Novel Technologies for Diagnosis of Conveyor Belt Looseness via Motor Current Signature Analysis

This paper proposes and investigates two novel worldwide non-invasive, low-cost, online automatic diagnostic technologies for conveyor belt looseness by motor current signature analysis. Belt looseness causes impulsive transient spikes due to intermittent belt–motor engagement, which are captured and essentially enhanced using spectral kurtosis (SK). Two diagnostic technologies are as follows: Cross-Correlations of Spectral Moduli of orders three and four to extract supply frequency harmonic cross-correlations from SK-filtered current signals, and Consolidated Spectral Kurtosis, a band-independent technology, which enables effective diagnosis by summing essential spectral kurtosis values across the entire frequency range. Comprehensive experimental trials on an industrial grain belt conveyor system demonstrate that the proposed technologies are effective for conveyor belt looseness diagnosis. The Cross-Correlations of Spectral Moduli technologies achieved a maximum total probability of correct diagnosis value of 98%. The Consolidated Spectral Kurtosis technology captures overall impulsive energy across the whole frequency range, achieving a maximum total probability of correct diagnosis value of 99.6%. This study highlights the diagnostic effectiveness and computational efficiency of the proposed technologies for the reliable diagnosis of conveyor belt looseness. Experimental comparison of the proposed technologies is undertaken.