Automatic fault detection for steel cord conveyor belt based on statistical features.

The X-ray images of steel cord conveyor belt are built on a repetitive unit of a pattern. Based on the statistical features and the idea of regularity, 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 was normalized and standardized. Then the MRB parameters of each pixel were 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 was obtained and the fault region was 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 higher precision, is simple and fast enough for real-time on-loom fault detection. Compared with the statistical method such as the mean and variance, the MRB method is sensitive to the faults and can detect the small faults. The image of MRB parameter has higher contrast, so it can stand out the fault region from the fault-free region. And the shape of fault region is well acquired by MRB method. [ABSTRACT FROM AUTHOR]