As the fundamental processing equipment of the mechanical manufacturing industry, CNC machine tools play an important role in China's national economic development. Once failure happens, the precision and reliability of CNC machine tools will degrade, which will affect the quality of the work piece. In severe cases, the failure will result in machine shutdown or scrap, which will bring huge economic loss to enterprises and countries. Therefore, conducting research on the fault diagnosis technology of CNC machine tools has great theoretical and practical significance. This dissertation is supported by the project Digital High-end NC Device with Bus Organization: Intelligent Fault Diagnosis Technology (2009ZX040009-013) of the National Science and Technology Major Project High-end CNC Machine tools and Fundamental Manufacturing Equipment of the Eleventh Five-Year Plan. The research on CNC machine tool fault diagnosis expert system is conducted and a general condition monitoring and fault diagnosis expert system for CNC machine tool is developed. Firstly, the overall structure of the CNC machine tool fault diagnosis expert system is designed. The versatility of the traditional expert system is limited, to solve this problem, an open modeling method based on fault tree analysis is proposed, which allows the user to build fault trees for different types of CNC machine tools in an interactive way. The information of the fault trees is then stored into database in the form of production rule, serving as the basis for subsequent fault diagnosis. Secondly, in order to extract the fault symptoms timely and accurately, an auxiliary fault symptom extraction method using the sensor information is proposed. For the non-stationary noise and vibration signals acquired in real time, wavelet packet algorithm is adopted for signature analysis and the improved BP neural network method is employed for state classification, which helps to achieve the goal of fault symptom extraction. Precise positioning of the cause of malfunction is realized by means of forward and backward reasoning with the integration of multi-sensor information. Finally, a general condition monitoring and fault diagnosis expert system software for CNC machine tool based on the Visual C++ development tool and ADO database connectivity technology is developed. For the designed expert system, many simulation experiments are conducted on the experimental platform, such as the static library diagnosis, the ...
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