Health monitoring of railway vehicle door system based on movement resistance analysis

Reliability of door system is directly related to the operation safety and efficiency of railway vehicles. However, door system is with high failure rate and its failure modes are not clearly known yet. Online accurate health monitoring is its urgent need for predictive maintenance, which is expected to achieve great time and cost savings. In this paper, a health monitoring method is proposed based on door movement resistance analysis on the signals of the intelligent driven motor. The major internal and external factors that cause friction increase during door movement are analyzed. Principal component analysis (PCA) is used to construct the health indicators for online monitoring. Two sets of experiments are conducted to verify the proposed method, where the global and local movement resistances are intentionally added to simulate internal and external factors, respectively. The results show that, the proposed health monitoring method can reveal the latent health status accurately and provide helpful information for predictive maintenance.