Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Optimal Weighted Wilcoxon–Mann–Whitney Test for Prioritized Outcomes Read chapter Read first chapter

2018 | OriginalPaper | Chapter

6. Wavelet-Based Profile Monitoring Using Order-Thresholding Recursive CUSUM Schemes

Authors : Ruizhi Zhang, Yajun Mei, Jianjun Shi

Published in: New Frontiers of Biostatistics and Bioinformatics

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

With the rapid development of advanced sensing technologies, rich and complex real-time profile or curve data are available in many processes in biomedical sciences and manufacturing. These profile data provide valuable intrinsic information about the performance or properties of the process, subject, or product, and it is often desirable to utilize them to develop efficient methodologies for process monitoring and fault diagnosing. In this article, we propose a novel wavelet-based profile monitoring procedure that is based on the order-thresholding transformation of recursive CUSUM statistics of multiple wavelet coefficients. Extensive simulation studies and a case study of tonnage profile data demonstrate that our proposed procedure is efficient for detecting the unknown local changes on the profile.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Mammogram Diagnostics Using Robust Wavelet-Based Estimator of Hurst Exponent
next chapter Estimating the Confidence Interval of Evolutionary Stochastic Process Mean from Wavelet Based Bootstrapping
Literature
Chang, S. I., & Yadama, S. (2010). Statistical process control for monitoring non-linear profiles using wavelet filtering and b-spline approximation. International Journal of Production Research, 48(4), 1049–1068.CrossRef
Chang, T. C., & Gan, F. F. (2006). Monitoring linearity of measurement gauges. Journal of Statistical Computation and Simulation, 76(10), 889–911.MathSciNetCrossRef
Chen, S., & Nembhard, H. B. (2011). A high-dimensional control chart for profile monitoring. Quality and Reliability Engineering International, 27(4), 451–464.CrossRef
Chicken, E., Pignatiello, J. J., Jr., & Simpson, J. R. (2009). Statistical process monitoring of nonlinear profiles using wavelets. Journal of Quality Technology, 41(2), 198.CrossRef
Donoho, D. L., & Johnstone, I. M. (1994). Ideal spatial adaptation by wavelet shrinkage. Biometrika, 81(3), 425–455.MathSciNetCrossRef
Donoho, D. L., & Johnstone, I. M. (1995). Adapting to unknown smoothness via wavelet shrinkage. Journal of the American Statistical Association, 90(432), 1200–1224.MathSciNetCrossRef
Donoho, D. L., & Johnstone, I. M. (1998). Minimax estimation via wavelet shrinkage. The Annals of Statistics, 26(3), 879–921.MathSciNetCrossRef
Fan, J. (1996). Test of significance based on wavelet thresholding and Neyman’s truncation. Journal of the American Statistical Association, 91(434), 674–688.MathSciNetCrossRef
Fan, J., & Lin, S. K. (1998). Test of significance when data are curves. Journal of the American Statistical Association, 93(443), 1007–1021.MathSciNetCrossRef
Gardner, M. M., Lu, J. C., Gyurcsik, R. S., Wortman, J. J., Hornung, B. E., Heinisch, H. H., et al. (1997). Equipment fault detection using spatial signatures. IEEE Transactions on Components, Packaging, and Manufacturing Technology: Part C, 20(4), 295–304.CrossRef
Hall, P., Poskitt, D. S., & Presnell, B. (2001). A functional data-analytic approach to signal discrimination. Technometrics, 43(1), 1–9.MathSciNetCrossRef
James, W., & Stein, C. (1961). Estimation with quadratic loss. In Proceedings of the fourth Berkeley symposium on mathematical statistics and probability (vol. 1, pp. 361–379).
Jeong, M. K., Lu, J. C., & Wang, N. (2006). Wavelet-based SPC procedure for complicated functional data. International Journal of Production Research, 44(4), 729–744.CrossRef
Jin, J., & Shi, J. (1999). Feature-preserving data compression of stamping tonnage information using wavelets. Technometrics, 41(4), 327–339.CrossRef
Jin, J., & Shi, J. (2001). Automatic feature extraction of waveform signals for in-process diagnostic performance improvement. Journal of Intelligent Manufacturing, 12(3), 257–268.CrossRef
Kang, L., & Albin, S. L. (2000). On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 32(4), 418.CrossRef
Kazemzadeh, R. B., Noorossana, R., & Amiri, A. (2008). Phase I monitoring of polynomial profiles. Communications in Statistics–Theory and Methods, 37(10), 1671–1686.MathSciNetCrossRef
Lee, J., Hur, Y., Kim, S. H., & Wilson, J. R. (2012). Monitoring nonlinear profiles using a wavelet-based distribution-free CUSUM chart. International Journal of Production Research, 50(22), 6574–6594.CrossRef
Lei, Y., Zhang, Z., & Jin, J. (2010). Automatic tonnage monitoring for missing part detection in multi-operation forging processes. Journal of Manufacturing Science and Engineering, 132(5), 051010.CrossRef
Liu, K., Zhang, R., & Mei, Y. (2017). Scalable sum-shrinkage schemes for distributed monitoring large-scale data streams. Statistica Sinica (Accepted).
Lorden, G. (1971). Procedures for reacting to a change in distribution. The Annals of Mathematical Statistics, 42(6), 1897–1908.MathSciNetCrossRef
Lorden, G., & Pollak, M. (2008). Sequential change-point detection procedures that are nearly optimal and computationally simple. Sequential Analysis, 27(4), 476–512.MathSciNetCrossRef
Mallat, S. (1999). A wavelet tour of signal processing. London: Academic Press.MATH
Mallat, S. G. (1989). Multifrequency channel decompositions of images and wavelet models. IEEE Transactions on Acoustics, Speech, and Signal Processing 37(12), 2091–2110.CrossRef
Moustakides, G. V. (1986). Optimal stopping times for detecting changes in distributions. The Annals of Statistics, 14(4), 1379–1387.MathSciNetCrossRef
Neyman, J. (1937). Smooth test for goodness of fit. Scandinavian Actuarial Journal, 20(3–4), 149–199.CrossRef
Paynabar, K., Zou, C., & Qiu, P. (2016). A change-point approach for phase-i analysis in multivariate profile monitoring and diagnosis. Technometrics, 58(2), 191–204.MathSciNetCrossRef
Qiu, P., Zou, C., & Wang, Z. (2010). Nonparametric profile monitoring by mixed effects modeling. Technometrics, 52(3), 265–277.MathSciNetCrossRef
Zhou, C., Liu, K., Zhang, X., Zhang, W., & Shi, J. (2016). An automatic process monitoring method using recurrence plot in progressive stamping processes. IEEE Transactions on Automation Science and Engineering, 13(2), 1102–1111.CrossRef
Zhou, S., Sun, B., & Shi, J. (2006). An SPC monitoring system for cycle-based waveform signals using Haar transform. IEEE Transactions on Automation Science and Engineering, 3(1), 60–72.CrossRef
Zou, C., & Qiu, P. (2009). Multivariate statistical process control using lasso. Journal of the American Statistical Association, 104(488), 1586–1596.MathSciNetCrossRef
Zou, C., Qiu, P., & Hawkins, D. (2009). Nonparametric control chart for monitoring profiles using change point formulation and adaptive smoothing. Statistica Sinica, 19(3), 1337–1357.MathSciNetMATH
Zou, C., Tsung, F., & Wang, Z. (2007). Monitoring general linear profiles using multivariate exponentially weighted moving average schemes. Technometrics, 49(4), 395–408.MathSciNetCrossRef
Zou, C., Wang, Z., Zi, X., & Jiang, W. (2015). An efficient online monitoring method for high-dimensional data streams. Technometrics, 57(3), 374–387.MathSciNetCrossRef
Zou, C., Zhou, C., Wang, Z., & Tsung, F. (2007). A self-starting control chart for linear profiles. Journal of Quality Technology, 39(4), 364–375.CrossRef
Metadata
Title
Wavelet-Based Profile Monitoring Using Order-Thresholding Recursive CUSUM Schemes
Authors
Ruizhi Zhang
Yajun Mei
Jianjun Shi
Copyright Year
2018
Book
New Frontiers of Biostatistics and Bioinformatics

Print ISBN: 978-3-319-99388-1

Electronic ISBN: 978-3-319-99389-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-99389-8_6

Premium Partner

    Image Credits