The Design Of Color-ring Resistor Quality Automatic Detection System

There is a growing demand for the electronic components, with the rapid development of electronic, new material and intelligent technologies. The requirement of electronic component quality is being stricter. The integrity inspection of the resistor color code is very important for the quality management in the electronic component producing process. It is necessary to perform automation production instead of artificial production to ensure the high quality of electronic components. In this study, an integrity inspection system for the resistor color code will be proposed.Axial color ring resistance will be obtained after the color ring detection and resistance detection. Color ring detection is the first quality detection link, but also the important part of the quality automatic detection system. Firstly by the image sensor the target object is converted into an image signal. Then it is converted into digital signals and transmitted to a dedicated image processing system. According to the pixel distribution, brightness and color information, all operations are carried out to target the feature extraction. According to the preset allowable degree and other conditions, the output result is given out. Resistance detection is the second quality detection link. According to the given output result, next step motion of the equipment could be get. Finally, the detection of the color loop defects of the resistance is detected quickly based on the combine of color ring detection and resistance detection. The detection results are displayed in the interface of the detection.The resistance defect detection is based on the detection of the color ring defect image. The key techniques of detecting the color ring defects include image preprocessing(gray transformation, denoising filtering), target image segmentation, color ring region extraction, etc. Gray transform enhances the target image. Spatial filtering weakens the image acquisition and the data transmission of variety noises. Threshold segmentation technique suppresses the background, and further highlights the target area. Then the rectangular region approximation could be applied. The color ring region extraction effect directly affects the recognition accuracy.The identification classification of color ring defect image is the important task and the key step of the detection of resistance defects. The classification and recognition will be based on the support vector machine theory and statistical learning identification method. The identification method defines the feature vector of the defect mode, and gives the standard samples to train the learning method of support vector. Two types of color ring defect pattern recognition problem decomposition process will be analyzed. This study will propose the support vector machine(SVM) identification process and experimental method. The experimental results will prove the reliability and stability of the method.The resistor color ring detection process is highly automated, combined with actual production process and rhythm. It ensures the timely detection, timely feedback, and could perfect substitute for artificial visual inspection. The automatic detection of color ring resistance defects and resistance could be realized. This study has an important practical significance to solve the bottleneck problem.