具有学习能力的智能诊断系统研究

随着电子设备系统的日益复杂化,依靠单一的推理技术的故障系统已难以满足复杂系统的诊断要求,将多种不同的推理技术结合起来的集成诊断系统,能够充分利用各自的优点,从而提高系统诊断的正确性和效率,是目前智能诊断研究的一个发展趋势。将研究复合系统的智能诊断问题,提出在一个复合系统的诊断过程中,通过机器学习,使基于规则的诊断和基于模型的诊断两种诊断技术相互结合,在诊断的不同阶段发挥出各自的作用,从而建立一个融合了RBD和MBD技术优点的、具有一定学习能力的智能诊断系统。

Research on intelligent diagnosis system with machine learning

With the gradual complication of some electronic system,using a single reasoning technology is more and more difficult to meet the demand of the fault diagnosis.Combining two or more reasoning technique is a trend of development of intelligent diagnosis,which can make use of their advantages and improve its efficiency.In this paper the intelligent diagnosis problem is discussed,a diagnosis architecture for the composite system is proposed,which combining rule-based diagnosis and model-based diagnosis.These two approaches work efficiently in different stage of the fault diagnosis system and with machine learning.