信息融合技术在设备故障诊断中的应用研究

【作者】 彭备战；

【导师】 林德杰；

【作者基本信息】 广东工业大学 ， 检测技术与自动化装置， 2002， 硕士

【摘要】 设备故障诊断是一门各学科交叉的新技术，近20多年来，得到了迅速发展，并产生了巨大的经济效益。信息融合是近年来兴起的一门学科，在许多领域得到了广泛的研究和应用，在设备故障诊断领域的应用尚处于起步阶段。设备故障诊断中可利用的信息很多，只有充分利用有用的信息来对设备的故障进行诊断才能提高故障诊断的精度和可靠性，因此故障诊断实质上是一个多信息融合的过程。本文提出了基于人工神经网络信息融合的故障诊断，分析了单子神经网络进行故障诊断的特点，提出了集成神经网络的故障诊断模型，研究了集成神经网络的建模方法、组建原则和实现策略，并结合诊断实例进行了仿真分析，结果表明利用神经网络信息融合进行故障诊断是一种有效的方法。针对故障诊断中的不确定性，提出了基于D-S证据理论的决策融合，简要介绍了D-S证据理论的基本概念，并结合算例进行了分析。针对运用D-S证据理论时难以确定基本概率分配函数的问题，提出了神经网络与证据推理相结合的决策融合诊断方法，并通过实例验证了这种方法的可行性和有效性。更多还原

【Abstract】 Fault diagnosis is a new multi-subject-crossed technique, It has been developed rapidly in last twenty years, and it has brought huge benefit. Information fusion is a subject formed recently, it has been researched and applied in many fields. But, it is in starting stage in fault diagnosis. There are much available information in fault diagnosis. Only when the available information is used, can the precision and credibility be improved. So fault diagnosis is a process of information. The fault diagnosis model is put forward in this paper. Based on the analysis of single neural network characteristic, the model of integrated neural network is put forward. At the same time , the way to establish model, the principle to compose and the strategy to realize are given in this paper. The result based on the simulation of the example show it is a effective way by using network to deal with the characteristic information. To the incertitude of fault diagnosis, the decision-making fusion based on evidence theory is put forward. The basic conception of evidence theory is introduced. With the simulation based on the example, we can know evidence theory fusion improved the fault diagnosis precision. It is hard to give the basic probability function in the process of using the evidence theory, So the model based on network and D-S evidence is put forward. The simulation of the example show it is feasible and effective.更多还原