| Summary: | Gearbox as an important component of the power system of agricultural machinery, plays a vital role in the normal operation of agricultural equipment. At present, the diagnosis of gearbox fault is mainly based on expert experience, and the accuracy is not guaranteed. In view of the achievements of Elman neural network in fault diagnosis, Elman neural network is used as the basic model of gearbox fault diagnosis. Considering that the Elman neural network is sensitive to the initial weight threshold and easy to fall into the local minimum, the mind evolution algorithm is introduced into the parameter optimization of the Elman neural network fault diagnosis model. Experimental results show that this assumption is successful, and the new model not only reduces diagnostic errors but also improves stability.
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