Research On Gear-box Intelligent Fault Detection Based On Neural Network

Gearbox is one of the most important elements in a tractor. It is significant to study the condition of monitoring and fault diagnosis of gearbox. This thesis aims at the investigation of automatic diagnosis techniques of gearbox.After introducing the main faults of gear and the causes of them, the project using neural-network in diagnosing is put forward. Following the steps of neural-network being used in pattern recognition, the paper is made up for three parts. Firstly, this paper illustrates the building of the indoor load-adding testing system applying on the study of diagnosis experiment and it's working principle. Secondly this paper introducing the way in transacting the signal and getting character of fault. It is the kst one that training the neural-network and testing it The later two parts are emphases of the paper. The software programmed by myself works out the task of the later two parts. The software includes support for XML. Using it the software can mark the project. The engine of MATLAB accomplishes the task of signal processing and neural-network. Using the source of MATLAB can reduce the load of programming. In this paper, a way to improve the BP arithmetic based on PCA theory is expounded. Trough experiment it can be proved that the improvement can notable lessen time in train network. At kst after dealing with the signal collected in test-bed for simukting the broken-down gear-box, using the software a neural-network is designed. After being trained and testing the neural-network is proved to reach the require of diagnose for gear-box.