Application of non-equal interval GM(1,1) model in oil monitoring of internal combustion engine

Shi-wei Chen , Zhu-guo Li , Shou-xi Zhou

Journal of Central South University ›› 2005, Vol. 12 ›› Issue (6) : 705 -708.

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Journal of Central South University ›› 2005, Vol. 12 ›› Issue (6) : 705 -708. DOI: 10.1007/s11771-005-0073-2
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Application of non-equal interval GM(1,1) model in oil monitoring of internal combustion engine

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Abstract

The basic difference non-equal interval model GM(1,1) in grey theory was used to fit and forecast data series with non-equal lengths and different inertias, acquired from oil monitoring of internal combustion engines. The fitted and forecasted results show that the length or inertia of a sequence affects its precision very much, i. e. the bigger the inertia of a sequence is, or the shorter the length of a series is, the less the errors of fitted and forecasted results are. Based on the research results, it is suggested that short series should be applied to be fitted and forecasted; for longer series, the newer datum should be applied instead of the older datum to be analyzed by non-equal interval GM(1,1) to improve the forecasted and fitted precision, and that data sequence should be verified to satisfy the conditions of grey forecasting.

Keywords

GM(1,1) model / oil monitoring / spectrometric analysis / internal combustion engine

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Shi-wei Chen, Zhu-guo Li, Shou-xi Zhou. Application of non-equal interval GM(1,1) model in oil monitoring of internal combustion engine. Journal of Central South University, 2005, 12(6): 705-708 DOI:10.1007/s11771-005-0073-2

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References

[1]

WuJ R, OuhyoungM. Reducing the latency in headmounted display by a novel prediction method using grey system theory[J]. Comput Graph Forum, 1994, 13(3): 503-512

[2]

WangW P, PengY H, LiX Y. Fuzzy-grey prediction of cutting force uncertainty in turning[J]. Journal of Materials Processing Technology, 2002, 129(26): 663-666

[3]

LuoM, KuhnellB T. Forecasting machine condition using grey system theory[J]. Condition Monitoring and Diagnostic Technology, 1991, 1(3): 102-105

[4]

PengZ, KirkT B. Wear particle classification in a fuzzy grey system[J]. Wear, 1999, 225–229(8): 1238-1247

[5]

ZhengY, LewisR W. On the optimization concept of grey systems[J]. J App Math Modelling, 1993, 17(7): 88-392

[6]

HsuC I, WenY H. Application of grey theory and multiobjective programming towards airline network design[J]. European Journal of Operational Research, 2000, 127(1): 44-68

[7]

LuoYou-xin, ZhouJi-rong. Nonequidistance GM (1,1) model and its application in fatigue experimental data processing and on-line control [J]. Journal of Mechanical Strength, 1996, 18(3): 60-63

[8]

ChenYou-liang, SunJun. Gray prediction model of unequal time series and its application to rock creep fracture[J]. Rock and Soil Mechanics, 1995, 16(4): 8-12

[9]

SunHu-yuan, WeiXu-jun. Non-equal time interval grey model and its application [J]. Journal of Basic Science and Engineering, 1996, 4(4): 407-411

[10]

ZHANG Hong, LI Zhu-guo. Application of non-equal GM (1, 1) in processing running-in data of diesels[J]. Lubrication Engineering, 2002(1): 19–20, 24.

[11]

DengJu-longGrey System Fundamental [M], 2002, Wuhan, Huazhong University of Science and Technology Press(in Chinese)

[12]

ZhangHongResearch on Unequal Interval Grey Prediction Models and Relational Analysis for Machinery Wear Monitoring[D], 2003, Shanghai, Shanghai Jiaotong University(in Chinese)

[13]

ZhangHong, LiZhu-guo, ChenZhao-neng. Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines[J]. Tribology International, 2003, 36(10): 753-756

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