Acceleration Anomaly Detection Method for Sensor Axle Box of Unmanned Vehicle

Abstract

Detecting the anomaly acceleration of the sensor’s axle box of unmanned vehicles is very important for judging the wear condition of vehicle track and evaluating the state of the track. A capacitive accelerometer is connected with acquisition equipment to collect the information of train axle box’s acceleration change when the vehicle is running; instrument amplifier AD8250 with a digitally programmable gain is selected as system signal conversion chip to realize acceleration signal conversion; sliding variance of axle box’s acceleration of the unmanned vehicle is calculated based on sliding variance statistical analysis method, which is confirmed by time window and distance window. Fixing the width of a sliding window according to the response statistics caused by the line excitation link, the acceleration sliding variance is compared with the standard one to determine whether the acceleration is in an anomaly state. The test results show that the anomaly acceleration of the sensor axle box of the unmanned vehicle detected by the proposed method is consistent with the actual results, which provides a reliable basis for vehicle track condition assessment.