摘要
利用人工神经网络具有自适应、自学习的BP算法,结合煤矿桥(门)式起重机检验的特点,建立了适用于桥(门)式起重机检验评价的BP神经网络模型,通过在MATLAB平台环境下进行设计和开发,并将训练结果与桥(门)式起重机大小车轨道相关的距离偏差实际检测评价结果进行了比较,验证了该BP神经网络模型运用于煤矿起重机检验工作是可行的。
Taking the advantage of the selfsuitable and self-education BP algorithm possessed by the artificial neural network and combining the inspection features of the bridge or portal crane of coal mine,an improved BP Artificial Neural Network model which adapt to the bridge or portal crane inspection is established,and the BP neural network model is trained and realized in the environment of MATLAB.By comparison of its simulation training results and the factual the bridge or portal crane inspection results,It is confirmed that it is feasible that the BP neural network model is used to inspect the bridge or portal crane of the coal mine.
出处
《煤矿机械》
北大核心
2012年第8期212-214,共3页
Coal Mine Machinery
