山西农业大学学报（自然科学版）2018，Vol.38Issue(1)：73-76,4.DOI:10.13842/j.cnki.issn1671-8151.201709022
基于BP-Adaboost算法的棉花采摘机预维修方法研究
Research on pre-maintenance method of cotton picking machine based on BP-Adaboost algorithm
摘要
Abstract
[Objective]In order to detect the possible failure of cotton picking machine and reduce the huge loss caused by large-scale fault,[Methods]a pre-maintenance method was proposed in this paper based on BP_Adaboost algorithm.Firstly, the parameters of the 8 core parts of the cotton picking machine were collected as the fault characteristic parameters.Then, the fault characteristic parameters were taken as the input values of the BP neural network,and the BP neural network weak classifier was constructed.Finally,the Adaboost strong prediction model was constructed by several BP neural network weak classifiers.[Results]The performance of Adaboost strong prediction model was verified using the actual data of the col-lected cotton picking machine.[Conclusion]The result showed that the proposed algorithm could effectively predict the fault of cotton picking machine with the accuracy of 97.4%,and it was better than the BP neural network weak predictor.关键词
棉花采摘机/预测维修/BP-Adaboost算法Key words
Cotton picking machine/Predictive maintenance/BP-Adaboost algorithm分类
信息技术与安全科学引用本文复制引用
马娜,段慧芳..基于BP-Adaboost算法的棉花采摘机预维修方法研究[J].山西农业大学学报（自然科学版）,2018,38(1):73-76,4.基金项目
国家863项目(2015BAF32B02) （2015BAF32B02）
山西农业大学科技创新基金(2016001) （2016001）
