微型嵌入式系统故障诊断方法综述
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摘要
随着物联网和大数据的高速发展,微型嵌入式系统已经广泛应用于外卖、共享单车、运输、快递和智能家居等行业之中。现有的故障诊断研究主要集中在传统嵌入式系统上,因此针对微型嵌入式系统故障诊断文献相对较少。针对上述问题和结合该系统的特点(有限计算能力和存储空间),提出了一类适合于微型嵌入式系统故障诊断方法分类方法,将其分为两大类,即本地故障诊断方法和远程故障诊断方法。讲述了微型嵌入式系统故障诊断方法的核心思想,总结出各方法在微型嵌入式系统上运用的优缺点和应该注意的问题,最后讨论了微型嵌入式系统故障诊断亟待解决的问题。
Nowadays,with the rapid development of Internet of things and big data,micro-embedded systems had been widely used in takeaway and sharing industries such as shared bikes,transportation,express delivery and smart home. Existing fault diagnosis research mainly focuses on traditional embedded systems. Therefore,relatively few fault diagnosis documents for micro-embedded systems. To solve the above problems and combine the characteristics of the system(limited computing capacity and storage space),this paper proposed a class of fault diagnosis method classification methods suitable for miniature embedded systems,divided into two categories,namely local fault diagnosis methods and remote fault diagnosis method. Then this paper described the core idea of the fault diagnosis method for micro-embedded systems,summarized the advantages and disadvantages of each method used in micro-embedded systems,and the problems that should be noted. Finally,this paper discussed the problems that need to be solved in the fault diagnosis of miniature embedded systems.
Nowadays,with the rapid development of Internet of things and big data,micro-embedded systems had been widely used in takeaway and sharing industries such as shared bikes,transportation,express delivery and smart home. Existing fault diagnosis research mainly focuses on traditional embedded systems. Therefore,relatively few fault diagnosis documents for micro-embedded systems. To solve the above problems and combine the characteristics of the system(limited computing capacity and storage space),this paper proposed a class of fault diagnosis method classification methods suitable for miniature embedded systems,divided into two categories,namely local fault diagnosis methods and remote fault diagnosis method. Then this paper described the core idea of the fault diagnosis method for micro-embedded systems,summarized the advantages and disadvantages of each method used in micro-embedded systems,and the problems that should be noted. Finally,this paper discussed the problems that need to be solved in the fault diagnosis of miniature embedded systems.
引文
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[2]Penhaker M,ˇCerny M,Martinák L,et al.Home Care:smart embedded biotelemetry system[J].IFMBE Proceedings,2007,14(3):711-714.
[3]涂刚,阳富民,胡贯荣.嵌入式操作系统综述[J].计算机应用研究,2000,17(11):4-5,9.(Tu Gang,Yang Fumin,Hu Guanrong.A survey of embedded operating systems[J].Application Research of Computers,2000,17(11):4-5,9.)
[4]王福刚,杨文君,葛良全.嵌入式系统的发展与展望[J].计算机测量与控制,2014,22(12):3843-3847,3863.(Wang Fugang,Yang Wenjun,Ge Liangquan.Development and prospect of embedded system[J].Computer Measurement&Control,2014,22(12):3843-3847,3863.)
[5]Pedram M.Power optimization and management in embedded systems[C]//Proc of Asia and South Pacific Design Automation Conference.New York:ACM Press,2001:239-244.
[6]Wiiisky A S.A survey of design methods for failure detection in dynamic systems[J].Automatica,1976,12(6):601-611.
[7]李红卫,杨东升,孙一兰,等,智能故障诊断方法研究综述和展望[J].计算机工程与设计,2013,34(2):632-637.(Li Hongwei,Yang Dongsheng,Sun Yilan,et al.Study review and prospect of intelligent fault diagnosis technique[J].Computer Engineering and Design,2013,34(2):632-637.)
[8]Kelkar S,Kamal R.Adaptive fault diagnosis algorithm for controller area network[J].IEEE Trans on Industrial Electronics,2014,61(10):5527-5537.
[9]Pan Jun,Chen Jinglong,Zi Yanyang,et al.Mono-component feature extraction for mechanical fault diagnosis using modified empirical wavelet transform via data-driven adaptive Fourier spectrum segment[J].Mechanical Systems&Signal Processing,2016(5):160-183.
[10]Mhamdi L,Dhouibi H,Liouane N,et al.Multiple fault diagnosis using mathematical models[C]//Proc of the 9th Asian Control Confe-rence.Piscataway,NJ:IEEE Press,2013:1-6.
[11]Gao Zhiwei,Cecati C,Ding S.A survey of fault diagnosis and faulttolerant techniques,partⅡ:fault diagnosis with knowledge-based and hybrid/active approaches[J].IEEE Trans on Industrial Electronics,2015,62(6):3768-3774.
[12]Gao Zhiwei,Cecati C,Ding S.A survey of fault diagnosis and faulttolerant techniques,partⅠ:fault diagnosis with model-based and signal-based approaches[J].IEEE Trans on Industrial Electronics,2015,62(6):3757-3767.
[13]Venkatasubramanian V,Rengaswamy R,Yin Kewen,et al.A review of process fault detection and diagnosis,partⅠ:quantitative modelbased methods[J].Computers&Chemical Engineering,2003,27(3):293-311.
[14]周东华,胡艳艳.动态系统的故障诊断技术[J].自动化学报,2009,35(6):748-758.(Zhou Donghua,Hu Yanyan.Fault diagnosis techniques for dynamic systems[J].Acta Automatica Sinica,2009,35(6):748-758.)
[15]Venkatasubramanian V,Rengaswamy R,Kavuri S N,et al.A review of process fault detection and diagnosis,partⅢ:process history based methods[J].Computers&Chemical Engineering,2003,27(3):327-346.
[16]Venkatasubramanian V,Rengaswamy R,Kavuri S N.A review of process fault detection and diagnosis,partⅡ:qualitative models and search strategies[J].Computers&Chemical Engineering,2003,27(3):313-326.
[17]Iri M,Aoki K,O’Shima E,et al.An algorithm for diagnosis of system failures in the chemical process[J].Computers&Chemical Engineering,1979,3(1):489-493.
[18]杨帆,萧德云.SDG建模及其应用的进展[J].控制理论与应用,2005,22(5):767-774.(Yang Fan,Xiao Deyun.Review of SDG modeling and its application[J].Control Theory&Applications,2005,22(5):767-774.)
[19]刘洪刚,吴建军,陈小前,等.基于SDG的智能故障诊断方法研究[J].系统工程与电子技术,2002,24(1):103-104.(Liu Honggang,Wu Jianjun,Chen Xiaoqian,et al.Study on the SDG-based intelligent fault diagnosis method[J].Systems Engineering and Electronics,2002,24(1):103-104.)
[20]Liu Yingjie,Xie Gang,Yang Yunyun.Fault location approach based on fuzzy five-range SDG and hierarchical method[C]//Proc of the27th Chinese Control and Decision Conference.Piscataway,NJ:IEEE Press,2015:2980-2985.
[21]Peng Di,Geng Zhiqiang,Zhu Qunxiong.A multilogic probabilistic signed directed graph fault diagnosis approach based on Bayesian inference[J].Industrial&Engineering Chemistry Research,2014,53(23):9792-9804.
[22]Smaili R,Harabi R E,Abdelkrim M.Fault diagnosis based on graphical tools for multi-energy processes[J].IFAC Proceedings Volumes,2014,47(3):7073-7078.
[23]Liu Yingjie,Meng Qinghao,Zeng Ming,et al.Fault diagnosis method based on probability extended SDG and fault index[C]//Proc of Intelligent Control and Automation.Piscataway,NJ:IEEE Press,2016:2868-2873.
[24]杨恒占,张可,钱富才.基于模糊分层SDG模型的故障推理方法[J].计算机系统应用,2017,26(4):104-109.(Yang Hengzhan,Zhang Ke,Qian Fucai.Fault reasoning method based on fuzzy hierarchical SDG model[J].Computer Systems&Applications,2017,26(4):104-109.)
[25]李娟,周东华,司小胜,等.微小故障诊断方法综述[J].控制理论与应用,2012,29(12):1517-1529.(Li Juan,Zhou Donghua,Si Xiaosheng,et al.Review of incipient fault diagnosis methods[J].Control Theory&Applications,2012,29(12):1517-1529.)
[26]Shakeri M,Raghavan V,Pattipati K R,et al.Sequential testing algorithms for multiple fault diagnosis[J].IEEE Trans on Systems,Man,and Cybernetics,Part A:Systems and Humans,1997,30(1):1-14.
[27]Ge Ning,Nakajima S,Pantel M.Online diagnosis of accidental faults for real-time embedded systems using a hidden Markov model[J].Simulation-Transactions of the Society for Modeling and Simulation International,2015,91(10):851-868.
[28]Yuan Shengfan,Chu Fulei.Support vector machines-based fault diagnosis for turbo-pump rotor[J].Mechanical Systems&Signal Processing,2006,20(4):939-952.
[29]Yang Shunkun.A fault diagnosis model for embedded software based on FMEA/FTA and Bayesian network[C]//Proc of IEEE International Conference on Reliability.Piscataway,NJ:IEEE Press,2009:778-782.
[30]Chen Guorong,Yan Ping,Yi Runzhong,et al.Fault diagnosis method based on system-phenomenon-fault tree[J].Chinese Journal of Mechanical Engineering,2011,24(3):466-473.
[31]Ma Chongguo,Wang Jianguo,Li Yazhou.The remote monitoring management and fault diagnosis system of the distributed open numerical control system[J].Key Engineering Materials,2014,589-590:746-751.
[32]Angeli C.Online expert systems for fault diagnosis in technical processes[J].Expert Systems,2008,25(2):115-132.
[33]Ding Zhiqin.Research on Internet-based open remote fault diagnosis expert system[C]//Proc of International Conference on Information and Multimedia Technology.Piscataway,NJ:IEEE Press,2009:1-4.
[34]Zhang Jianhu,Lei Lei,Li Jiafeng,et al.Research on electronic equipment fault diagnosis expert system based on embedded Linux[J].Advanced Materials Research,2013,683:837-840.
[35]李秀喜,吉世明.基于半定量SDG模型的化工过程故障诊断[J].清华大学学报:自然科学版,2012,52(8):1112-1115,1129.(Li Xiuxi,Ji Shiming.Based on semi-quantitative SDG model chemical process fault diagnosis[J].Journal of Tsinghua University:Science and Technology,2012,52(8):1112-1115,1129.)
[36]Wang Yingying,Li Qiuju,Chang Ming,et al.Research on fault diagnosis expert system based on the neural network and the fault tree technology[J].Procedia Engineering,2012,31(16):1206-1210.
[37]Huang N E,Shen Zheng,Long S R.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series[J].Proceedings:Mathematical,Physical and Engineering Sciences,1998,454(1971):903-995.
[38]Dybala J,Zimroz R.Rolling bearing diagnosing method based on empirical mode decomposition of machine vibration signal[J].Applied Acoustics,2014,77(3):195-203.
[39]Gao Q,Duan C,Fan H,et al.Rotating machine fault diagnosis using empirical mode decomposition[J].Mechanical Systems&Signal Processing,2008,22(5):1072-1081.
[40]Meng Lingjie,Xiang Jiawei,Wang Yanxue,et al.A hybrid fault diagnosis method using morphological filter-translation invariant wavelet and improved ensemble empirical mode decomposition[J].Mechanical Systems and Signal Processing,2015,50-51(1):101-115.
[41]Zhang Xiaoyuan,Liang Yitao,Zhou Jianzhong.A novel bearing fault diagnosis model integrated permutation entropy,ensemble empirical mode decomposition and optimized SVM[J].Measurement,2015,69(6):164-179.
[42]Amarnath M,Krishna I R P.Empirical mode decomposition of acoustic signals for diagnosis of faults in gears and rolling element bearings[J].IET Science Measurement&Technology,2012,6(4):279-287.
[43]李尔国,俞金寿.PCA在过程故障检测与诊断中的应用[J].华东理工大学学报,2001,27(5):572-576.(Li Erguo,Yu Jinshou.Fault detection and diagnosis based on principal component analysis[J].Journa1 of East China University of Science and Technology,2001,27(5):572-576.)
[44]Gharavian M H,Ganj F A,Ohadi A R,et al.Comparison of FDA-based and PCA-based features in fault diagnosis of automobile gearboxes[J].Neurocomputing,2013,121(18):150-159.
[45]Ma Hehe,Hu Yi,Shi Hongbo.A novel local neighborhood standardization strategy and its application in fault detection of multimode processes[J].Chemometrics and Intelligent Laboratory Systems,2012,118(7):287-300.
[46]Lu Yunsong,Wang Fuli,Chang Yuqing,et al.PCA-SDG based fault diagnosis on CAPL furnace temperature system[C]//Proc of the25th Control and Decision Conference.Piscataway,NJ:IEEE Press,2013:3550-3554.
[47]Wang Chunxia,Hu Jing,Wen Chenlin.Multi-level PCA and its application in fault diagnosis[C]//Proc of the 26th Chinese Control and Decision Conference.Piscataway,NJ:IEEE Press,2014:2810-2814.(下转第1292页)
[48]Yang Junyan,Zhang Youyun,Zhu Yongsheng.Intelligent fault diagnosis of rolling element bearing based on SVMs and fractal dimension[J].Mechanical Systems&Signal Processing,2007,21(5):2012-2024.
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