A filtering method based on wavelet transform for collected data of automatic ammunition loading system

Embedded fault diagnosis machine for the automatic ammunition loading system real-time monitors the automatic ammunition loading system, collects the data by using sensors, analyzes the data, detects and isolates faults, or predicts the health of the system in the future. The denoising of the collected data is of great significance to effectively reveal the operation information of ammunition automatic loading system. In order to solve the problem of the traditional median filter could not be taken into account the details and the smoothness, a filtering method based on wavelet transform for automatic ammunition loading system is proposed in this paper. This method can effectively reduce the noise and improve the signal noise ratio (SNR), the signal after wavelet filter retains all the low frequency of the single axis swing, filters out the high frequency noise. It ensures the correctness of the follow-up data analysis and processing, detection, isolation of the fault or predict the health of the system.