Pantograph-Catenary Arc Detection Based on Electrical Parameter Transient Variations Correlated With Current-Zero Arc Phenomena

Reliable pantograph-catenary (P-C) contact is fundamental to locomotive operational stability. P-C arcing (P-C arc) discharges are induced by deteriorated contact conditions; thus, real-time arc detection becomes imperative for proactive maintenance interventions. Conventional methodologies are designed based on optical/acoustic signals induced by the P-C structure or normal frequency bands of electrical parameters accompanying arcs. However, some limitations exist: environmental interference would largely affect the out-carriage sensing modalities. For approaches based on conventional electrical parameters, the accuracy is compromised, attributable to two principal factors: the selection of electrical parameters is constrained, which might be inadequate to delineate arc features. The frequency band utilized is relatively low, failing to effectively pinpoint arc features. This article presents a novel transient analysis framework, targeting electrical parameters during arc current-zero periods. Multiple electrical parameters are analyzed to identify the optimal detection frequency bands, exhibiting maximal discriminative power between arcing/normal contact states. The features are calculated by windowed fast Fourier transformation (FFT) according to the analysis and then processed and temporally synchronized to form datasets. Finally, a random forest (RF) classifier constructed based on the datasets enables real-time detection. Experimental validation confirms superior detection efficacy.