A transformer data monitoring system and method

Abstract

The present application discloses a transformer data monitoring system and method, mainly relating to the technical field of transformer monitoring, and is used to solve the problem that the existing analysis methods cannot perform time series analysis on transformer data. It includes: an anomaly detection module, which is used to obtain a time-frequency distribution map; obtain the preset reference distribution map with the highest fitting degree corresponding to the time-frequency distribution map; determine whether the preset reference distribution map corresponds to abnormal current; a data analysis module, which is used to send electrical parameter data to a data processing module; a data processing module, which is used to perform content numerical processing on the electrical parameter data and convert the electrical parameter data into numerical parameter data; obtain a parameter curve graph of the data parameter data, and obtain the preset curve graph with the highest fitting degree corresponding to the parameter curve graph; and further obtain a preset anomaly conclusion corresponding to the preset curve graph. Through the above method, the present application realizes the time series analysis of data and realizes the rapid detection of transformer anomalies.

Description

Technical Field

[0001] This application relates to the technical field of transformer monitoring, and particularly to a transformer data monitoring system and method. Background Art

[0002] A transformer is a device that uses the principle of electromagnetic induction to change the AC voltage. Its main functions include: voltage transformation, current transformation, impedance transformation, isolation, voltage stabilization (magnetic saturation transformer), etc. Transformers are basic power transmission and distribution equipment and are widely used in industries, agriculture, transportation, urban communities and other fields.

[0003] At present, the normal operation of a transformer is mainly monitored through the joint operation of monitoring devices, servers, and monitoring background software. Among them, the monitoring devices are temperature sensors and three-phase acquisition modules installed on site, which are connected to a 485 line and a 4G / Ethernet collector. The on-site data can be transmitted back to the server. The server is specifically used to store monitoring data. The monitoring background software is responsible for collecting data, viewing real-time data, querying alarms, etc.

[0004] However, since the existing method can only analyze the real-time data of the transformer, the analysis conclusions obtained from the real-time data are less reliable, and time series analysis of the transformer data cannot be achieved. Summary of the Invention

[0005] In view of the above deficiencies of the prior art, the present invention provides a transformer data monitoring system and method to solve the above technical problems.

[0006] In a first aspect, the present application provides a transformer data monitoring system, which includes: an anomaly detection module, configured to obtain a standard injury current and a measured injury current uploaded by a plurality of transformers; import the difference injury current between the standard injury current and the measured injury current into a joint time-frequency analysis algorithm to obtain a time-frequency distribution map; obtain the preset reference distribution map with the highest fitting degree corresponding to the time-frequency distribution map; determine whether the preset reference distribution map corresponds to an abnormal current; a data analysis module, configured to, when determining that the reference distribution map corresponds to an abnormal current, obtain the electrical parameter data and location data corresponding to the transformer; determine the corresponding data processing module based on the location data; and then send the electrical parameter data to the data processing module; the data processing module is configured to perform content numerical processing on the electrical parameter data, convert the electrical parameter data into numerical parameter data; obtain a parameter curve graph of the numerical parameter data, obtain the preset curve graph with the highest fitting degree corresponding to the parameter curve graph; and then obtain the preset abnormal conclusion corresponding to the preset curve graph.

[0007] Further, the anomaly detection module further includes an injury current acquisition unit; the injury current acquisition unit is configured to obtain the transfer function corresponding to the transformer under a preset impact voltage; import twice the impact voltage into the transfer function to obtain the standard injury current.

[0008] Further, the data analysis module includes: a data processing module determination unit; the data processing module determination unit is configured to obtain location data, determine a transmission area corresponding to the location data; send a data distribution instruction to all servers within the transmission area, and determine the server that responds first as the data processing module; wherein, the transmission area is an area centered on the location data with a preset distance as the radius.

[0009] Further, the data processing module includes: a numerical processing unit; the numerical processing unit is configured to obtain electrical parameter data composed of several groups of data; determine preset data corresponding to each group of data through a keyword extraction algorithm, and then obtain INT data corresponding to each group of data through a preset data-INT database to obtain numerical parameter data.

[0010] In a second aspect, the present application provides a method for monitoring transformer data. The method includes: obtaining a standard injury current and obtaining measurement injury currents uploaded by several transformers; importing the difference injury current between the standard injury current and the measurement injury current into a joint time-frequency analysis algorithm to obtain a time-frequency distribution diagram; obtaining the preset reference distribution diagram with the highest fitting degree corresponding to the time-frequency distribution diagram; determining whether the preset reference distribution diagram corresponds to an abnormal current; when it is determined that the reference distribution diagram corresponds to an abnormal current, obtaining electrical parameter data and location data corresponding to the transformer; determining a corresponding data analysis device based on the location data; and then sending the electrical parameter data to the data analysis device; performing content numerical processing on the electrical parameter data through the data analysis device to convert the electrical parameter data into numerical parameter data; obtaining a parameter curve diagram of the numerical parameter data, obtaining the preset curve diagram with the highest fitting degree corresponding to the parameter curve diagram; and then obtaining a preset abnormal conclusion corresponding to the preset curve diagram.

[0011] Further, obtaining the standard injury current specifically includes: obtaining the transfer function corresponding to the transformer under a preset impact voltage; importing twice the impact voltage into the transfer function to obtain the standard injury current.

[0012] Further, determining a corresponding data analysis device based on the location data specifically includes: obtaining location data, determining a transmission area corresponding to the location data; sending a data distribution instruction to all servers within the transmission area, and determining the server that responds first as the data analysis device; wherein, the transmission area is an area centered on the location data with a preset distance as the radius.

[0013] Further, converting the electrical parameter data into numerical parameter data specifically includes: obtaining electrical parameter data composed of several groups of data; determining a preset data-INT database corresponding to each group of data through a keyword extraction algorithm to respectively obtain INT data corresponding to each group of data, and then obtaining numerical parameter data.

[0014] Those skilled in the art can understand that the present invention has at least the following beneficial effects: Through the anomaly detection module, it is possible to quickly detect whether there is an abnormal transformer without the participation of other various data, improving the acquisition efficiency of abnormal data. Through the data analysis module, it is possible to reasonably allocate processing servers (data processing modules), reducing the time consumption of data analysis. Through the data processing module, it is possible to quickly and effectively analyze data and quickly detect whether the transformer is abnormal. And through joint time-frequency analysis, the one-dimensional frequency domain signal is mapped onto a two-dimensional plane to reflect the time-frequency joint characteristics, realizing the time series analysis of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The following describes some embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0016] Figure 1 is a schematic diagram of the internal structure of a transformer data monitoring system provided by an embodiment of the present application.

[0017] Figure 2 is a flowchart of a transformer data monitoring method provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Those skilled in the art should understand that the embodiments described below are only the preferred embodiments of the present disclosure, and do not mean that the present disclosure can only be implemented through these preferred embodiments. These preferred embodiments are only used to explain the technical principles of the present disclosure and are not used to limit the protection scope of the present disclosure. Based on the preferred embodiments provided by the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts should still fall within the protection scope of the present disclosure.

[0019] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, commodity or device including the element.

[0020] The technical solutions proposed in the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0021] Figure 1 is a transformer data monitoring system provided by an embodiment of the present application. As Figure 1As shown in the figure, the system provided by the embodiment of the present application mainly includes: an anomaly detection module 110, a data analysis module 120, and a data processing module 130.

[0022] When monitoring transformer data, first, the anomaly detection module 110 (any feasible device or apparatus capable of performing anomaly detection, etc.) is used to obtain the standard injury current and several measured injury currents uploaded by the transformers; the difference injury current between the standard injury current and the measured injury current is imported into the joint time-frequency analysis algorithm to obtain a time-frequency distribution map; the preset reference distribution map with the highest fitting degree corresponding to the time-frequency distribution map is obtained; it is determined whether the preset reference distribution map corresponds to an abnormal current.

[0023] The joint time-frequency analysis here is used to map the one-dimensional frequency-domain signal to a two-dimensional plane with a time series to reflect the time-frequency joint characteristics of the non-stationary signal. The joint time-frequency analysis algorithm is any feasible algorithm capable of obtaining a time-frequency distribution map. As an example, the difference injury current is converted into a frequency-domain signal through the short-time Fourier transform, and a time-frequency distribution map is constructed with the frequency-domain signal as the vertical axis and the acquisition time of the difference injury current as the horizontal axis.

[0024] It should be noted that the method for obtaining the standard injury current can be obtained through a preset acquisition interface or calculated through an algorithm. Among them, "calculated through an algorithm" can be specifically: the transfer function corresponding to the transformer under the preset impact voltage is obtained through the injury current acquisition unit 111 in the anomaly detection module 110; then, twice the impact voltage is imported into the transfer function to obtain the standard injury current. Among them, "obtaining the transfer function corresponding to the transformer under the preset impact voltage" can be specifically: several preset impact voltages are input into the transformer, and several injury currents fed back by the transformer are obtained; several preset impact voltages, injury currents, and the corresponding relationship between them are imported into any neural learning algorithm to obtain the function between the preset impact voltage and the injury current, and then this function is set as the transfer function.

[0025] It should be noted that the anomaly detection module 110 stores several experimental reference distribution maps and the preset experimental conditions corresponding to the experimental reference distribution maps. Among them, the experimental reference distribution map can be the experimental time-frequency distribution map obtained by those skilled in the art under the preset experimental conditions. The preset experimental conditions are divided into: normal current conditions and abnormal current conditions. The above "obtaining the preset reference distribution map with the highest fitting degree" can be specifically: the time-frequency distribution map and several experimental reference distribution maps are imported into MATLAB, and the image similarity between the time-frequency distribution map and several experimental reference distribution maps is obtained through MATLAB, and the experimental reference distribution map with the highest similarity is determined as the preset reference distribution map with the highest fitting degree. After obtaining the preset reference distribution map with the highest fitting degree, it is checked whether the preset experimental conditions corresponding to the preset reference distribution map are abnormal current conditions.

[0026] When determining the abnormal current corresponding to the reference distribution diagram, the data analysis module 120 (any feasible device or apparatus capable of receiving data, etc.) acquires the electrical parameter data and position data corresponding to the transformer; determines the corresponding data processing module 130 based on the position data; and then sends the electrical parameter data to the data processing module 130.

[0027] It should be noted that "determining the corresponding data processing module 130 based on the position data" can be specifically: obtaining the position data through the data processing module determination unit 121 in the data analysis module 120, determining the sending area corresponding to the position data; sending a data distribution instruction to all servers within the sending area, and determining the first-responsive server as the data processing module 130; where the sending area is an area centered on the position data with a preset distance as the radius. The preset distance can be any feasible distance.

[0028] After the data processing module 130 obtains the electrical parameter data, the data processing module 130 performs content numerical processing on the electrical parameter data to convert the electrical parameter data into numerical parameter data; obtains the parameter curve graph of the numerical parameter data, and obtains the preset curve graph with the highest fitting degree corresponding to the parameter curve graph; and then obtains the preset abnormal conclusion corresponding to the preset curve graph.

[0029] Among them, "performing content numerical processing on the electrical parameter data to convert the electrical parameter data into numerical parameter data" can be specifically: obtaining the electrical parameter data composed of several groups of data through the numerical processing unit 131 in the data processing module 130; determining the preset data corresponding to each group of data through the keyword extraction algorithm, and then obtaining the INT data corresponding to each group of data through the preset data-INT database, so as to realize the conversion of the electrical parameter data into numerical parameter data. It should be noted that the preset data-INT database stores the corresponding relationship between the preset data and the INT value. Here, the INT data is integer numerical data (int type data), and the corresponding relationship can be obtained by those skilled in the art through multiple experiments.

[0030] In addition, the embodiment of the present application also provides a transformer data monitoring method, as Figure 2 shown, the method provided by the embodiment of the present application mainly includes the following steps:

[0031] Step 210, obtaining the standard injury current, and obtaining the measured injury currents uploaded by several transformers; importing the difference injury current between the standard injury current and the measured injury current into the joint time-frequency analysis algorithm to obtain a time-frequency distribution diagram; obtaining the preset reference distribution diagram with the highest fitting degree corresponding to the time-frequency distribution diagram; and determining whether the preset reference distribution diagram corresponds to an abnormal current.

[0032] Among them, obtaining the standard fault current can be specifically: obtaining the transfer function corresponding to the transformer under a preset impact voltage; introducing twice the impact voltage into the transfer function to obtain the standard fault current.

[0033] Step 220, when determining the abnormal current corresponding to the reference distribution diagram, obtain the electrical parameter data and position data corresponding to the transformer; determine the corresponding data analysis device based on the position data; and then send the electrical parameter data to the data analysis device.

[0034] Among them, determining the corresponding data analysis device based on the position data can be specifically: obtaining the position data, determining the sending area corresponding to the position data; sending a data distribution instruction to all servers within the sending area, and determining the server that responds first as the data analysis device; where the sending area is an area centered on the position data with a preset distance as the radius.

[0035] Step 230, perform content numerical processing on the electrical parameter data through the data analysis device, convert the electrical parameter data into numerical parameter data; obtain the parameter curve graph of the numerical parameter data, obtain the preset curve graph with the highest fitting degree corresponding to the parameter curve graph; and then obtain the preset abnormal conclusion corresponding to the preset curve graph.

[0036] Among them, converting the electrical parameter data into numerical parameter data can be specifically: obtaining the electrical parameter data composed of several groups of data; through the keyword extraction algorithm, determine the preset data-INT database corresponding to each group of data, respectively obtain the INT data corresponding to each group of data, and then obtain the numerical parameter data.

[0037] So far, the technical solutions of the present disclosure have been described in combination with multiple previous embodiments. However, it is easy for those skilled in the art to understand that the protection scope of the present disclosure is not limited to these specific embodiments. Without departing from the technical principle of the present disclosure, those skilled in the art can split and combine the technical solutions in the above-mentioned various embodiments, and can also make equivalent changes or replacements to the relevant technical features. Any changes, equivalent replacements, improvements, etc. made within the technical concept and / or technical principle of the present disclosure will fall within the protection scope of the present disclosure.

Claims

1. A transformer data monitoring system, characterized in that, The system includes: An anomaly detection module, configured to obtain a standard injury indication current and obtain measurement injury indication currents uploaded by a plurality of transformers; import the difference injury indication current between the standard injury indication current and the measurement injury indication currents into a joint time-frequency analysis algorithm to obtain a time-frequency distribution map; obtain the preset reference distribution map with the highest fitting degree corresponding to the time-frequency distribution map; determine whether the preset reference distribution map corresponds to an abnormal current; A data analysis module, configured to obtain electrical parameter data and location data corresponding to a transformer when it is determined that the reference distribution map corresponds to an abnormal current; determine the corresponding data processing module based on the location data; and then send the electrical parameter data to the data processing module; A data processing module, configured to perform content numerical processing on the electrical parameter data, convert the electrical parameter data into numerical parameter data; obtain a parameter curve graph of the numerical parameter data, obtain the preset curve graph with the highest fitting degree corresponding to the parameter curve graph; and then obtain the preset abnormal conclusion corresponding to the preset curve graph.

2. The transformer data monitoring system according to claim 1, characterized in that, The anomaly detection module further includes an injury indication current acquisition unit; The injury indication current acquisition unit is configured to obtain the transfer function corresponding to a transformer under a preset impact voltage; import twice the impact voltage into the transfer function to obtain a standard injury indication current.

3. The transformer data monitoring system according to claim 1, characterized in that, The data analysis module includes: a data processing module determination unit; The data processing module determination unit is configured to obtain location data, determine the sending area corresponding to the location data; send a data distribution instruction to all servers within the sending area, and determine the first-responsive server as the data processing module; wherein, the sending area is an area centered on the location data with a preset distance as the radius.

4. The transformer data monitoring system according to claim 1, characterized in that, The data processing module includes: a numerical processing unit; The numerical processing unit is configured to obtain electrical parameter data composed of several groups of data; determine the preset data corresponding to each group of data through a keyword extraction algorithm, and then obtain the INT data corresponding to each group of data through a preset data-INT database to obtain numerical parameter data.

5. A transformer data monitoring method, characterized in that, The method includes: Obtain a standard injury indication current and obtain measurement injury indication currents uploaded by a plurality of transformers; import the difference injury indication current between the standard injury indication current and the measurement injury indication currents into a joint time-frequency analysis algorithm to obtain a time-frequency distribution map; obtain the preset reference distribution map with the highest fitting degree corresponding to the time-frequency distribution map; determine whether the preset reference distribution map corresponds to an abnormal current; When it is determined that the reference distribution map corresponds to an abnormal current, obtain electrical parameter data and location data corresponding to a transformer; determine the corresponding data analysis device based on the location data; and then send the electrical parameter data to the data analysis device; Perform content numerical processing on the electrical parameter data through a data analysis device, convert the electrical parameter data into numerical parameter data; obtain a parameter curve graph of the numerical parameter data, obtain the preset curve graph with the highest fitting degree corresponding to the parameter curve graph; and then obtain the preset abnormal conclusion corresponding to the preset curve graph.

6. The transformer data monitoring method according to claim 5, characterized in that, Obtaining the standard injury indication current specifically includes: Obtain the transfer function corresponding to the transformer under a preset impulse voltage; import twice the impulse voltage into the transfer function to obtain a standard injury indication current.

7. The transformer data monitoring method according to claim 5, characterized in that, Determine the corresponding data analysis device based on the position data, specifically including: Obtain position data, determine the sending area corresponding to the position data; send a data distribution instruction to all servers within the sending area, and determine the server that responds first as the data analysis device; wherein, the sending area is an area centered on the position data with a preset distance as the radius.

8. The transformer data monitoring method according to claim 5, characterized in that, Convert the electrical parameter data into numerical parameter data, specifically including: Obtain electrical parameter data composed of several groups of data; through a keyword extraction algorithm, determine the preset data - INT database corresponding to each group of data to respectively obtain the INT data corresponding to each group of data, and further obtain numerical parameter data.

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