【摘要】 针对单一故障诊断方法诊断精度偏低的问题,提出了决策级信息融合故障诊断模型。该模型首先分别用BP神经网络和综合关联度故障诊断方法对故障进行诊断,然后利用D-S证据理论分别将BP神经网络和综合关联度故障诊断方法在同一时刻不同测点的诊断结果进行局部融合,最后将BP神经网络诊断的局部融合结果和综合关联度诊断的局部融合结果进行全局决策级融合,诊断对象是否有故障并判断故障的模式。离心式风机故障诊断实例证明了该方法的有效性。更多还原

【Abstract】 Directing to the low precision of single fault diagnosis method,a decision-level information fusion diagnosis system model was proposed,in which,the method based on the BP neural network and the method based on synthetically relational analysis were applied to the fault diagnosis firstly,and then the Dempster-Shafer evidence theory was utilized to partial fusions in diagnostic results,which were acquired in different test-points at the same time.At last,the decision fusion was applied to different partial fusions and got the finally diagnostic result.The sauction fan fault diagnosis example shows the validity of the dicision-level fusion fault diagnosis model.更多还原