Combining Multi-Source Data to Evaluate the Operation Status of High-Speed Railway Catenary

  • Keli Wang, Chunmin Shi, Jian Huang, Kejun Wang, Chuanbin Cheng


In order to accurately assess the operating status of the catenary to ensure the safe operation of high-speed railways, a method for assessing the operating status of the catenary integrating multi-source data is proposed. First, multi-source data such as catenary test, inspection data, operation and maintenance data, and surrounding environment data are selected as the index data set, then the membership function is determined to calibrate the distribution state of the index. Using the distribution status as the data label, a catenary operating status evaluation model based on the long- and short-term memory network is constructed, and the deep network is trained by collecting various multi-source data to establish the mapping relationship between indicator data and status. The test results show that the evaluation accuracy of the method is %, which can provide good theoretical guidance for the operation and maintenance of the catenary.