CAJ | 학술논문

目前带式输送机应用范围广，且日益大型化、复杂化，但随之而来的维修、检测、安全性等问题也日益突出。故障诊断能够处理以上多方面问题，为当下研究重点。本文以BP神经网络为理论支撑，建立具有预测功能的BP神经网络故障诊断模型，对提高故障诊断的识别、分类能力以及故障定位能力有很大帮助，仿真结果显示有良好的诊断效果。
목전대식수송궤응용범위엄，차일익대형화、복잡화，단수지이래적유수、검측、안전성등문제야일익돌출。고장진단능구처리이상다방면문제，위당하연구중점。본문이BP신경망락위이론지탱，건립구유예측공능적BP신경망락고장진단모형，대제고고장진단적식별、분류능력이급고장정위능력유흔대방조，방진결과현시유량호적진단효과。
The belt conveyor is more and more widely used these days,with increasingly large-scale and complicated trend,but followed by more serious problems in maintenance,detection,and safety,etc.Fault diagnosis can be used to deal with these problems,which is the research focus at present.The BP neural network fault diagnosis model with predic-tion function is built in the paper with BP neural network as the theoretic support,which is very helpful for improving recog-nition of the fault diagnosis,classification capacity,and fault positioning capacity.The simulation result shows excellent di-agnosis effects.