A correction testing method for mechanical characteristic parameter of circuit breaker based on vision technology

Abstract

Mechanical characteristic parameter of a circuit breaker (CB) is an important basis to evaluate its performance. Traditional testing methods involve installing complex sensors and cannot perform testing online. A non-touch testing method based on computer vision technology is proposed in this paper. During operation, we use a high-speed camera to capture image sequences, and then search for the target frame by frame using the normalized cross-correlation pyramid (NCC-P) algorithm. At the same time, the error caused by vibration displacement of the CB is corrected through the movement condition of the fixed part. Finally, the moving trail of the main shaft is constructed accurately and, furthermore, the mechanical characteristic parameter is calculated by the relationship between the main shaft and the CB contact. Experiment shows that the proposed method can test the mechanical characteristic parameter accurately and quickly.

Circuit Breaker Energy Storage Spring Deformation Characteristics Test Method Based on Identification Region Estimation and Optimization of SSD-P Algorithm

“…In order to further highlight the advantages of the algorithm proposed in this paper compared with the traditional method, it is compared with NCC and MAD algorithm proposed in [12], and draw the y coordinate displacement-time curve of tracking the target in one closing experiment. The tracking results of NCC and MAD algorithm are shown in Fig.13 and Fig.14.…”

“…In high-speed target tracking, image matching algorithm is directly related to the accuracy and iterative convergence of recognition algorithm. The sequential similarity detectionpyramid (SSD-P) matching algorithm combines the search strategy of SSD algorithm and image pyramid decomposition, which improves the calculation speed while ensuring good robustness [12]- [14], but the shape similarity of each coil of spring affects the accuracy of matching. In this paper, a sequence similarity detection image pyramid matching based on recognition region estimation (SSD-P-E) algorithm is proposed to recognize the spring deformation characteristics.…”

“…At present, in the tracking algorithm of image moving target, the matching algorithm based on point characteristics has the advantages of small computation and fast matching speed [11], but it is more sensitive to the errors of characteristics extraction and characteristics matching, so it is difficult to get high matching accuracy; The matching algorithm based on block characteristics makes use of all gray information of the image, with high matching accuracy and good robustness, but its obvious disadvantages are large amount of calculation and slow speed. The most commonly used algorithms are sequential similarity detection (SSD), normalized cross correlation (NCC), mean of absolute difference (MAD)algorithm, and so on [12]. In [13], based on NCC algorithm, image pyramid search strategy is introduced and applied to the mechanical characteristics test of circuit breaker.…”