Automatic Fault State Alarm Method for OCS Master station System Based on Signal Feature Analysis
Hewen Luo, Guohao Li · 2023
In order to improve the safety and stability of the operation of the OCS master station system, a signal feature analysis based automatic alarm method for the fault status of the OCS master station system is proposed. Analyze the structural composition of the OCS master station system, collect fault data of the OCS master station system operation through sensors, and extract the features of the fault signal using dual tree complex wavelet decomposition. Based on the extracted fault signal features, support vector machines are used to classify and identify faults in the OCS master station system. Based on the identified faults, design an automatic fault status alarm process to complete the automatic alarm of the OCS master station system fault status. The test results show that compared with existing alarm methods, the proposed method can quickly diagnose faults in the OCS master station system and has high alarm accuracy.