Combining learning methods and time-scale analysis for defect diagnosis of a tramway guiding system

International audience ; This paper presents a diagnosis system for detecting tramway rollers defects. First, the continuous wavelet transform is applied on vibra- tion signals measured by specific accelerometers. Then, the Singular Values Decomposition (SVD) is applied on the time-scale representations to extract a set of singular values as classification features. The resulting multi-class classification problem is decomposed into several 2-class sub-problems. The predicted probabilities are coupled using a pairwise coupling method. Empirical results demonstrate the efficiency and robustness of the overall diagnosis system on measurement data.