In order to improve the efficiency of mechanical detection,a mechanical sound anomaly detection technique based on masked autoencoder is proposed.In this technique,the mask autoencoder can be used to learn and extract the features in the data information,and the detection of abnormal/normal mechanical sound can he achieved through training.The results of the validation experiments show that the AUC values of the proposed method in this experiment are 0.7292,0.7262,0.9141,and 0.9050 for fan,pump,slide,and valve sound detection,respectively.The average AUC value of the method is 0.8191,which is an improvement of 11.8％with respect to the baseline system's AUC value.The experimental results show that the method proposed in this experiment can effectively detect mechanical sound anomalies.
NETL
NSTL
万方数据
