IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v525y2019icp1080-1087.html
   My bibliography  Save this article

The Lempel–Ziv measure based pedigree map to detect and evaluate correlation between aero-engine gas path system variables

Author

Listed:
  • Dong, Keqiang
  • Long, Linan
  • Zhang, Hong
  • Su, Xieyang

Abstract

There is a great interest in studying complexity of the aero-engine gas path time series. This paper presents a Lempel–Ziv complexity measure for analysis of aero-engine gas path system signals. By applying a binary Lempel–Ziv measure to define the absolute distance between two non-null numerical sequences, the pedigree map of systemic clustering is constructed to provide a metric for the number of distinct deterministic patterns. And then, we propose a ternary Lempel–Ziv measure, improving on the binary Lempel–Ziv measure, and making it more suited for the analysis of aero-engine gas path time series. The results indicate that the maps, demonstrating the relationship between parameters, based on ternary Lempel–Ziv measure are more vivid than the map based on binary Lempel–Ziv measure.

Suggested Citation

  • Dong, Keqiang & Long, Linan & Zhang, Hong & Su, Xieyang, 2019. "The Lempel–Ziv measure based pedigree map to detect and evaluate correlation between aero-engine gas path system variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1080-1087.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:1080-1087
    DOI: 10.1016/j.physa.2019.04.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119303930
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.04.027?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dong, Keqiang & Zhang, Hong & Gao, You, 2017. "Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 363-369.
    2. B. Podobnik & I. Grosse & D. Horvatić & S. Ilic & P. Ch. Ivanov & H. E. Stanley, 2009. "Quantifying cross-correlations using local and global detrending approaches," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 243-250, September.
    3. Zhao, Xiaojun & Shang, Pengjian & Lin, Aijing & Chen, Gang, 2011. "Multifractal Fourier detrended cross-correlation analysis of traffic signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3670-3678.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhai, Lu-Sheng & Liu, Ruo-Yu, 2019. "Local detrended cross-correlation analysis for non-stationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 222-233.
    2. Dutta, Srimonti & Ghosh, Dipak & Samanta, Shukla, 2014. "Multifractal detrended cross-correlation analysis of gold price and SENSEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 195-204.
    3. Fan, Qingju & Li, Dan, 2015. "Multifractal cross-correlation analysis in electricity spot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 17-27.
    4. Yanguang Chen, 2015. "A New Methodology of Spatial Cross-Correlation Analysis," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-20, May.
    5. Ladislav Kristoufek, 2014. "Spectrum-based estimators of the bivariate Hurst exponent," Papers 1408.6637, arXiv.org, revised Nov 2014.
    6. Yuan, Naiming & Fu, Zuntao, 2014. "Different spatial cross-correlation patterns of temperature records over China: A DCCA study on different time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 71-79.
    7. Cao, Guangxi & Xu, Longbing & Cao, Jie, 2012. "Multifractal detrended cross-correlations between the Chinese exchange market and stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4855-4866.
    8. Dong, Keqiang & Zhang, Hong & Gao, You, 2017. "Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 363-369.
    9. Cao, Guangxi & Xu, Wei, 2016. "Nonlinear structure analysis of carbon and energy markets with MFDCCA based on maximum overlap wavelet transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 505-523.
    10. Shi, Wenbin & Shang, Pengjian & Wang, Jing & Lin, Aijing, 2014. "Multiscale multifractal detrended cross-correlation analysis of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 35-44.
    11. Guo, Yaoqi & Yu, Zhuling & Yu, Chenxi & Cheng, Hui & Chen, Weixun & Zhang, Hongwei, 2021. "Asymmetric multifractal features of the price–volume correlation in China’s gold futures market based on MF-ADCCA," Research in International Business and Finance, Elsevier, vol. 58(C).
    12. Cao, Guangxi & Cao, Jie & Xu, Longbing & He, LingYun, 2014. "Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 460-469.
    13. Zhuang, Xiaoyang & Wei, Yu & Ma, Feng, 2015. "Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 101-113.
    14. Xi, Caiping & Zhang, Shuning & Xiong, Gang & Zhao, Huichang & Yang, Yonghong, 2017. "Two-dimensional multifractal cross-correlation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 96(C), pages 59-69.
    15. Pal, Mayukha & Madhusudana Rao, P. & Manimaran, P., 2014. "Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 452-460.
    16. Dutta, Srimonti & Ghosh, Dipak & Chatterjee, Sucharita, 2016. "Multifractal detrended Cross Correlation Analysis of Foreign Exchange and SENSEX fluctuation in Indian perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 188-201.
    17. Li, Wei & Lu, Xinsheng & Ren, Yongping & Zhou, Ying, 2018. "Dynamic relationship between RMB exchange rate index and stock market liquidity: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 726-739.
    18. Xi, Caiping & Zhang, Shuning & Xiong, Gang & Zhao, Huichang & Yang, Yonghong, 2017. "The application of the multifractal cross-correlation analysis methods in radar target detection within sea clutter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 839-854.
    19. Wang, Fang & Wang, Lin & Chen, Yuming, 2018. "Quantifying the range of cross-correlated fluctuations using a q–L dependent AHXA coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 454-464.
    20. Fang, Sheng & Lu, Xinsheng & Li, Jianfeng & Qu, Ling, 2018. "Multifractal detrended cross-correlation analysis of carbon emission allowance and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 551-566.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:1080-1087. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.