Electronic Science and Technology ›› 2022, Vol. 35 ›› Issue (1): 21-28.doi: 10.16180/j.cnki.issn1007-7820.2022.01.004

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Automatic Detection Method of Crane Track Altitude Difference Based on Spot Position

ZONG Shengkang,CHENG Jianpeng,ZHANG Xiliang   

  1. School of Mechanical Engineering,Jiangsu University,Zhenjiang 212013,China
  • Received:2020-09-15 Online:2022-01-15 Published:2022-02-24
  • Supported by:
    National Natural Science Foundation of China(51175230)


The automatic detection technology of crane track is immature, which cannot meet the requirements of the track detection. In view of this problem, an automatic detection method of crane track altitude based on the position of the light spot image is proposed. A laser launcher and an imaging board are placed on both sides of the track. The laser is transmitted and projected on the imaging board to form a spot image. The gray-scale distribution of the light spot image is trimmed to enhance the difference between image sharpness and gray-scale distribution. The improved two-dimensional Otsu algorithm is used to accurately segment the spot image, and the edge of the spot is extracted for circle fitting. The center coordinates of the edge fitting circle are calculated to complete the spot image position recognition. Moreover, the position deviation of the light spot in the vertical direction is calculated to obtain the height difference between the two detection points of the crane track. Experimental research shows that the average error of spot image position recognition using the detection method of spot position recognition in this study is about ±0.22 mm, and the maximum error does not exceed ±0.4 mm. Compared with the traditional method of spot image position recognition, the accuracy of the proposed methed is improved by about 0.10 mm. Based on the track height difference of the spot position, the average error of detection is about ±0.8 mm, and the error range is ±1.8 mm, which meets the requirements of track detection.

Key words: laser beam, position recognition, image processing, hoisting machinery, track detection, spot image, photoelectric detection, machine vision

CLC Number: 

  • TP391.4