High-strength bolt detection using fuzzy theory

Abstract

A large number of high-strength bolts are used to connect multiple steel members when erecting steel bridges. All high-strength bolts are visually checked one by one to confirm whether they are tightened correctly or not, which requires large effort. This paper proposes an automatic bolt detection method to automatically determine whether the high-strength bolt is tightened correctly or not. In the proposed method, images of multiple high-strength bolts are raster-scanned, and a presence probability map is created from the HOG features of each small region and the high-strength bolt detection frame obtained from SVM. Since the bolt size is not constant in the image, the exact bolt bounding box is estimated by fuzzy inference using the obtained detection frames and existence probability values. The accuracy of the proposed method was evaluated using 42 images taken at a steel bridge erection site. Experiments results showed that the proposed method can detect high-strength bolts in 0.753 precision, 0.614 recall, and 0.676 F-measure with fuzzy inference.