| 引用本文: | 邱静,温熙森,胡政.基于动力学模型的柔性加工设备机电系统状态监测与故障预警.[J].国防科技大学学报,1998,20(3):84-88.[点击复制] |
| Qiu Jing,Wen Xisen,Hu zheng.Condition Monitoring and Fault Prediction of Mechanical-Electronic Systems of Flexible Machining Devices Based on Dynamics Model[J].Journal of National University of Defense Technology,1998,20(3):84-88[点击复制] |
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| 基于动力学模型的柔性加工设备机电系统状态监测与故障预警 |
| 邱静, 温熙森, 胡政 |
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(国防科技大学 机械电子工程与仪器系 湖南 长沙 410073)
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| 摘要: |
| 在建立的加工设备机电系统精确动力学模型及对模型参数实时辨识的基础上[1], 建立柔性加工设备机电系统的状态监测模型, 包括BAYES故障检测、突发故障检测及故障分析与定位等; 同时利用Kullback信息距离和多层递阶AR模型实现系统的状态与故障预警。在加工设备上的实验表明模型可行有效, 它能排除柔性多变工况、时变性及随机干扰对监测与预警功能的影响, 提高其鲁棒性和自适应能力。 |
| 关键词: 柔性加工设备, 机电系统, 动力学模型, 状态监测, 故障预警 |
| DOI： |
| 投稿日期：1997-09-26 |
| 基金项目:国防预研基金资助项目 |
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| Condition Monitoring and Fault Prediction of Mechanical-Electronic Systems of Flexible Machining Devices Based on Dynamics Model |
| Qiu Jing, Wen Xisen, Hu zheng |
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(Department of Mechatronic Engineering and Instrumentation, NUDT, Changsha, 410073)
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| Abstract: |
| Based on the dynamics models and their identification of mechanical-electronic systems of flexible machining devices, we have built up a real condition monitoring model which includes BAYES fault detection, abrupt fault detection and fault analysis&location. Utilizing the Kullback information distance and the multilevel hierarchical AR model, we have realized the prediction and alarming of faults of flexible machining devices. The experiments on the JCS-020 Machine Center have indicated the models are feasible and valid. They can properly eliminate the influence of the changeful machining mode and process, the factors of time-varying and random disturbances on the condition monitoring, fault diagnosis and prediction, and greatly improve robustness and adaptability of monitoring and diagnosis in the FMS environments. |
| Keywords: flexible machining device, mechanical-electronic system, dynamics model, condition monitoring, fault prediction & alarming |
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