Data of vibration sensor of metro electromechanical equipment

When the abnormality is found, it is necessary to find the cause of the abnormality in time to prevent great maintenance loss. Testing the abnormal vibration of the equipment has a great role in improving the work efficiency and improving the service life of the equipment.

Current maintenance frequency of subway equipment system is higher, fault or abnormal samples are scarce, how to find the equipment is also the difficulty, therefore, this paper adopts the method of artificial simulation equipment abnormal, collected the electrical equipment abnormal data, and puts forward the analysis of equipment abnormal data, the model can provide the premise for real-time automatic detection of anomalies, the method is proposed, can provide the electrical equipment abnormal perception data set, algorithm, model, greatly reduce the frequent maintenance frequency, provide technical solutions for automation operations and remote operations.