Citation: | ZHANG Jian, LI Yanjun, CAO Yuyuan, et al. Immune SVM used in wear fault diagnosis of aircraft engine[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(7): 1419-1425. doi: 10.13700/j.bh.1001-5965.2016.0553(in Chinese) |
Aircraft engine is wearing during its service life and will finally break down. The wear fault can be diagnosed by analyzing the ferrography data of oil monitoring. The use of immune algorithm optimized support vector machine (SVM) in aircraft engine wear fault diagnosis was researched in this paper. First, the process and algorithm of SVM and immune algorithm were summarized. Then, the optimization of SVM's penalty factor, slack variable and kernel function parameters by immune algorithm was researched. The verification results of an engine's oil ferrography analysis data and adding noise data show that the method can effectively diagnose the aircraft engine wear fault and has good robustness. Finally, the impact of kernel function, multi-classification decision method, initial population size, affinity calculation formula, optimization algorithm and normalization method on diagnosis accuracy was analyzed, and the best algorithm was achieved.
[1] |
李艳军, 左洪福, 吴振锋.基于磨粒分析方法的发动机磨损故障智能诊断技术[J].南京航空航天大学学报, 2001, 33(3):221-226. http://www.cnki.com.cn/Article/CJFDTOTAL-NJHK200103003.htm
LI Y J, ZUO H F, WU Z F.Intelligent diagnostics for engine wear failure based on debris analysis[J]. Journal of Nanjing University of Aeronautics and Astronautics, 2001, 33(3):221-226(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-NJHK200103003.htm
|
[2] |
王汉功, 陈桂明.铁谱图像分析理论与技术[M].北京:科学出版社, 2005:245.
WANG H G, CHEN G M.Ferro graphic image analysis theory and technology[M]. Beijing:Science Press, 2005:245(in Chinese).
|
[3] |
李民赞.光谱分析技术及其应用[M].北京:科学出版社, 2006:1.
LI M Z.Spectral analysis technique and application[M]. Beijing:Science Press, 2006:1(in Chinese).
|
[4] |
吴振锋, 左洪福, 孙有朝.航空发动机磨损故障的常用监控手段及其对比[J].航空工程与维修, 2000, 60(5):25-26. http://www.cnki.com.cn/Article/CJFDTOTAL-KONG200005010.htm
WU Z F, ZUO H F, SUN Y C.The common monitoring techniques of aero engine and their comparison[J]. Aviation Maintenance & Engineering, 2000, 60(5):25-26(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-KONG200005010.htm
|
[5] |
邓明, 金业壮.航空发动机故障诊断[M].北京:北京航空航天大学出版社, 2012:187-191.
DENG M, JIN Y Z.The aircraft engine fault diagnosis[M]. Beijing:Beihang University Press, 2012:187-191(in Chinese).
|
[6] |
杨云, 朱家元, 张恒喜.基于新型机器学习的电子装备系统智能故障诊断研究[J].计算机工程与应用, 2003, 39(22):210-213. doi: 10.3321/j.issn:1002-8331.2003.22.068
YANG Y, ZHU J Y, ZHANG H X.Electronic equipment systems intelligent fault diagnosis based on new machine learning approach[J]. Computer Engineering and Applications, 2003, 39(22):210-213(in Chinese). doi: 10.3321/j.issn:1002-8331.2003.22.068
|
[7] |
孙铁轩, 邵春福, 计寻, 等.基于ARIMA与信息粒化SVR组合模型的交通事故时序预测[J].清华大学学报(自然科学版), 2014, 54(3):348-354. http://www.cnki.com.cn/Article/CJFDTOTAL-QHXB201403011.htm
SUN T X, SHAO C F, JI X, et al.Urban traffic accident time series prediction model based on combination of ARIMA and information granulation SVR[J]. Journal of Tsinghua University(Science and Technology), 2014, 54(3):348-354(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-QHXB201403011.htm
|
[8] |
王旭辉, 黄圣国, 曹力, 等.基于LS-SVM的航空发动机气路参数趋势在线预测[J].吉利大学学报(工学版), 2008, 38(1):239-244. http://www.cnki.com.cn/Article/CJFDTOTAL-JLGY200801048.htm
WANG X H, HUANG S G, CAO L, et al.LS-SVM based online trend prediction of gas path parameters of aero engine[J]. Journal of Jilin University (Engineering and Technology Edition), 2008, 38(1):239-244(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-JLGY200801048.htm
|
[9] |
陈立波, 宋兰琪, 宋科, 等.基于支持向量机的航空发动机磨损趋势预测[J].润滑与密封, 2008, 33(5):84-87. http://www.cnki.com.cn/Article/CJFDTOTAL-RHMF200805025.htm
CHEN L B, SONG L Q, SONG K, et al.Wear trend forecast of aviation engine based on support vector machine model[J]. Lubrication Engineering, 2008, 33(5):84-87(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-RHMF200805025.htm
|
[10] |
张周锁, 李凌均, 何正嘉.基于支持向量机的机械故障诊断方法研究[J].西安交通大学学报, 2002, 36(2):1303-1306. http://cdmd.cnki.com.cn/Article/CDMD-10407-2010020205.htm
ZHANG Z S, LI L J, HE Z J.Research on diagnosis method of machinery fault based on support vector machine[J]. Journal of Xi'an Jiaotong University, 2002, 36(2):1303-1306(in Chinese). http://cdmd.cnki.com.cn/Article/CDMD-10407-2010020205.htm
|
[11] |
SHIN H J, EOM D H, KIM S S.One-class support vector machines an application in machine fault detection and classification[J]. Computers & Industrial Engineering, 2005, 48(2):395-408.
|
[12] |
徐启华, 师军.基于支持向量机的航空发动机故障诊断[J].航空动力学报, 2005, 20(2):298-302. http://cdmd.cnki.com.cn/Article/CDMD-10143-1015534019.htm
XU Q H, SHI J.Aero-engine fault diagnosis based on support vector machine[J]. Journal of Aerospace Power, 2005, 20(2):298-302(in Chinese). http://cdmd.cnki.com.cn/Article/CDMD-10143-1015534019.htm
|
[13] |
孙超英, 刘鲁, 刘传武, 等.基于Boosting-SVM算法的航空发动机故障诊断[J].航空动力学报, 2010, 25(11):2584-2588. http://www.cnki.com.cn/Article/CJFDTOTAL-HKDI201011026.htm
SUN C Y, LIU L, LIU C W, et al.Aero-engine fault diagnosis based on Boosting-SVM[J]. Journal of Aerospace Power, 2010, 25(11):2584-2588(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-HKDI201011026.htm
|
[14] |
莫宏伟.人工免疫系统原理与应用[M].哈尔滨:哈尔滨工业大学出版社, 2003:48-57.
MO H W.Principle and application of artificial immune system[M]. Harbin:Harbin Institute of Technology Press, 2003:48-57(in Chinese).
|
[15] |
ENDOH S, TOMA N, YAMADA K.Immune algorithm for n-TSP[C]//IEEE International Conference on Systems, Man and Cybernetics.Piscataway, NJ:IEEE Press, 1998, 4:3844-3849.
|
[16] |
SASAKI M, KAWAFUKU M, TAKAHASHI K.An immune feedback mechanism based adaptive learning of neural network controller[C]//ICONIP'99, 6th International Conference on Neural Information Processing.Piscataway, NJ:IEEE Press, 1999, 2:502-507.
|
[17] |
蒋加伏, 陈荣元, 唐贤瑛, 等.基于免疫-蚂蚁算法的多约束QoS路由选择[J].通信学报, 2004, 25(8):89-95. http://www.cnki.com.cn/Article/CJFDTOTAL-TXXB200408011.htm
JIANG J F, CHEN R Y, TANG X Y, et al.A multiple constrained QoS routing based on immune-ant algorithm[J]. Journal of Communications, 2004, 25(8):89-95(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-TXXB200408011.htm
|
[18] |
颜瑞, 张祥.基于改进免疫算法优化支持向量机的钢材消费预测[J].工业工程, 2013, 16(5):90-95. http://www.cnki.com.cn/Article/CJFDTOTAL-GDJX201305017.htm
YAN R, ZHANG X.Forecasting of steel demands by using support vector machine and immune algorithm[J]. Industrial Engineering, 2013, 16(5):90-95(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-GDJX201305017.htm
|
[19] |
高文军. 基于人工免疫算法优化支持向量机的电力变压器故障诊断研究[D]. 太原: 太原理工大学, 2012.
GAO W J.Study on fault diagnosis foe power transformer based on support vector machine of artificial immune algorithm[D]. Taiyuan:Taiyuan University of Technology, 2012(in Chinese).
|