| Nowadays, home and abroad are pay more attention to the research on processing and precision for rapid prototyping machine, rather than condition detection and fault diagnosis for it, in order to improve the reliability of rapid prototyping machine and detect its faults and hidden faults timely, eliminate them timely and exactly, based on the Selective Laser Sintering (SLS) machine developed by Huazhong University of Science & Technology (HUST) themselves, this dissertation has researched its condition detection and fault diagnosis. Against its continuous long timework, we have developed the condition detection and fault diagnosis expert system for SLS machine.The common faults in the process of SLS machine running are researched ,According to the existing conditions of SLS machine, the hardware& software of the condition detection and fault diagnosis expert system for SLS machine are designed based on fault tree analysis and expert system. The software are developed in PowerRP 2004 for SLS by visual c++6.0 technologies.During the research and developing process of the system, knowledge representation by frame and general rule is established on the fault tree model, and the system has been realized knowledge base and formal structure of fault tree by related database, combined the predominance of database. The database is entirety managed by the related database manage system. Moreover, the algorithm of diagnosis reasoning of certain fault is realized. Finally, the user interface of the system is programmed by object- oriented technology, it has friendly graphics window. It's operated simply and conveniently.Many experiments indicates many common faults such as no laser emitting, laser cooler's flux shortfall or temperature high, fall control of galvanometer scanning, have been detected and diagnosed .The system run steadily, the reliability of SLS machine has been truly improved, Furthermore, it has been successfully applied to HUST'HRPS-II SLS machine and run well. |
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