Abstract

A turnout is a key piece of equipment and one of the weakest links of the railway infrastructures. Continuously welded turnouts (CWTs) have been widely laid on high-speed railway bridges because of the topographic and environmental limitations, where special attention is required to ensure the safety of the high-speed railways. A real-time monitoring system will be interesting for the service status of the CWT on the bridge, which was designed and established for the first time in China. Real-time data of the service status indicators were obtained by fiber grating and video perception technologies. The data features of the monitoring results were analyzed. A regression model and backpropagation neural network model were adopted to predict the key indicators. An alarm mechanism with a static threshold and outlier diagnosis was established. The monitoring system has been in good operation state for more than 4 years, effectively ensuring railway safety and security.

Full Text
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