Fuzzy Reasoning based Reliability Fault Prediction of CNC Machine Tools

CNC machine tools are the infrastructure of manufacturing industry, and many fields cannot do without them. This paper studies fault data a series tools, predicts level based on activity parameters Gutenberg Richter curve fuzzy information theory. Apply model to reliability analysis use this fit curves separately. Fit each stage with curves, results show that b value can reflect frequency tools. Due correlation fuzziness between system faults, it is more appropriate neural network strong adaptability good learning ability, which easily adjust parameters, express complex, high-dimensional nonlinear through fewer conditions. The reasoning link relationship level, b-value, N-value. Analyze error predicted original small indicates has predictive ability. Applying ability research will yield results.