Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision

In the process of producing winding coils for power transformers, it is necessary to detect the tilt angle of the winding, which is one of the important parameters that affects the physical performance indicators of the transformer. The current detection method is manual measurement using a contact...

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Main Authors: Jiazhong Xu, Shiyi Zheng, Kewei Sun, Pengfei Song
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/23/10/4755
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author Jiazhong Xu
Shiyi Zheng
Kewei Sun
Pengfei Song
author_facet Jiazhong Xu
Shiyi Zheng
Kewei Sun
Pengfei Song
author_sort Jiazhong Xu
collection DOAJ
description In the process of producing winding coils for power transformers, it is necessary to detect the tilt angle of the winding, which is one of the important parameters that affects the physical performance indicators of the transformer. The current detection method is manual measurement using a contact angle ruler, which is not only time-consuming but also has large errors. To solve this problem, this paper adopts a contactless measurement method based on machine vision technology. Firstly, this method uses a camera to take pictures of the winding image and performs a 0° correction and preprocessing on the image, using the OTSU method for binarization. An image self-segmentation and splicing method is proposed to obtain a single-wire image and perform skeleton extraction. Secondly, this paper compares three angle detection methods: the improved interval rotation projection method, quadratic iterative least squares method, and Hough transform method and through experimental analysis, compares their accuracy and operating speed. The experimental results show that the Hough transform method has the fastest operating speed and can complete detection in an average of only 0.1 s, while the interval rotation projection method has the highest accuracy, with a maximum error of less than 0.15°. Finally, this paper designs and implements visualization detection software, which can replace manual detection work and has a high accuracy and operating speed.
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spelling doaj.art-080f958ad4104e1cae4f345a27a86a732023-11-18T03:12:10ZengMDPI AGSensors1424-82202023-05-012310475510.3390/s23104755Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine VisionJiazhong Xu0Shiyi Zheng1Kewei Sun2Pengfei Song3School of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Mechanical Engineering, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaIn the process of producing winding coils for power transformers, it is necessary to detect the tilt angle of the winding, which is one of the important parameters that affects the physical performance indicators of the transformer. The current detection method is manual measurement using a contact angle ruler, which is not only time-consuming but also has large errors. To solve this problem, this paper adopts a contactless measurement method based on machine vision technology. Firstly, this method uses a camera to take pictures of the winding image and performs a 0° correction and preprocessing on the image, using the OTSU method for binarization. An image self-segmentation and splicing method is proposed to obtain a single-wire image and perform skeleton extraction. Secondly, this paper compares three angle detection methods: the improved interval rotation projection method, quadratic iterative least squares method, and Hough transform method and through experimental analysis, compares their accuracy and operating speed. The experimental results show that the Hough transform method has the fastest operating speed and can complete detection in an average of only 0.1 s, while the interval rotation projection method has the highest accuracy, with a maximum error of less than 0.15°. Finally, this paper designs and implements visualization detection software, which can replace manual detection work and has a high accuracy and operating speed.https://www.mdpi.com/1424-8220/23/10/4755transformer coilswinding tilt angle detectimage self-segmentation and splicingrotation projection method
spellingShingle Jiazhong Xu
Shiyi Zheng
Kewei Sun
Pengfei Song
Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision
Sensors
transformer coils
winding tilt angle detect
image self-segmentation and splicing
rotation projection method
title Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision
title_full Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision
title_fullStr Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision
title_full_unstemmed Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision
title_short Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision
title_sort research and application of contactless measurement of transformer winding tilt angle based on machine vision
topic transformer coils
winding tilt angle detect
image self-segmentation and splicing
rotation projection method
url https://www.mdpi.com/1424-8220/23/10/4755
work_keys_str_mv AT jiazhongxu researchandapplicationofcontactlessmeasurementoftransformerwindingtiltanglebasedonmachinevision
AT shiyizheng researchandapplicationofcontactlessmeasurementoftransformerwindingtiltanglebasedonmachinevision
AT keweisun researchandapplicationofcontactlessmeasurementoftransformerwindingtiltanglebasedonmachinevision
AT pengfeisong researchandapplicationofcontactlessmeasurementoftransformerwindingtiltanglebasedonmachinevision