnormal diagnosis result of each item to be detected, the transformer monitoring result is fed back to the cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal according to the monitoring results.
[0163] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0164] For each item to be detected, obtain the data value range corresponding to each candidate status level corresponding to the item to be detected;
[0165] Determine the operating status level of the item to be tested based on the data value range and the operating data corresponding to the item to be tested.
[0166] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0167] Process the operating data corresponding to the test item to obtain target data;
[0168] The candidate state level whose data value range includes the target data is used as the operating state level corresponding to the item to be detected.
[0169] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0170] Clean the operating data corresponding to the test item to obtain cleaned operating data;
[0171] Perform data scoring processing on the cleaned operating data to obtain target data.
[0172] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0173] For each item to be tested, determine the fault diagnosis accuracy for the item to be tested according to the operating status level;
[0174] Perform fault diagnosis on each item to be tested based on the fault diagnosis accuracy and operation data to obtain abnormal diagnosis results of the item to be tested.
[0175] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0176] Perform fault diagnosis on each item to be tested based on its corresponding operating status level and operating data to obtain the cause of the fault;
[0177] Determine the corresponding treatment suggestions for the cause of the fault;
[0178] The cause of the fault and the treatment suggestions are taken as the abnormal diagnosis results of the item to be tested.
[0179] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:
[0180] Obtaining operating data of the transformer corresponding to at least one item to be tested;
[0181] Analyze the status of each item to be tested based on the operating data and determine the corresponding operating status level of each item to be tested;
[0182] Perform fault diagnosis on each item to be detected based on the corresponding operating status level and operating data of each item to be detected, and obtain abnormal diagnosis results of each item to be detected;
[0183] According to the operating status level corresponding to each item to be detected and the abnormal diagnosis result of each item to be detected, the transformer monitoring result is fed back to the cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal according to the monitoring results.
[0184] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0185] For each item to be detected, obtain the data value range corresponding to each candidate status level corresponding to the item to be detected;
[0186] Determine the operating status level of the item to be tested based on the data value range and the operating data corresponding to the item to be tested.
[0187] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0188] Process the operating data corresponding to the test item to obtain target data;
[0189] The candidate state level whose data value range includes the target data is used as the operating state level corresponding to the item to be detected.
[0190] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0191] Clean the operating data corresponding to the test item to obtain cleaned operating data;
[0192] Perform data scoring processing on the cleaned operating data to obtain target data.
[0193] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0194] For each item to be tested, determine the fault diagnosis accuracy for the item to be tested according to the operating status level;
[0195] Perform fault diagnosis on each item to be tested based on the fault diagnosis accuracy and operation data to obtain abnormal diagnosis results of the item to be tested.
[0196] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:
[0197] Perform fault diagnosis on each item to be tested based on its corresponding operating status level and operating data to obtain the cause of the fault;
[0198] Determine the corresponding treatment suggestions for the cause of the fault;
[0199] The cause of the fault and the treatment suggestions are taken as the abnormal diagnosis results of the item to be tested.
[0200] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions.
[0201] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.
[0202] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0203] The above embodiments merely illustrate several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.
Claims
1. A transformer data monitoring method, characterized in that: The method comprises: Obtaining operating data of the transformer corresponding to at least one item to be tested; Performing status analysis on each of the items to be detected based on the operating data to determine the operating status level corresponding to each of the items to be detected; Performing fault diagnosis on each of the items to be detected according to the operating status level corresponding to each of the items to be detected and the operating data, to obtain an abnormality diagnosis result for each of the items to be detected; According to the operating status level corresponding to each of the items to be detected and the abnormal diagnosis results of each item to be detected, the transformer monitoring results are fed back to the cloud server, so that the cloud server sends adjustment instructions for the transformer to the user terminal according to the monitoring results.
2. The method according to claim 1, characterized in that The performing status analysis on each of the items to be detected based on the operation data to determine the operation status level corresponding to each of the items to be detected includes: For each of the items to be detected, obtaining a data value range corresponding to each candidate status level corresponding to the item to be detected; The operating status level corresponding to the item to be detected is determined according to the data value range and the operating data corresponding to the item to be detected.
3. The method according to claim 2, characterized in that Determining the operating status level corresponding to the item to be detected based on the data value range and the operating data corresponding to the item to be detected includes: Processing the operating data corresponding to the item to be detected to obtain target data; The candidate state level whose data value range includes the target data is used as the running state level corresponding to the item to be detected.
4. The method according to claim 3, characterized in that The processing of the operating data corresponding to the item to be detected to obtain target data includes: Cleaning the operating data corresponding to the item to be detected to obtain cleaned operating data; The cleaned operating data is subjected to data scoring processing to obtain target data.
5. The method according to claim 1, wherein The performing fault diagnosis on each of the items to be detected based on the operating status level corresponding to each of the items to be detected and the operating data to obtain an abnormality diagnosis result for each of the items to be detected includes: For each of the items to be detected, determining the fault diagnosis accuracy of the item to be detected according to the operating status level; Fault diagnosis is performed on each of the items to be detected according to the fault diagnosis accuracy and the operating data to obtain an abnormality diagnosis result of the item to be detected.
6. The method according to claim 5, characterized in that The performing fault diagnosis on each of the items to be detected based on the operating status level corresponding to each of the items to be detected and the operating data to obtain an abnormality diagnosis result of the item to be detected includes: Performing fault diagnosis on each of the items to be detected according to the operating status level corresponding to each of the items to be detected and the operating data to obtain the cause of the fault of the item to be detected; Determine the corresponding treatment suggestions for the fault cause; The fault cause and the treatment suggestion are used as the abnormality diagnosis result of the item to be detected.
7. A transformer data monitoring device, characterized in that: The device comprises: An acquisition module, configured to acquire operating data of the transformer corresponding to at least one item to be detected; a determination module, configured to perform status analysis on each of the items to be detected based on the operation data, and determine an operation status level corresponding to each of the items to be detected; a diagnosis module, configured to perform fault diagnosis on each of the items to be detected based on the operating status level corresponding to each of the items to be detected and the operating data, and obtain an abnormality diagnosis result for each of the items to be detected; The feedback module is used to feed back the transformer monitoring results to the cloud server based on the operating status level corresponding to each of the items to be detected and the abnormal diagnosis results of each item to be detected, so that the cloud server can send adjustment instructions for the transformer to the user terminal based on the monitoring results.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.
10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.