For the sound signal generated by the shaking of foreign objects in the electric energy meter

a new endpoint detection method for foreign matter sound signal in electric meter is proposed by studying on traditional endpoint detection method of acoustic identification process. The method combines wavelet packet energy features

short-time TEO logarithmic energy and fuzzy C-means clustering（ FCM）

and finally uses the extracted wavelet packet energy features and support vector machine（ SVM） to complete the training and recognition of foreign matter in the electric energy meter. Compared with the traditional threshold-based endpoint detection algorithm

the endpoint detection algorithm has higher accuracy of detecting on foreign objects

and can better detect foreign objects in the energy meter.