Scratches Detection of Optical Fiber Connector Based on Wavelet Packet and Machine Vision

The important meaning of the optical fiber connector scratches detection was introduced based on wavelet packet and machine vision. To detect the optical fiber connector scratches by using the UltraPAC system, aiming at the scratches feature, the method of analyzing and extracting the scratches eigenvalue by using wavelet packet analysis and pattern recognition by making use of the wavelet neural network is discussed. This method can realize to extract the interrelated information which can reflect optical fiber connector scratches feature from the ultrasonic information being detected and analysis it by the information. Construct the network model for realizing the qualitative scratches detection. The results of experiment show that the wavelet packet analysis adequately make use of the information in time-domain and in frequency-domain of the optical fiber connector scratches echo signal, multi-level partition the frequency bands and analyze the high-frequency part further which don’t been subdivided by multi-resolution analysis, and choose the interrelated frequency bands to make it suited with signal spectrum. Thus, the time-frequency resolution is risen, the good local amplificatory property of the wavelet neural network and the study characteristic of multi-resolution analysis can achieve the higher accuracy rate of the qualitative classification of optical fiber connector scratches detection. Finally, the studies are described about detection method of the optical fiber connector scratches based on machine vision.