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中文摘要：
为了减少对知识化制造系统生产故障的误诊和漏诊，本文首先提出了一取的故障监测方法，该方法先对采集的信号进行多维特征提取，再通过归纳学习建立设备的正常状态空间，并以此来判断设备的故障状态。然后，提出一种故障误判概率控制方法。通过多维特征提取和误判概率控制，可以很好地减少对故障的漏判和误判。仿真实验证实了该故障监测方法的有效性。
英文摘要：
In order to minimize the probability of false diagnosis in knowledgeable manufacturing systems, a new approach based on inductive learning to fault detection is proposed in this paper. Firstly, multi-dimension features are extracted from sampled signals and compose a normal state space of equipment by inductive learning, according to which an abnormal signal can be detected. A method of controlling the probability of false diagnosis is then proposed to greatly decrease it.The effectiveness of the approach is verified by simulation examples.
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