Extra-high voltage transformer fault detection method

Abstract

The invention discloses an extra-high voltage transformer fault detection method, which comprises the following steps: S1, detection preparation: evaluating the environment around a transformer, ensuring that no external heat source interferes with a thermal imaging result, and determining an optimal shooting angle and distance according to the structural characteristics of the transformer; s2, real-time monitoring: scanning and shooting the transformer by using a thermal imager, recording the temperature distribution condition of the transformer, collecting image information generated by the thermal imager in real time by a data acquisition module, and transmitting the image information to a data processing module; and S3, data analysis and processing: a data processing module performs image processing, removes background noise, highlights possible overheat points, compares current detection data with a preset safety threshold and historical data, judges whether temperature abnormity exists or not, and gives an alarm in time by an alarm unit when a dangerous-level temperature is detected. According to the invention, possible internal faults of the transformer can be detected, an alarm can be given in time, the use safety is improved, the detection accuracy of the transformer is improved, and the cost and error of manual inspection are reduced at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of transformer fault detection, and specifically to a method for detecting faults in extra-high voltage transformers. Background Technique

[0002] Power transformers are one of the important components of the power system. Ensuring their safe operation is very important. Once a fault occurs, it will affect the operation status of the power grid. Therefore, it is necessary to effectively monitor transformers. Due to the complex working environment of transformers, the fault detection of them is easily affected by external interference, resulting in inaccurate detection results.

[0003] At present, distribution transformers adopt manual inspections, supplemented by tools such as temperature guns to measure the temperature of key parts for comparison to judge whether the operation is normal. However, the actual distribution points of distribution transformers are numerous and widely distributed, resulting in the following problems in on-site operations: The distribution points of transformers are numerous and widely distributed, and the work efficiency of maintenance personnel is relatively low. Using the manual inspection method not only greatly increases the work intensity of the staff, but also has a long inspection cycle and cannot detect problems in time, which needs to be improved. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the existing defects, provide a method for detecting faults in extra-high voltage transformers, realize the detection of possible internal faults in transformers, give an alarm in time, improve the use safety, improve the detection accuracy rate of transformers, and at the same time reduce the cost and error of manual inspections, and can effectively solve the problems in the background technique.

[0005] To achieve the above object, the present invention provides the following technical solution: A method for detecting faults in extra-high voltage transformers, including the following steps: S1. Detection preparation: Evaluate the environment around the transformer to ensure that there is no external heat source interfering with the thermal imaging results, and determine the best shooting angle and distance according to the structural characteristics of the transformer; S2. Real-time monitoring: Use a thermal imager to scan and photograph the transformer, record its temperature distribution, and the data acquisition module collects the image information generated by the thermal imager in real time and transmits it to the data processing module; S3. Data analysis and processing: The data processing module performs image processing, removes background noise, highlights the possible overheating points, compares the current detection data with the pre-set safety threshold and historical data to judge whether there is temperature abnormality, and the communication unit uploads the processing information to the remote monitoring center. When a dangerous-level temperature is detected, the alarm unit gives an alarm in time.

[0006] Preferably, in step S2, a tripod is used to stabilize the thermal imager, the shooting angle is adjusted, and a telephoto lens or a remote control device is used for shooting when the distance is far.

[0007] Preferably, in step S3, the image processing includes the following steps: a. Image preprocessing: Noise reduction and contrast enhancement. Remove the noise in the image through a filtering algorithm, and use histogram equalization or adaptive contrast enhancement to improve the image quality, making the temperature difference more obvious and facilitating the identification of hot spots; b. Feature extraction: Use the Canny operator edge detection algorithm to identify the transformer contour and the boundaries of internal components; c. Temperature analysis: Convert the color or grayscale value of the infrared image into an actual temperature value. Set an absolute temperature threshold, and if it exceeds this threshold, it is considered that there is a potential problem point. The calculation formula for converting to temperature is as follows: , In the formula: represents the actual temperature of the target; and are constants related to the thermal imager, determined according to the response curve of the device and the calibration process; L represents the radiance value obtained from the thermal imager, corresponding to the grayscale value or digital count value in the image.

[0008] Preferably, the alarm unit uses an audible and visual alarm; the communication unit uses GPRS wireless communication technology to upload the processed information to the remote monitoring center.

[0009] Compared with the prior art, the beneficial effects of the present invention are: By using a thermal imager to collect the transformer and generate an image, record its temperature distribution, perform noise reduction and contrast enhancement processing on the image, use the Canny operator edge detection algorithm to identify the transformer contour and the boundaries of internal components, and then convert the color or grayscale value of the infrared image into an actual temperature value. Compare the actual temperature value with the pre-set safety threshold and historical data to determine whether there is a temperature anomaly, realizing the detection of possible internal faults of the transformer, giving an alarm in time, improving the use safety, enhancing the detection accuracy of the transformer, and at the same time reducing the cost and error of manual inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 is a schematic flow chart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] The present invention can be explained in detail through the following embodiments. The purpose of disclosing the present invention is to protect all technical improvements within the scope of the present invention. In the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "front", "rear", "left", "right", etc. indicating the orientation or positional relationship, it is only corresponding to the drawings of the present application for the convenience of describing the present invention, rather than indicating or implying that the device or element referred to must have a specific orientation.

[0012] Please refer to Figure 1 , the present invention provides a technical solution: a method for detecting faults in ultra-high voltage transformers, including the following steps: S1. Detection preparation: Evaluate the environment around the transformer to ensure that there is no external heat source interfering with the thermal imaging results. According to the structural characteristics of the transformer, determine the optimal shooting angle and distance; S2. Real-time monitoring: Use a thermal imager to scan and photograph the transformer, record its temperature distribution, and the data acquisition module collects the image information generated by the thermal imager in real time and transmits it to the data processing module; S3. Data analysis and processing: The data processing module performs image processing, removes background noise, highlights the possible overheating points, compares the current detection data with the preset safety threshold and historical data to determine whether there is a temperature anomaly. The communication unit uploads the processed information to the remote monitoring center, and when a dangerous-level temperature is detected, the alarm unit issues an alarm in a timely manner; Further, in step S3, the image processing includes the following steps: a. Image preprocessing: Denoise and increase contrast. Remove the noise in the image through a filtering algorithm, and use histogram equalization or adaptive contrast enhancement to improve the image quality, making the temperature difference more obvious for easy identification of hot spots; b. Feature extraction: Use the Canny operator edge detection algorithm to identify the outline of the transformer and the boundaries of internal components; c. Temperature analysis: Convert the color or gray value of the infrared image into the actual temperature value, set an absolute temperature threshold, and if it exceeds this threshold, it is considered that there is a potential problem point. The calculation formula for conversion to temperature is as follows: , In the formula: represents the actual temperature of the target; and are constants related to the thermal imager, determined according to the response curve of the device and the calibration process; L represents the radiation luminance value obtained from the thermal imager, corresponding to the gray value or digital count value in the image; Collect the transformer through a thermal imager and generate an image, record its temperature distribution, perform noise reduction and contrast enhancement on the image, use the Canny operator edge detection algorithm to identify the transformer contour and the boundaries of internal components, then convert the color or grayscale value of the infrared image into the actual temperature value, compare the actual temperature value with the pre-set safety threshold and historical data to determine whether there is a temperature anomaly. Edge detection technology can be effectively applied to identify the transformer contour and the boundaries of its internal components, which provides a basis for further analyzing the transformer status. By combining edge information with temperature data, determine whether there is an area with abnormal heat generation, realize the detection of possible internal faults of the transformer, give an alarm in time, improve the use safety, enhance the detection accuracy of the transformer, and at the same time reduce the cost and error of manual inspection; Further, in step S2, use a tripod to stabilize the thermal imager, adjust the shooting angle, use a telephoto lens or a remote control device to shoot when the distance is far; check and confirm that there is no other structure or object blocking the line of sight between the thermal imager and the transformer, and try to use a direct viewing angle for shooting, so that the most direct and clear thermal image can be obtained, and avoid using extreme angles (such as being too tilted), because this may cause reflection or refraction phenomena, affecting the accuracy of temperature measurement. Understand the natural heat dissipation direction of the transformer and adjust the shooting angle accordingly. Usually, heat dissipates upward, so shooting from the side or slightly downward may be more conducive to capturing the true temperature distribution. To obtain more accurate results, the same position can be shot from multiple angles. Comparing the thermal images at different angles can help verify whether there are abnormal hot spots and improve the reliability of the detection; In addition, the alarm unit uses an audible and visual alarm; the communication unit uses GPRS wireless communication technology to upload the processed information to the remote monitoring center.

[0013] The parts not detailed in the present invention are the prior art. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention; therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting, aiming to include all changes falling within the meaning and scope of the equivalent elements in the content of the present invention.

Claims

1. A method for detecting faults of ultra-high voltage transformers, characterized in that: The following steps are involved: S1. Preparation for testing: Assess the environment around the transformer to ensure that there is no external heat source interfering with the thermal imaging results. Determine the best shooting angle and distance based on the structural characteristics of the transformer. S2. Real-time monitoring: Use a thermal imager to scan and photograph the transformer and record its temperature distribution. The data acquisition module collects the image information generated by the thermal imager in real time and transmits it to the data processing module; S3. Data analysis and processing: The data processing module performs image processing, removes background noise, highlights possible hot spots, compares current detection data with pre-set safety thresholds and historical data, and determines whether there is a temperature anomaly. The communication unit uploads the processed information to the remote monitoring center. When a dangerous level of temperature is detected, the alarm unit promptly issues an alarm.

2. A UHV transformer fault detection method according to claim 1, characterized in that: In step S2, a tripod is used to stabilize the thermal imager, and the shooting angle is adjusted. When the distance is far, a telephoto lens or a remote control device is used to shoot.

3. A UHV transformer fault detection method according to claim 1, characterized in that: In step S3, the image processing includes the following steps: a. Image preprocessing: noise reduction and contrast enhancement. The noise in the image is removed by filtering algorithms. Square image equalization or adaptive contrast enhancement is used to improve the image quality, making the temperature difference more obvious and facilitating the identification of hot spots. b. Feature extraction: Use the Canny operator edge detection algorithm to identify the transformer outline and internal component boundaries; c. Temperature analysis: Convert the color or grayscale value of the infrared image into an actual temperature value, set an absolute temperature threshold, and if it exceeds the threshold, it is considered that there is a potential problem point. The calculation formula for converting to temperature is as follows: ， Where: Indicates the actual temperature of the target; and is a constant associated with the thermal imager, determined from the device's response curve and during the calibration process; L Represents the radiance value obtained from the thermal imager, corresponding to the grayscale value or digital count value in the image.

4. The method for detecting faults of a UHV transformer according to claim 1, characterized in that: The alarm unit adopts an audible and visual alarm; the communication unit adopts GPRS wireless communication technology to upload the processed information to a remote monitoring center.

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