Fault Automatic Detection Method for Steel Cord Conveyor Belt Based on the Regularity Analysis

Abstract

The X-ray images of steel cord conveyor belt are built on a repetitive unit of a pattern. Based on the statistical features and regularity analysis, a fault automatic detection method named MRB(Modified Regular Bands)was proposed to monitor the status of steel cord conveyor belt. Firstly, the input image of steel cord conveyor belt is normalized. Secondly, the normalized image is standardized. And then the MRB parameters of each pixel are calculated by the progressive scanning. Finally, after subtracting the MRB parameter mean of the whole image, the detected result whether it is a fault image or not is obtained and the fault region is extracted from the fault image, by the way of comparing with the thresholds obtained from training stage. The results of the detection of four kinds of typical steel cord conveyor belt faults show that the MRB method has a higher precision, is simple and fast enough for real-time online fault detection. Comparing with the statistical method such as the mean and variance, MRB method is sensitive to the faults and can detect the small faults. The image of MRB parameter has the higher contrast, so it can stand out the fault region from the fault-free region. And the shape of fault region is acquired well by MRB method.