Prejudgment transformer fault perception ability cultivation system based on infrared detection technology

Abstract

The invention discloses a pre-judgment transformer fault perception capability cultivation system based on an infrared detection technology, and the system comprises a fault checking and capability improvement module, a temperature rise detection device development module, and an intelligent early warning system development module. A transformer fault area is positioned by analyzing historical data and operation characteristics, practical teaching is carried out by using a developed infrared temperature detection device, theory and practice are combined, and the fault troubleshooting and maintenance capability of students is improved, and the invention relates to the technical field of power equipment detection and maintenance. According to the pre-judgment transformer fault perception ability cultivation system based on the infrared detection technology, a fault checking and ability improving module is arranged, a mode of combining theory and practice is utilized, the transformer fault diagnosis ability of a trainee in the inspection process is trained, the trainee not only understands the fault principle, but also has the actual operation ability, and the fault diagnosis ability of the trainee is improved. And professional operation and maintenance talents are cultivated for the power system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power equipment detection and maintenance, in particular to a pre-judgment transformer fault perception ability training system based on infrared detection technology. BACKGROUND

[0002] With the rapid development of economy, the demand for electricity remains on the rise, and the increasing scale of power grid and power generation capacity makes the capacity and voltage level of power transformers continue to improve. As primary equipment of power transmission and distribution system, the reliability of transformer is crucial to the safe and stable operation of power grid. However, in the harsh operating environment, various faults occur frequently, causing significant personal injury and equipment asset loss. During daily inspection, the inspector obtains the temperature rise information of the transformer and accurately finds various faults caused by transformer overheating, such as mechanical structure thermal expansion damage caused by local overheating in the transformer, accelerated aging of transformer component insulation materials caused by overheating, etc., which plays an important role in the stable operation of power transmission and distribution lines. Through the flexible installation of temperature rise detection device, the operation state and development trend of power transformer are mastered, and the temperature rise information is found in time, so as to realize accurate evaluation of the operation state of the transformer equipment, which is of great significance to ensure the safe and reliable operation of the equipment and improve the service life of the equipment.

[0003] However, in actual operation, the sensor equipment of the box-type transformer is often limited by the number and position of installation, and the global operation state of the transformer equipment cannot be obtained, which causes the power inspector to be unable to comprehensively judge the operation state of the transformer, affecting the improvement of the transformer inspection ability of the inspector. With the rapid development of computers and information technology and the integration of industrial internet and internet of things, it is almost universally recognized and applied to obtain the global operation state of the power transformer through digital technology. Therefore, the present application provides a pre-judgment transformer fault perception ability training system based on infrared detection technology. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a pre-judgment transformer fault perception ability training system based on infrared detection technology, which solves the problem that the sensor equipment of the box-type transformer is often limited by the number and position of installation, and the global operation state of the transformer equipment cannot be obtained, which causes the power inspector to be unable to comprehensively judge the operation state of the transformer, affecting the improvement of the transformer inspection ability of the inspector.

[0005] To achieve the above purpose, the present application is realized by the following technical scheme: The pre-judgment transformer fault perception ability training system based on infrared detection technology comprises a fault troubleshooting and ability improvement module, a temperature rise detection device development module and an intelligent early warning system development module. The troubleshooting and ability improvement module locates the transformer fault area by analyzing historical data and operation characteristics, carries out practical teaching by using an infrared temperature detection device, realizes the combination of theory and practice, and improves the troubleshooting and maintenance ability of students; The temperature rise detection device development module determines the key temperature monitoring area by studying the correlation between transformer power transformation and operation heat, completes the full-process development of the portable practical temperature measurement device from architecture, hardware, software to protection, and meets the detection and practical training needs; The intelligent early warning system development module establishes a temperature algorithm model by developing core algorithms for temperature measurement error compensation and data prediction, developing a supporting App software module and completing system integration, and realizes intelligent monitoring and early warning of transformer temperature.

[0006] Preferably, the fault feature research unit and the practical teaching application unit are included in the fault troubleshooting and ability improvement module.

[0007] Preferably, the fault feature research unit analyzes transformer historical operation data and inspection records, excavates equipment operation rules, locates key areas and key points prone to faults, and provides direction guidance for subsequent fault troubleshooting.

[0008] Preferably, the practical teaching application unit uses an infrared temperature detection device to carry out practical operation, and verifies experimental detection and theoretical learning with each other, realizing the organic combination of theoretical knowledge and practical skills.

[0009] Preferably, the temperature rise detection device development module includes a monitoring law research unit and a device development implementation unit.

[0010] Preferably, the monitoring law research unit studies the correlation between transformer power transformation and equipment operation heat according to inspection training requirements, analyzes probability distribution rules, and thus determines the key temperature monitoring area, laying a foundation for device development.

[0011] Preferably, the device development implementation unit is responsible for completing the full-process work from hardware architecture design, hardware principle design, PCB design, to temperature data acquisition and transmission application software development, protection device design and manufacturing, and finally forming a portable practical temperature measurement device to meet the needs of box-type transformer temperature detection and practical training.

[0012] Preferably, the intelligent early warning system development module includes a core algorithm development unit and a software application development unit.

[0013] Preferably, the core algorithm development unit develops temperature measurement error compensation and temperature data prediction methods to realize key area temperature fault point excavation, out-of-limit intelligent early warning and key part temperature trend automatic analysis of the box-type transformer.

[0014] Preferably, the software application development unit develops a digital dynamic temperature monitoring and early warning App software module for key parts of a box-type transformer, and integrates the core algorithm with the module to realize real-time monitoring and intelligent early warning of the temperature state of the transformer.

[0015] The application provides a transformer fault prediction and perception ability training system based on infrared detection technology. 1. The transformer fault prediction and perception ability training system based on infrared detection technology is provided with a fault troubleshooting and ability improvement module, which trains the trainees' transformer fault diagnosis ability in the inspection process by combining theory with practice, so that the trainees not only understand the fault principle, but also have practical operation ability, thereby cultivating professional operation and maintenance personnel for the power system.

[0016] 2. The transformer fault prediction and perception ability training system based on infrared detection technology is provided with a temperature rise detection device development module, which develops a portable transformer temperature rise detection device through innovative design. The device covers architecture design, hardware principle design, software development and multiple links, and can accurately measure the temperature change of the key parts of the transformer. In actual application, on the one hand, the detection device installation and detection position can be adjusted conveniently through magnetic attraction for the trainees' practical teaching; on the other hand, the device also meets the needs of on-site temperature monitoring of the box-type transformer, and provides reliable basis for the operation state evaluation of the equipment by acquiring temperature data in real time.

[0017] 3. The transformer fault prediction and perception ability training system based on infrared detection technology is provided with an intelligent early warning system development module. The developed App software can realize transmission, analysis and sharing of temperature data, can preliminarily judge the detection data, and can assist the trainees in improving practical ability. Moreover, the temperature data of the key parts of the transformer can be monitored in real time, abnormal temperature change can be quickly identified and intelligently warned, the timeliness and accuracy of the transformer fault warning are greatly improved, the operation and maintenance personnel can take measures in advance to prevent faults, reduce equipment downtime and maintenance cost, and ensure the stable operation of the power system. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 It is a principle block diagram of the application; Figure 2 It is a principle block diagram of the fault troubleshooting and ability improvement module of the application; Figure 3 It is a principle block diagram of the temperature rise detection device development module of the application; Figure 4 It is a principle block diagram of the intelligent early warning system development module of the application; Figure 5The box-type transformer temperature point schematic diagram of the present application.

[0019] In the figure: 1 - troubleshooting and ability improvement module, 11 - fault feature research unit, 12 - practical teaching application unit, 2 - temperature rise detection device development module, 21 - monitoring law research unit, 22 - device development implementation unit, 3 - intelligent early warning system development module, 31 - core algorithm development unit, 32 - software application development unit. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0021] Please refer to Figures 1-5 The present application provides a technical solution: The pre-judgment transformer fault perception ability training system based on infrared detection technology comprises a fault troubleshooting and ability improvement module 1, a temperature rise detection device development module 2, and an intelligent early warning system development module 3. The fault troubleshooting and ability improvement module 1 locates the transformer fault area by analyzing historical data and operating characteristics, develops practical teaching using the developed infrared temperature detection device, realizes the combination of theory and practice, and improves the fault troubleshooting and maintenance ability of the students. The temperature rise detection device development module 2 determines the key temperature monitoring area by studying the correlation between transformer power and operating heat, completes the full-process development of the portable practical training temperature measurement device from architecture, hardware, software to protection, and meets the detection and practical training needs. The intelligent early warning system development module 3 develops the core algorithms of temperature measurement error compensation and data prediction, establishes a temperature algorithm model combined with edge technology, develops a supporting App software and completes system integration, and realizes intelligent monitoring and early warning of transformer temperature.

[0022] The portable practical training temperature measurement device can conveniently adjust the installation and detection position of the detection device according to the operating characteristics of the actual equipment, and conveniently verify the diagnosis result of the transformer for the trainees.

[0023] In the embodiments of the present application, the fault troubleshooting and ability improvement module 1 comprises a fault feature research unit 11 and a practical teaching application unit 12.

[0024] In the embodiment of the present application, the fault feature research unit 11 can accurately locate the key areas and key points prone to failure by deeply analyzing the historical operation data and inspection records of the transformer, and mining the operation rules of the equipment, thereby providing direction guidance for subsequent fault troubleshooting.

[0025] In the embodiment of the present application, the practical teaching application unit 12 uses the infrared temperature detection device developed by the project to carry out practical operation, and verifies the experimental detection and theoretical learning with each other, thereby realizing the organic combination of theoretical knowledge and practical skills.

[0026] By setting the fault troubleshooting and ability improvement module 1, the trainees can improve their transformer fault diagnosis ability in the inspection process by using the combination of theory and practice, so that the trainees not only understand the fault principle, but also have practical operation ability, thereby cultivating professional operation and maintenance personnel for the power system.

[0027] In the embodiment of the present application, the temperature rise detection device development module 2 includes a monitoring law research unit 21 and a device development implementation unit 22.

[0028] In the embodiment of the present application, the monitoring law research unit 21 deeply studies the correlation between the transformer power transformation and the equipment operation heat according to the inspection training requirements, analyzes the probability distribution law, and thereby determines the key area of temperature monitoring, thereby laying a foundation for device development.

[0029] In the embodiment of the present application, the device development implementation unit 22 is responsible for completing the whole process work from hardware architecture design, hardware principle design, PCB board design, to temperature data acquisition and transmission application software development, protection device design and manufacturing, and finally forms a portable practical temperature measurement device to meet the needs of temperature detection and practical training of the box-type transformer.

[0030] By setting the temperature rise detection device development module 2, a portable transformer temperature rise detection device is innovatively designed, which covers architecture design, hardware principle design, software development and other links, can accurately measure the temperature change of the key parts of the transformer, and in actual application, on the one hand, it can be used for practical teaching of trainees, and the detection device installation and detection position can be adjusted conveniently through magnetic attraction; on the other hand, it also meets the needs of on-site temperature monitoring of the box-type transformer, and provides reliable basis for the operation state evaluation of the equipment by acquiring temperature data in real time.

[0031] In the embodiment of the present application, the intelligent early warning system development module 3 includes a core algorithm development unit 31 and a software application development unit 32: The core algorithm development unit 31 can realize the mining of temperature fault points of key areas of the box-type transformer, intelligent early warning of over-limit and automatic analysis of temperature trends of key parts by developing the methods of temperature measurement error compensation and temperature data prediction. The software application development unit 32 develops an App software for monitoring and early warning of the key part of the box-type transformer in a digital dynamic temperature mode, integrates the core algorithm with the App software, and realizes real-time monitoring and intelligent early warning of the temperature state of the transformer.

[0032] By setting the intelligent early warning system development module 3, the developed App software can realize transmission, analysis and sharing of temperature data, preliminary judgment of test data, and improvement of practical ability of assistant trainees. In addition, the temperature data of the key part of the transformer can be monitored in real time, abnormal temperature changes can be quickly identified and intelligently warned, the timeliness and accuracy of the transformer fault warning are greatly improved, the operation and maintenance personnel can take measures in advance to prevent faults, reduce equipment downtime and maintenance costs, and ensure the stable operation of the power system.

[0033] Meanwhile, the contents not described in detail in the specification are all the existing technologies known to those skilled in the art.

[0034] The specific implementation is as follows: Characteristic research and analysis: Collect technical data of transformers of different models and service life, including structural drawings, rated parameters, operation and maintenance records, etc., establish a transformer information database, select 3-5 typical transformers in a transformer substation, install high-precision sensors, and monitor parameters such as voltage, current, load rate, oil temperature, and winding temperature in real time during operation. Collect data for 1-3 months, use data analysis software such as MATLAB, analyze the correlation between data from aspects such as transformer structural characteristics (such as winding turns, core material), operation characteristics (such as load change law, start-stop frequency), and detection parameter characteristics (such as temperature distribution, vibration signal), and summarize the characteristics of transformer temperature rise; Hardware device development: According to the analysis results, design a hardware device architecture suitable for transformer temperature detection, determine the sensor layout, signal transmission method, data processing module, and other components, select appropriate components such as high-precision temperature sensors, signal amplifiers, and microcontrollers, draw the hardware circuit schematic, use software such as AltiumDesigner for PCB design, and complete the production and welding of the circuit board; Fault point and temperature rise characteristic determination: According to the transformer loss characteristics (such as copper loss and iron loss), simulate the internal heat conduction process of the transformer by using finite element analysis software, determine the parts prone to faults and the temperature rise change law, combine historical fault data and actual detection, determine the junction temperature points of the transformer test, such as the winding joint, the core lamination joint, etc. as the key monitoring points, and determine the temperature range of each point under normal operation and fault state; Probe research and comparison: In-depth study of the working principle and technical parameters of thermistor probes and photon probes, build a test platform, test the performance of the two probes, test the temperature measurement accuracy, response time, stability and other indicators of the two probes under different temperature environments (-20℃-80℃) and humidity conditions (20%-90%RH), compare and analyze their advantages and disadvantages, evaluate the feasibility of replacing thermistor probes with photon probes based on the characteristics of transformer operating environment and detection requirements, and determine the final probe type; Circuit development: According to the characteristics of the selected photon probe, design the matching temperature sensor circuit, including photoelectric conversion circuit, preamplifier circuit, filter circuit, etc., realize the conversion of optical signal to electrical signal, develop key signal processing circuits, amplify, filter, A / D convert and other processes for the converted electrical signal, improve signal quality and data acquisition accuracy, write sensor driver program, realize communication with data processing module, and ensure accurate transmission of temperature data; Signal processing: Using edge computing technology, pre-process the collected temperature voltage signal on the hardware device side, remove noise interference through filtering algorithm, improve signal purity, use digital signal processing technology to amplify, shape, normalize and other processes for the signal, so that it meets the requirements of subsequent algorithm calculation; Algorithm model establishment: Comprehensive use of two-dimensional interpolation method, Spline interpolation algorithm and least squares algorithm, combined with actual transformer operation data, establish temperature algorithm model, use a large amount of historical temperature data to train and optimize the model, adjust model parameters, so that the temperature error calculated by the model meets the design requirement of temperature measurement accuracy (such as ±0.5℃); Hardware device development and integration: According to the algorithm model and signal processing requirements, perfect the design of infrared temperature detection hardware device, including power module, data storage module, communication module, etc., integrate temperature sensor circuit, signal processing circuit, algorithm module, etc., make a complete infrared temperature detection hardware device, test the function and performance of the hardware device, ensure the normal operation of the device; Itemized test: Temperature measurement accuracy test: Place the infrared temperature detection device in a high-low temperature environment test chamber, set different temperature points (such as -25℃, 0℃, 25℃, 50℃, 75℃), compare and test with high-precision standard thermometer, record measurement error, analyze the static temperature measurement accuracy of the device under high-low temperature environment, electromagnetic compatibility test: Test the electromagnetic compatibility of each device in the temperature measurement system, including anti-interference test (such as electrostatic discharge immunity, radio frequency electromagnetic field radiation immunity) and emission test (such as conducted emission, radiated emission), ensure the normal work of the device in complex electromagnetic environment; Whole system test: install the infrared temperature detection device on the box-type transformer, simulate the actual operation condition, carry out long-time continuous monitoring, collect the temperature data of each key position of the transformer, analyze and process the collected data, verify the overall performance of the device, including the accuracy, stability of data collection, reliability of signal transmission, and real-time performance of the system, etc. Optimization and improvement of the device, according to the test results, analyze the problems and deficiencies of the device, such as large temperature measurement error, electromagnetic compatibility not up to standard, etc., optimize and improve the device according to the problems, adjust the hardware circuit parameters, improve the software algorithm, optimize the device structure, etc., test again until the device performance meets the design requirements, improve the applicability of the device.

[0035] It should be noted that in this text, relational terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device.

[0036] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A system for cultivating the ability to predict transformer faults based on infrared detection technology, characterized by, It comprises a fault troubleshooting and ability improvement module (1), a temperature rise detection device development module (2) and an intelligent early warning system development module (3): The fault troubleshooting and ability improvement module (1) locates the transformer fault area by analyzing historical data and operation characteristics, carries out practical teaching by using an infrared temperature detection device, realizes the combination of theory and practice, and improves the fault troubleshooting and maintenance ability of students; The temperature rise detection device development module (2) determines the key temperature monitoring area by studying the correlation between transformer power and operating heat, completes the whole process development of the portable practical temperature measurement device from architecture, hardware, software to protection, and meets the detection and practical training needs; The intelligent early warning system development module (3) develops the core algorithms of temperature measurement error compensation and data prediction, establishes a temperature algorithm model combined with edge technology, develops a supporting App software module and completes system integration, and realizes intelligent monitoring and early warning of transformer temperature.

2. The system for training the ability of transformer fault perception based on infrared detection technology according to claim 1, characterized in that: The fault troubleshooting and ability improvement module (1) comprises a fault characteristic research unit (11) and a practical teaching application unit (12). 3.The system of claim 2, wherein the system further comprises: a first infrared ray detector configured to detect a first infrared ray emitted from the transformer; a second infrared ray detector configured to detect a second infrared ray emitted from the transformer; and a third infrared ray detector configured to detect a third infrared ray emitted from the transformer. The fault characteristic research unit (11) analyzes transformer historical operation data and inspection records, excavates equipment operation rules, accurately locates key areas and key points prone to faults, and provides direction guidance for subsequent fault troubleshooting. 4.The system of claim 2, wherein the system further comprises: a first infrared ray detector configured to detect a first infrared ray emitted from the transformer; a second infrared ray detector configured to detect a second infrared ray emitted from the transformer; and a third infrared ray detector configured to detect a third infrared ray emitted from the transformer. The practical teaching application unit (12) uses an infrared temperature detection device to carry out practical operation, and verifies experimental detection and theoretical learning with each other, realizing the organic combination of theoretical knowledge and practical skills. 5.The system of claim 1, wherein the system further comprises: a transformer fault detection device configured to detect a fault of the transformer; and a transformer fault detection device configured to detect a fault of the transformer. The temperature rise detection device development module (2) comprises a monitoring law research unit (21) and a device development implementation unit (22). 6.The system of claim 5, wherein the system further comprises: a first infrared ray detector configured to detect a first infrared ray emitted from the transformer; a second infrared ray detector configured to detect a second infrared ray emitted from the transformer; and a third infrared ray detector configured to detect a third infrared ray emitted from the transformer. The monitoring law research unit (21) studies the correlation between transformer power and equipment operating heat according to inspection training requirements, analyzes probability distribution law, and thus determines the key area of temperature monitoring, laying a foundation for device development. 7.The system of claim 5, wherein the system further comprises: a first infrared ray detector configured to detect a first infrared ray emitted from the transformer; a second infrared ray detector configured to detect a second infrared ray emitted from the transformer; and a third infrared ray detector configured to detect a third infrared ray emitted from the transformer. The device development implementation unit (22) is responsible for completing the whole process work from hardware architecture design, hardware principle design, PCB board design, to temperature data acquisition and transmission application software development, protection device design and manufacturing, and finally forming a portable practical temperature measurement device to meet the needs of box-type transformer temperature detection and practical training. 8.The system of claim 1, wherein the system further comprises: a transformer fault detection device configured to detect a fault of the transformer. The intelligent early warning system development module (3) comprises a core algorithm development unit (31) and a software application development unit (32). 9.The system of claim 8, wherein the system further comprises: a transformer fault detection device configured to detect a fault of the transformer. The core algorithm development unit (31) develops temperature measurement error compensation and temperature data prediction methods to realize the excavation of key area temperature fault points of box-type transformers, intelligent early warning of over-limit and automatic analysis of temperature trends of key parts. 10.The system of claim 8, wherein the system further comprises: a transformer fault detection device configured to detect a fault of the transformer. The software application development unit (32) develops a box-type transformer key part digital dynamic temperature monitoring and early warning App software module, integrates the core algorithm, and realizes real-time monitoring and intelligent early warning of transformer temperature state.

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