石油与天然气化工
石油與天然氣化工
석유여천연기화공
CHEMICAL ENGINEERING OF OIL AND GAS
2013年
5期
524-527
,共4页
邢志娜%王菊香%刘洁%申刚
邢誌娜%王菊香%劉潔%申剛
형지나%왕국향%류길%신강
在用润滑油%闪点%近红外光谱%人工神经网络
在用潤滑油%閃點%近紅外光譜%人工神經網絡
재용윤활유%섬점%근홍외광보%인공신경망락
using lubricant%flash point%near-infrared spectroscopy%artificial neural network (ANN)
提出一种基于近红外光谱技术的在用润滑油闪点快速检测方法。通过比较样品光谱和混入燃油光谱之间的光谱差异进行波段筛选,利用人工神经网络方法(ANN)和偏最小二乘方法(PLS)进行建模并比较,最终确定针对3个特征波段建立的ANN 在用润滑油闪点的数学模型性能较优,模型的 R2和SEP分别达到0.9183、3.06℃。实验结果表明,ANN方法作为一种处理非线性问题的化学计量学方法,能较好地实现对在用润滑油的闪点测定。利用近红外光谱分析技术对快速判断润滑油是否混入轻质油料,为及时准确找到设备故障所在提供依据具有重要的指导意义。
提齣一種基于近紅外光譜技術的在用潤滑油閃點快速檢測方法。通過比較樣品光譜和混入燃油光譜之間的光譜差異進行波段篩選,利用人工神經網絡方法(ANN)和偏最小二乘方法(PLS)進行建模併比較,最終確定針對3箇特徵波段建立的ANN 在用潤滑油閃點的數學模型性能較優,模型的 R2和SEP分彆達到0.9183、3.06℃。實驗結果錶明,ANN方法作為一種處理非線性問題的化學計量學方法,能較好地實現對在用潤滑油的閃點測定。利用近紅外光譜分析技術對快速判斷潤滑油是否混入輕質油料,為及時準確找到設備故障所在提供依據具有重要的指導意義。
제출일충기우근홍외광보기술적재용윤활유섬점쾌속검측방법。통과비교양품광보화혼입연유광보지간적광보차이진행파단사선,이용인공신경망락방법(ANN)화편최소이승방법(PLS)진행건모병비교,최종학정침대3개특정파단건립적ANN 재용윤활유섬점적수학모형성능교우,모형적 R2화SEP분별체도0.9183、3.06℃。실험결과표명,ANN방법작위일충처리비선성문제적화학계량학방법,능교호지실현대재용윤활유적섬점측정。이용근홍외광보분석기술대쾌속판단윤활유시부혼입경질유료,위급시준학조도설비고장소재제공의거구유중요적지도의의。
A rapid NIR measurement was applied to flash point of using lubricant .The spectra band were chosen by comparing sample’s spectra and mixed fuel’s spectra .The different calibra-tion models of flash point were built by the means of ANN and PLS respectively .Then these models were compared through model valid parameter .In result ,the ANN model with three characteristic bands was optimal .Its R2 and SEP were 0 .918 3 ,3 .06 ℃ respectively .It was indi-cated that ANN method can determinate flash point of using lubricant as a non-linear chemomet-rics means ,which could take place of traditional method for rapid measurement of diesel lubri-cant quality .That’s to say ,NIR technology was an important technology to judge using lubri-cant whether mixed with light oil and provide instruction for confirming equipment failure in time .