化工自动化及仪表
化工自動化及儀錶
화공자동화급의표
CONTROL AND INSTRUMENTS IN CHEMICAL INDUSTRY
2015年
2期
160-164
,共5页
故障诊断%核非负矩阵%贡献图
故障診斷%覈非負矩陣%貢獻圖
고장진단%핵비부구진%공헌도
fault diagnosis%KNMF%contribution plots
将核非负矩阵分解方法引入到过程监控中,设计了K2和SPE统计量反映原始数据的能量波动情况,进而检测过程故障的发生。同时提出一种KNMF贡献图计算方法,根据变量和非线性数据的相关性,计算变量贡献值并绘制贡献图,用于故障辨识。在TE模型上的仿真结果验证了KNMF故障检测的良好性能,利用KNMF贡献图可以较好地辨识故障变量。
將覈非負矩陣分解方法引入到過程鑑控中,設計瞭K2和SPE統計量反映原始數據的能量波動情況,進而檢測過程故障的髮生。同時提齣一種KNMF貢獻圖計算方法,根據變量和非線性數據的相關性,計算變量貢獻值併繪製貢獻圖,用于故障辨識。在TE模型上的倣真結果驗證瞭KNMF故障檢測的良好性能,利用KNMF貢獻圖可以較好地辨識故障變量。
장핵비부구진분해방법인입도과정감공중,설계료K2화SPE통계량반영원시수거적능량파동정황,진이검측과정고장적발생。동시제출일충KNMF공헌도계산방법,근거변량화비선성수거적상관성,계산변량공헌치병회제공헌도,용우고장변식。재TE모형상적방진결과험증료KNMF고장검측적량호성능,이용KNMF공헌도가이교호지변식고장변량。
The kernel non-negative matrix factorization ( KNMF) method was introduced to the process moni-toring, and two new statistics K2 and SPE which responding to the fluctuation of raw data were designed to de-tect faults.According to the correlation between measured variables and nonlinear data, KNMF contribution plots were proposed to calculate contribution value and to draw contribution plots as the faulty variable re-quired.Simulation in Tennessee Eastman ( TE) model proves the detection performance of KNMF and making use of contribution plots can identify the faulty variable well.