J4  2013, Vol. 47 Issue (8): 1437-1443    DOI: 10.3785/j.issn.1008-973X.2013.08.017
 机械工程

State prediction on hydraulic system of shield
HUANG Ke, ZHOU Qi-cai, ZHAO Jiong, Xiong Xiao-lei
School of Mechanical Engineering, tongji university, shanghai 201804,china
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Abstract:

In order to solve the problem that being easy to have big error through fixed model monitoring time varying system, the methods combing moving windows algorithm with grey prediction algorithm(MWGM(1,1)) was proposed. describing detailed recursive algorithm to update prediction model adopting the way of removing part of past data from modeling sequence and absorbing new ones from sampling data, and key quantities of prediction math model that were a&b were decomposed in order to simplify recursion formula. then describing how to determine the length of windows were done. the effectiveness of such MWGM(1,1) algorithm was tested by statistical data from national statistics yearbook. Taking hydraulic system of shield for example, variable-weighted auto-regressive with extra inputs algorithm constructed system model by known fault sample and testing fault sample, to gain each autoregressive coefficients for extracting feature, and the time series about this system and known state gained by gray comprehensive relational grade, and the state prediction was realized by improving grey model. The test result shows that it is helpful to make model react the hydraulic system state changes by recursive updating effectively.

 : N 941.5

 ［1］ 舒诗湖,向高,何文杰,等.灰色模型在城市中长期用水量预测中的应用［J］.哈尔滨工业大学学报,2009,02（41）： 85-87. SHU Shi-hu, XIANG Gao, HE Wen-jie, et al.Application of GM(1,1) in long-term urban water demand forecast ［J］.Journal of Harbin Institute of Technology,2009,02(41): 85-87. ［2］ 牛勇,王震宇,王红军,等.改进灰色模型在中长期电力负荷预测中的应用［J］.东北电力大学学报,2009,04（29）： 64-68. NIU Yong, WANG Zhen-yu, WANG Hong-jun, et al. Application of improved grey model for mid and long-term power demand forecasting ［J］.Journal of  Northeast Dianli university Natural science edition,2009,04(29): 64-68. ［3］ 杨胡萍,毕志鹏.粒子群优化的灰色模型在中长期负荷预测中的应用［J］.电测与仪表,2011,02(48)： 4043, 63. YANG Hu-ping, BI ZHi-peng. Particle swarm optimization-based grey model for long-term load forecasting［J］.Electrical Measurement & Instrumentation,2011,02(48): 4043, 63. ［4］ 丁屹峰,程浩忠,江峰青，等.不同增长趋势下中长期电量预测组合优化灰色模型［J］.上海交通大学学报,2003,09（37）： 13551357, 1371. DING Yi-feng, CHENG Hao-zhong, JIANG Feng-qing, et al. Combined optimum grey model for mid-long term electric capacity forecasting under different growing trends［J］.Journal of ShangHai JiaoTong University,2003,09(37): 13551357, 1371. ［5］ 刘思峰,谢乃明.灰色系统理论及其应用［M］.4版.北京：科学出版社,2010.05: 5264, 96-100. ［6］ 中华人民共和国国家统计局.国内生产总值［EB/OL］.［2012-09-15］.http:∥www.stats.gov.cn/tjsj/ndsj/2011/indexch.htm ［7］ 贺湘宇,何清华.基于有源自回归模型与模糊C-均值聚类的挖掘机液压系统故障诊断［J］.吉林大学学报：工学版,2008,01: 183-187. HE Xiang-yu, HE Qing-hua. Fault diagnosis for excavator hydraulic system based on auto-regressive with extra inputs model and fuzzy C-means clustering ［J］.Journal of Jilin University: Engineering Science,2008,01: 183-187. ［8］ CHIANG L H, KOTANCHEK M E, KORDON A K. Fault diagnosis based on Fisher discriminant analysis and support vector machines $J$. Computers and Chemical Engineering,2004,28(8): 1389-1401. ［9］ RENCHER A C.  Methods of multivariate analysis ［M］.New York: John Wiley& Sons,2002: 270-299. ［10］ 付永领,祁晓野.AMESIM系统建模和仿真：从入门到精通［M］.北京：北京航空航天大学出版社,2006.06: 155-161. ［11］ Rexroth bosch group.定量泵［EB/OL］.［2012-9-15］.http:∥www.boschrexroth.com.cn/country_units/asia/china/zh/products_/brh-i/p_pages/01_pumps/01_axialpistonpumps/01_fixeddisplacement/index.jsp