Abstract
A contactless method based on infrared image matching is presented for zero-value insulator detection on outdoor porcelain insulator string. An improved SIFT (scale-invariant feature transformation) method is developed to extract features and accomplish the pre-matching between the insulator string to be detected and the standard string in the image library. An improved RANSAC (random sampling consistency) algorithm is developed to remove mismatching points and achieve more accurate and faster detection. Firstly, an adaptive circle window is designed to improve the sensitivity of the SIFT operator on arc features extraction from insulators. Then, the dimension of the feature is decreased from128 to 32 by dividing the circle into 4 fan-shaped regions and descript the feature on 8 directions to achieve the lower computation burden and high accuracy. For the SIFT method and RANSAC method uses Euclidean distance to measure the similarity between features extracted from the string to be detected and the string in the standard library, mismatching may be caused. Spatial geometric features of the neighborhood around the feature point are used to construct the error function to improve the RANSAC method and remove the mismatching points. Faster matching is obtained by a threshold control for decreasing the number of data checking for the consensus set data models. Testing results show that the presented method is effective in the detection of zero-value resistances for outdoor insulator string. Compare with the SIFT method and SIFT + RANSAC method, the presented method has higher accuracy and faster detection speed.
Highlights
Outdoor insulators are exposed in the air, suffered from rain, snow, frost, dew, etc., endures long-term operating voltage and wire tension, which may result in insulation failure
An image matching method combined with the scale-invariant feature transformation (SIFT) method [15] and the Random sampling consistency algorithm (RANSAC) method [16] is presented in this paper for zero-value insulators detection
SIFT method is used for pre-matching the zero-value insulator string to be detected with the standard string in the image library and the RANSAC method is used to achieve further matching and remove the mismatching points
Summary
Outdoor insulators are exposed in the air, suffered from rain, snow, frost, dew, etc., endures long-term operating voltage and wire tension, which may result in insulation failure Under severe cases, they may cause zero-value insulators and leads to single-phase grounding, flashover, breakdown, or power outage. Zero-value insulators occupy a lower gray rang and normal insulators occupy the higher rang Based upon this feature, an image matching method combined with the scale-invariant feature transformation (SIFT) method [15] and the Random sampling consistency algorithm (RANSAC) method [16] is presented in this paper for zero-value insulators detection. SIFT method is used for pre-matching the zero-value insulator string to be detected with the standard string in the image library and the RANSAC method is used to achieve further matching and remove the mismatching points. Between zero-value insulator strings and the standard insulator strings is achieved by the implementation of the presented method
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