基于机器学习的煤矿用气动架柱式钻机的寿命预测研究  

Study on Life Prediction of Pneumatic Column Drilling Machine Based on Machine Learning

作　　者：杨样[1] 

机构地区：[1]南阳理工学院,河南南阳473004

出　　处：《煤矿机械》2012年第10期42-44,共3页Coal Mine Machinery

摘　　要：为了能够提高对气动架柱式钻机寿命预测的准确性,从而提高煤矿生产的安全水平,深入地研究了机器学习在煤矿用气动架柱式钻机寿命预测中的应用。分析了支持向量机的基本原理;提出了遗传算法的基本流程,并且利用遗传算法对支持向量机算法进行改进;以某气动架柱式钻机为例,对其进行了寿命预测,预测结果和实测结果、BP神经网络预测结果进行比较,预测结果表明该方法具有较高的寿命预测精度。In order to improve correctness of life prediction of pneumatic column drilling machine,and improve safe level of coal mine production,and application of machine learning on life prediction of pneumatic column drilling machine is studied in depth.The basic theory of support vector machine is analyzed,and then basic procedure of genetic algorithm is put forward,and amendment of support vector machine algorithm is carried out based on genetic algorithm,the life prediction of a pneumatic column drilling machine is carried out,and the prediction results are compared with actual test results and predicting results obtained by BP neutral network,and results show that this method has a higher predicting precision.

关 键 词：机器学习 支持向量机 气动架柱式钻机 寿命预测 

分 类 号：TD421[矿业工程—矿山机电]