Decision Level Information Fusion Method for Equipment Diagnosis Based on BP Neural Network

Directing to the low precision of single fault diagnosis method, a decision-level information fusion diagnosis system model was proposed to obtain more reliability and more accurate diagnosis, in which, the method based on the BP neural network was applied to the fault diagnosis firstly, and then the D-S evidence theory was utilized to partial fusions in diagnostic results, which was acquired in different test-points at the same time. At last, the decision fusion was applied to partial fusions and got the finally diagnostic result. The s suction auction fan fault diagnosis example shows the validity of the decision-level fusion fault diagnosis model, which could reduce the uncertainty of decision and greatly increase the precision of diagnosis.