Detection and Isolation of Wheelset Intermittent Over-Creeps for Electric Multiple Units Based on a Weighted Moving Average Technique

Wheelset intermittent over-creeps (WIOs), i.e., slips or slides, can decrease the overall traction and braking performance of Electric Multiple Units (EMUs). However, they are difficult to detect and isolate due to their small magnitude and short duration. This paper presents a new index called variable-to-minimum difference (VMD) and a novel technique called weighted moving average (WMA). Their combination, i.e., the WMA-VMD index, which uses correlation information to find an optimal weight vector (OWV) for the VMD indices within a time window, is employed to detect and isolate WIOs in real time. The uniqueness of the OWV is proven, and its properties such as the symmetrical structure are revealed. WIO detectability and isolability conditions of the WMA-VMD index are provided, leading to the property analyses of two nonlinear, discontinuous operators, $\min $ and VMD _i . Experimental studies are conducted based on practical running data and a hardware-in-the-loop platform of an EMU, which show the effectiveness of the developed method.