工业仪表与自动化装置
工業儀錶與自動化裝置
공업의표여자동화장치
INDUSTRIAL INSTRUMENTATION & AUTOMATION
2015年
1期
50-53,57
,共5页
矿井通风机%故障诊断%二次回归方程%差分进化算法%分类识别
礦井通風機%故障診斷%二次迴歸方程%差分進化算法%分類識彆
광정통풍궤%고장진단%이차회귀방정%차분진화산법%분류식별
mine ventilation machine%fault diagnosis%two regression equations%differential evolu-tion algorithm%classification
针对矿井通风机故障诊断过程中样本数据有限的特点,提出了一种经差分进化算法优化的二次回归诊断方法。将样本数据分为建模数据和测试数据,测试结果表明该方法具有适用性强、操作简单、精准度高,且无需太多样本数据等特点,值得推广。
針對礦井通風機故障診斷過程中樣本數據有限的特點,提齣瞭一種經差分進化算法優化的二次迴歸診斷方法。將樣本數據分為建模數據和測試數據,測試結果錶明該方法具有適用性彊、操作簡單、精準度高,且無需太多樣本數據等特點,值得推廣。
침대광정통풍궤고장진단과정중양본수거유한적특점,제출료일충경차분진화산법우화적이차회귀진단방법。장양본수거분위건모수거화측시수거,측시결과표명해방법구유괄용성강、조작간단、정준도고,차무수태다양본수거등특점,치득추엄。
According to the characteristics of the sample data is limited in ventilator fault diagnosis process, put forward the differential evolution algorithm to optimize two regression diagnosis method.The sample data into the modeling data and test data, test results show that the method has features such as strong applicability, simple operation, high accuracy and does not need too many sample data, worthy of promotion.