For switchgear conformity inspection,an acceptance test algorithm based on singularity analysis of torque signals was proposed.According to the correlation between the eligibility of the switchgear and the singularity characteristics of torque sig-nal,12 statistical features of torque signal were compressed to 5 by Fisher discriminant method,and the sample set composed of the features was set as input to train the SVM classifier which could distinguish the eligibility of the switchgear after training.Fi-nally,the proposed method was verified by experiments.The experimental results show that the recognition rate of the proposed al-gorithm is100%,and delay within30ms,all the identified points fall within the set area.In the case of damped interference,com-pared with the wavelet transform theory method,it has better robustness while taking into account fast response,and does not need a large number of training samples and training time.
RobotAcceptance TestTorqueCharacteristic Analysis of Singularity
NETL
NSTL
维普
万方数据
