Posture Adjustment of Microphone Based on Image Recognition in Automatic Welding System

As the requirements of production process is getting higher and higher with the reduction of volume, microphone production automation become an urgent need to improve the production efficiency. The most important part is studied and a precise algorithm of calculating the deviation angle of four types microphones is proposed, based on the feature extraction and visual detection. Pretreatment is performed to achieve the real-time microphone image. Canny edge detection and typical feature extraction are used to distinguish the four types of microphones, categorizing them as type M1 and type M2. And Hough transformation is used to extract the image features of microphone. Therefore, the deviation angle between the posture of microphone and the ideal posture in 2D plane can be achieved. Depending on the angle, the system drives the motor to adjust posture of the microphone. The final purpose is to realize the high efficiency welding of four different types of microphones.