论文部分内容阅读
贝叶斯网络的社别故障诊断方法使为更好解决其不完整性、不确定性而产生的,能够有效应用于关联性不强、设备内部构造更加复杂的诊断工作中,因而在许多方面都得到了较好应用。当前设备故障中的不确定性,主要是概率论与模糊逻辑等方法。本文主要研究了贝叶斯网络中设备故障的诊断方法,并说明这种诊断方法在设备故障中的应用优势,使其在故障诊断中的应用发展更加完善。
The method of Bayesian Network’s social-based fault diagnosis makes it better to solve its incompleteness and uncertainty, and it can be effectively used in the diagnosis of less relatedness and more complex structure inside the device. In many aspects Have been better applied. The current equipment failure in the uncertainty, mainly the probability theory and fuzzy logic and other methods. This paper mainly studies the method of diagnosing equipment faults in Bayesian networks, and illustrates the application advantages of this method in equipment faults, so as to make its application in fault diagnosis more perfect.