Wavelet Transform-Based Approach to Defect Identification in Railway Carbon Contact Strips
AbstractPantographs of electric rail vehicles are fitted with carbon contact strips, which slide along the contact wire of catenary to provide constant electrical contact. Contact strips are exposed to wear and damages. Using damaged contact strips significantly increases the risk of catenary rupture. Therefore, their technical condition has to be inspected frequently. In previous work a 3D laser scanning system was proposed for recording contact strips surface shape when vehicles pass an inspection point on a railway line. The system was complimented with an effective automatic wear estimation algorithm. However, this algorithm is insensitive to some shallow defects which are considered hazardous. This paper presents defects identification approach based on differentiation of contact strips profiles. It is assumed that the hazard of catenary rupture corresponds to the peak value in the differentiated profile. A wavelet transform was used to allow for robust differentiation of profiles featured by low signal-to-noise ratio. A method for choosing well-balanced dilatation parameter was proposed, in order to obtain good accuracy of differentiation of both smooth and narrow-edged contact strip defects. Results of simulations implemented in Matlab confirm that the proposed approach can be applied to an algorithm aiming for automatic defects identification.
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