Research on Vibration Fault Detection of Coal Mine Main Ventilation Fan Based on High-Order Cumulative Quantity
Due to various factors such as the rotor during the operation of the main ventilation fan in coal mines,inaccurate detection of vibration fault categories often occurs in the design of vibration fault detection methods for coal mine main ventilation fans,resulting in poor detection accuracy of the methods.A method for detecting vibration faults in coal mine main ventilation fans based on high-order cumulative quantities is proposed.Denoising the collected vibration signals,calculating their multiscale functions,conducting time-frequency domain analysis on the vibration signals,calculating the covariance of the vibration signals,and computing their higher-order cumulants to extract the skewness and kurtosis features of the vibration signals,and constructing the feature vectors of the vibration signals.By calculating the entropy value of the vibration signal feature vector,identifying the fault characteristics,and then calculating the fault value of the signal,different types of vibration faults can be detected.The experimental results show that the designed detection method has an average false alarm rate of 5.6% and high detection accuracy in practical applications.
high-order cumulative quantitycoal mine main ventilation fanvibration malfunctionfault detectiontime-frequency domain analysiseigenvectorfault value
万方数据
维普
