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Wireless Sensor Failure Identification Technology for Thermal Monitoring System of NC Machine Tools based on Bayesian Networks

机译:基于贝叶斯网络的数控机床热监控系统无线传感器故障识别技术

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Wireless sensors are increasingly adopted in mechanical systems to acquire and wirelessly transmit sensed information for machine condition monitoring. For wireless sensors on spindle, the reliability of the sensors system at high rotary speed is the key factor to guarantee the validity of monitoring. How to identify sensor failure accurately and timely is essential to enhance reliability of monitoring system. To address this issue, a novel method based on the BNs was presented to distinguish sensor failure from other transmission errors. The method described causal relationships of factors inducing sensor failure by graph theory and deduced sensor failure by Bayesian statistical techniques. Experiments carried on NC machining center prove the validity of this approach.
机译:机械系统中越来越多地采用无线传感器来获取和无线传输感测到的信息,以进行机器状态监视。对于主轴上的无线传感器,传感器系统在高转速下的可靠性是保证监控有效性的关键因素。如何准确,及时地识别传感器故障,对于提高监控系统的可靠性至关重要。为了解决这个问题,提出了一种基于BN的新颖方法,以将传感器故障与其他传输错误区分开来。该方法通过图论描述了导致传感器故障的因素之间的因果关系,并通过贝叶斯统计技术描述了导致传感器故障的因素之间的因果关系。在数控加工中心进行的实验证明了该方法的有效性。

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