The invention belongs to the technical field of
image processing, and particularly relates to a jaw
crusher eccentric shaft
anomaly detection method and
system.The jaw
crusher eccentric shaft
anomaly detection method comprises the following steps that S1, an original
grayscale image of the end face of an eccentric shaft of a jaw
crusher is obtained, and the center coordinate of the end face of the eccentric shaft is determined through circular contour positioning; converting the original
grayscale image into a polar coordinate
system image by taking the central coordinate as an original point; s2, evaluating a
radial gradient and a tangential gradient of each pixel point in the analysis window on the polar coordinate
system image, and determining an edge response
stability index according to a distribution relationship between the
radial gradient and the tangential gradient; and S3, calculating a global
motion vector of the rack background feature point and a local
motion vector of the eccentric shaft end face feature region. According to the invention, strong background vibration interference is effectively counteracted, trace slippage in the
germination stage can be identified, and the safety and monitoring precision of equipment operation are significantly improved.