LANG Rongling, WANG Yuan, GAO Fei, et al., “Fault Diagnosis of Airborne Equipments Based on Similarity Search,” Chinese Journal of Electronics, vol. 22, no. 4, pp. 855-860, 2013,
Citation: LANG Rongling, WANG Yuan, GAO Fei, et al., “Fault Diagnosis of Airborne Equipments Based on Similarity Search,” Chinese Journal of Electronics, vol. 22, no. 4, pp. 855-860, 2013,

Fault Diagnosis of Airborne Equipments Based on Similarity Search

Funds:  This work is supported by the National Natural Science Foundation of China (No.61202078, No.61071139) and the National High Technology Research and Development Program of China (863 Program) (No.SQ2010AA1101356002).
More Information
  • Corresponding author: LANG Rongling, WANG Yuan, GAO Fei, PAN Lei
  • Received Date: 2012-09-01
  • Rev Recd Date: 2012-11-01
  • Publish Date: 2013-09-25
  • The flight data generated during airplane's flights can be used for fault diagnosis, which is of great importance for improving the security and reducing the cost of maintenance of airplanes. It's an important fault diagnosis method t ofind out novel patterns of flight data, but flight data has characteristics of high dimension and containing stochastic noise. In this paper, we take advantage of similarity querying method t ofind out novel patterns in order to reduce the negative effect brought by high dimension and stochastic noise. Firstly, we reduce the dimension and eliminate the stochastic noise of flight data by piecewise linear representation method. Then, the indexical tree based on distance reduction rate is created to achieve efficient search. At last, the proposed approach is evaluated with a series of experiments on simulative data and real-world data. The experimental results show that this method can be successfully applied in practice.
  • loading
  • R. Agrawal, C. Faloutsos, A. Swami, “Efficient similarity searchi n sequence databases”, Proc. 4th International ConferenceF oundations of Data Organization and Algorithms, Chicago,U SA, Vol.730, pp.69-84, 1993.
    WookJe Park, Sangmin Lee, Sanghyuk Lee and T.O. Ting, “Designs imilarity measure and application t ofault detection of laterald irectional mode flight system”, Advances in Swarm Intelligence,L ecture Notes in Computer Science, Vol.7332, pp.183-1 91, 2012.
    Duan Yanfeng, Yu Xiao, Yu Daren, “Power plant fault diagnosisb ased on DTW”, Turbine Technology, Vol.52, No.1, pp.57-60,2 010. (in Chinese)
    Lv Chunjie, Yao Yongyu, Jiang Hao, “The application of thes imilarity extraction of historical time-series in the mechanicald iagnosis”, Mechanical Research & Application, No.2, pp.21-2 3, 2009. (in Chinese)
    Rajshekhar, Gupta A., Sam anta A.N., et al., “Fault diagnosisu sing dynamic time warping”, Pattern Recognition and MachineI ntelligence, Kolkata, India, Vol.4815, pp.57-66, 2007.
    K. Chan, W. Fu, “Efficient time series matching by wavelets”, Proceedings of the 15th IEEE International Conference onD ata Engineering, IEEE Computer Society Press, Los Alamitos,p p.126-133, 1999.
    J. Lin, E.J. Keogh, “A symbolic representation of time seriesw ith implications for streaming algorithms”, Proceedings of the8 th SIGMOD Workshop on DMKD, San Diego, CA, USA, pp.2-17, 2003.
    E. Keogh, “A fast and robust method for pattern matching int ime series databases”, The 9th International Conference onT ools with Artificial Intelligence, California, USA, pp.578-584,1 997.
    N.T. Son, D.T. Anh, “An improvement of PI Pfor time series dimensionalityr eduction and its index structure”, Knowledge and Systems Engineering, Second International Conference, Ho ChiM inh City, Vietnam, pp.47-54, 2010.
    Qiu Junping, Wang Feifei, “Research on similarity search andi ndexing of time series”, Shan Dong Library Quarterly, Vol.6,pp.8-11, 2009. (in Chinese)
    Lin Ziyu, “Fast similarity search in timeseries databases with aNew indexing mechanism based on moving average”, Doctoral Thesis, Xiamen University, 2005. (in Chinese)
    Qu Jilin, “Indexing and querying of time series in data mining”,Doctoral Thesis, Tianjin University, 2006. (in Chinese)
    H.V. Jagadish, Beng Chin Ooi, Kian-Lee Tan, “Speeding ups earch in peer-to-peer networks with multi-way tree structure”,A CM International Conference on Management of Data, NewY ork, USA, pp.1-12, 2006.
    Lin Ziyu, Yang Dongqing, Wang Tengjiao, “Similar search of time series with moving average based indexing”, Journal of Software, Vol.19, No.9, pp.2349-2361, 2008.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (451) PDF downloads(945) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return