数控机床故障预警与诊断系统设计

发布时间：2018-01-21 18:05

本文关键词： 数控机床故障预警寿命预测模糊神经网络　出处：《西南交通大学》2013年硕士论文　论文类型：学位论文

【摘要】：针对数控机床的多样性、异构性以及多种高新技术高度集成的特点,研究了数控机床关键部件的性能退化机理,确定了数控机床关键部件的高敏感度信号特征,给出了高敏感度信号特征的数据结构,开发了数控机床关键部件信号的获取和处理技术,搭建了故障特征数据库。结合高档数控机床故障频发特点,构建了数控机床的性能退化模型,完善了故障预警及机床状态评估理论,开发了数控机床控制系统的运行状态信息获取模块,利用性能退化模型拟合信号高敏感度特征与数控机床关键功能部件期望剩余寿命之间的映射关系,探究数控机床关键部件的性能退化规律,建立了维修专家知识库。本文开发完成的具有自主知识产权和高技术附加值的“高档数控机床故障预警和诊断系统”,有效实现了高档数控机床的在线和远程故障预警和自动诊断功能。目前,该系统已在多台数控机床上推广应用。机床状态的检测和故障的诊断都由计算机自动完成,其诊断的高准确性和高效率远高于基于经验的维修模式。同时,本系统在预警故障的同时还提供了相应的处理方法,及时给出备件订购需求,有效缩短了设备停工时间,大大降低设备故障的排除难度,极大提高了维修效率。应用实践表明,本系统能够有效保障数控机床长期安全可靠的运行,为数控机床用户制定生产计划或维护维修计划提供依据。
[Abstract]:In view of the diversity, heterogeneity and high integration of high and new technology of CNC machine tools, the mechanism of performance degradation of key components of NC machine tools is studied, and the characteristics of high sensitivity signals of key components of NC machine tools are determined. The data structure of high sensitivity signal feature is given, the signal acquisition and processing technology of key components of NC machine tool is developed, and the fault feature database is built. Combined with the frequent fault characteristics of high-grade CNC machine tools, the performance degradation model of NC machine tools is constructed, and the theory of fault warning and machine tool state evaluation is improved. The operation state information acquisition module of NC machine tool control system is developed, and the mapping relationship between the high sensitivity characteristic of signal and the expected residual life of key functional components of CNC machine tool is fitted by performance degradation model. This paper probes into the law of performance degradation of key parts of NC machine tools, and establishes a knowledge base of maintenance experts. In this paper, with independent intellectual property rights and high-tech added value of the "high-grade CNC machine tool fault warning and diagnosis system". The functions of on-line and remote fault warning and automatic diagnosis of high-grade NC machine tools are effectively realized. The system has been widely used in many NC machine tools. The condition detection and fault diagnosis of the machine tools are automatically completed by the computer. The high accuracy and high efficiency of the diagnosis is much higher than the maintenance mode based on experience. At the same time. At the same time, the system also provides the corresponding treatment method, gives the spare parts ordering demand in time, effectively shortens the equipment shutdown time, and greatly reduces the difficulty of troubleshooting the equipment fault. The application practice shows that the system can effectively guarantee the long-term safe and reliable operation of CNC machine tools and provide the basis for NC machine tool users to make production plans or maintenance and maintenance plans.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TG659;TP277

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