Electronic Parts Appearance Quality Prediction System Based on Wavelet-Fuzzy Neural Networks

In order to realization electronic parts product appearance quality detection control, one kind of processor based on the intelligent knowledge automatic extraction and system intelligence modeling was presented. In the processor, wavelet-fuzzy technique and neural network technique are combined. Uses the fuzzy wavelet extraction image feature, and wavelet function is used as fuzzy membership function. The fuzzy inference is realized by neural network and the shape of membership function can be adjusted in real time. It endues the processor with better capability of learning and self adapt. Based on establishment product quality oriented key characteristics index dynamic adaptability analysis control system, an architecture of intelligent fuzzy neural network combined with quality management module of manufacturing execution system (MES) is presented. It formed a detection product appearance quality of intelligent decision support system. The results of experiments demonstrate that the system can detect product appearance quality perfectly, with a high precision and has the practicality.