Detection of opening motion characteristics in DC circuit breakers based on machine vision.
A circuit breaker is a crucial component in power systems, and its operation is essential for evaluating its interruption performance. However, electromagnetic interference often affects sensor accuracy. To address this issue, this paper investigates a non-contact measurement technique for assessing...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0312253 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1825206818627911680 |
|---|---|
| author | Zhaoyu Ku Jinjin Li Dongheng Li Huajun Dong |
| author_facet | Zhaoyu Ku Jinjin Li Dongheng Li Huajun Dong |
| author_sort | Zhaoyu Ku |
| collection | DOAJ |
| description | A circuit breaker is a crucial component in power systems, and its operation is essential for evaluating its interruption performance. However, electromagnetic interference often affects sensor accuracy. To address this issue, this paper investigates a non-contact measurement technique for assessing the motion characteristics of circuit breakers. A motion detection method based on Franklin moments is proposed. A synchronous image acquisition platform was established using high-speed cameras to capture the motion of 252kV circuit breakers. The captured images are preprocessed, with coarse edges extracted using the Laplacian algorithm. Franklin moment convolution calculations are then applied to determine sub-pixel coordinates of the image edges based on these coarse edges. By analyzing the frame-to-frame variations of these sub-pixel coordinates, the opening motion characteristics of the circuit breaker are extracted. This method can detect the vibration parameters and bouncing phenomenon of circuit breaker motion machine in millisecond level, and the accuracy is 0.01 mm. These findings offer valuable insights for future research on circuit breaker performance. |
| format | Article |
| id | doaj-art-bcb2a52d760845a2ac7a68f45e97635d |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-bcb2a52d760845a2ac7a68f45e97635d2025-02-07T05:30:57ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031225310.1371/journal.pone.0312253Detection of opening motion characteristics in DC circuit breakers based on machine vision.Zhaoyu KuJinjin LiDongheng LiHuajun DongA circuit breaker is a crucial component in power systems, and its operation is essential for evaluating its interruption performance. However, electromagnetic interference often affects sensor accuracy. To address this issue, this paper investigates a non-contact measurement technique for assessing the motion characteristics of circuit breakers. A motion detection method based on Franklin moments is proposed. A synchronous image acquisition platform was established using high-speed cameras to capture the motion of 252kV circuit breakers. The captured images are preprocessed, with coarse edges extracted using the Laplacian algorithm. Franklin moment convolution calculations are then applied to determine sub-pixel coordinates of the image edges based on these coarse edges. By analyzing the frame-to-frame variations of these sub-pixel coordinates, the opening motion characteristics of the circuit breaker are extracted. This method can detect the vibration parameters and bouncing phenomenon of circuit breaker motion machine in millisecond level, and the accuracy is 0.01 mm. These findings offer valuable insights for future research on circuit breaker performance.https://doi.org/10.1371/journal.pone.0312253 |
| spellingShingle | Zhaoyu Ku Jinjin Li Dongheng Li Huajun Dong Detection of opening motion characteristics in DC circuit breakers based on machine vision. PLoS ONE |
| title | Detection of opening motion characteristics in DC circuit breakers based on machine vision. |
| title_full | Detection of opening motion characteristics in DC circuit breakers based on machine vision. |
| title_fullStr | Detection of opening motion characteristics in DC circuit breakers based on machine vision. |
| title_full_unstemmed | Detection of opening motion characteristics in DC circuit breakers based on machine vision. |
| title_short | Detection of opening motion characteristics in DC circuit breakers based on machine vision. |
| title_sort | detection of opening motion characteristics in dc circuit breakers based on machine vision |
| url | https://doi.org/10.1371/journal.pone.0312253 |
| work_keys_str_mv | AT zhaoyuku detectionofopeningmotioncharacteristicsindccircuitbreakersbasedonmachinevision AT jinjinli detectionofopeningmotioncharacteristicsindccircuitbreakersbasedonmachinevision AT donghengli detectionofopeningmotioncharacteristicsindccircuitbreakersbasedonmachinevision AT huajundong detectionofopeningmotioncharacteristicsindccircuitbreakersbasedonmachinevision |