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There are 28674 results for: content related to: Identification of faulty sensors using principal component analysis

  1. Detection, identification, and reconstruction of faulty sensors with maximized sensitivity

    AIChE Journal

    Volume 45, Issue 9, September 1999, Pages: 1963–1976, S. Joe Qin and Weihua Li

    Version of Record online : 16 APR 2004, DOI: 10.1002/aic.690450913

  2. Detection and identification of faulty sensors in dynamic processes

    AIChE Journal

    Volume 47, Issue 7, July 2001, Pages: 1581–1593, S. Joe Qin and Weihua Li

    Version of Record online : 16 APR 2004, DOI: 10.1002/aic.690470711

  3. Probabilistic model for sensor fault detection and identification

    AIChE Journal

    Volume 49, Issue 7, July 2003, Pages: 1787–1802, Nasir Mehranbod, Masoud Soroush, Michael Piovoso and Babatunde A. Ogunnaike

    Version of Record online : 16 APR 2004, DOI: 10.1002/aic.690490716

  4. You have free access to this content
    Statistical process monitoring: basics and beyond

    Journal of Chemometrics

    Volume 17, Issue 8-9, August - September 2003, Pages: 480–502, S. Joe Qin

    Version of Record online : 22 SEP 2003, DOI: 10.1002/cem.800

  5. Data-driven fault detection and isolation for multimode processes

    Asia-Pacific Journal of Chemical Engineering

    Volume 6, Issue 3, May/June 2011, Pages: 470–483, Jialin Liu

    Version of Record online : 10 FEB 2011, DOI: 10.1002/apj.549

  6. Enhanced process monitoring for wastewater treatment systems

    Environmetrics

    Volume 19, Issue 6, September 2008, Pages: 602–617, Chang Kyoo Yoo, Kris Villez, Stijn W.H. Van Hulle and Peter A. Vanrolleghem

    Version of Record online : 18 DEC 2007, DOI: 10.1002/env.900

  7. Subspace approach to multidimensional fault identification and reconstruction

    AIChE Journal

    Volume 44, Issue 8, August 1998, Pages: 1813–1831, Ricardo Dunia and S. Joe Qin

    Version of Record online : 16 APR 2004, DOI: 10.1002/aic.690440812

  8. Improving the Performance of Exponentially Weighted Moving Average Control Charts

    Quality and Reliability Engineering International

    Volume 30, Issue 4, June 2014, Pages: 571–590, Mu'azu Ramat Abujiya, Muhammad Hisyam Lee and Muhammad Riaz

    Version of Record online : 10 APR 2013, DOI: 10.1002/qre.1509

  9. Optimal fault signal estimation

    International Journal of Robust and Nonlinear Control

    Volume 12, Issue 8, 15 July 2002, Pages: 697–727, A. A. Stoorvogel, H. H. Niemann, A. Saberi and P. Sannuti

    Version of Record online : 17 JUN 2002, DOI: 10.1002/rnc.714

  10. Data-based linear Gaussian state-space model for dynamic process monitoring

    AIChE Journal

    Volume 58, Issue 12, December 2012, Pages: 3763–3776, Qiaojun Wen, Zhiqiang Ge and Zhihuan Song

    Version of Record online : 19 MAR 2012, DOI: 10.1002/aic.13776

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    Comparison of five cluster validity indices performance in brain [18F]FET-PET image segmentation using k-means

    Medical Physics

    Volume 44, Issue 1, January 2017, Pages: 209–220, Bedor Abualhaj, Guoyang Weng, Melissa Ong, Ali Asgar Attarwala, Flavia Molina, Karen Büsing and Gerhard Glatting

    Version of Record online : 19 JAN 2017, DOI: 10.1002/mp.12025

  12. Fuzzy Interval TSK Type-2 Modeling with Parameterized Conjunctors

    Asian Journal of Control

    Volume 17, Issue 3, May 2015, Pages: 963–976, Ayse Cisel Aras and Okyay Kaynak

    Version of Record online : 23 JUL 2014, DOI: 10.1002/asjc.944

  13. Improved process monitoring using nonlinear principal component models

    International Journal of Intelligent Systems

    Volume 23, Issue 5, May 2008, Pages: 520–544, David Antory, George W. Irwin, Uwe Kruger and Geoffrey McCullough

    Version of Record online : 26 MAR 2008, DOI: 10.1002/int.20281

  14. FDI Design for Uncertain Nonlinear Systems with Both Actuator and Sensor Faults

    Asian Journal of Control

    Volume 17, Issue 1, January 2015, Pages: 213–224, Junqi Yang and Fanglai Zhu

    Version of Record online : 10 APR 2014, DOI: 10.1002/asjc.867

  15. Improved Exponentially Weighted Moving Average Control Charts for Monitoring Process Mean and Dispersion

    Quality and Reliability Engineering International

    Volume 31, Issue 2, March 2015, Pages: 217–237, Abdul Haq, Jennifer Brown, Elena Moltchanova and Amer Ibrahim Al-Omari

    Version of Record online : 2 SEP 2013, DOI: 10.1002/qre.1573

  16. The content validity index: Are you sure you know what's being reported? critique and recommendations

    Research in Nursing & Health

    Volume 29, Issue 5, October 2006, Pages: 489–497, Denise F. Polit and Cheryl Tatano Beck

    Version of Record online : 14 SEP 2006, DOI: 10.1002/nur.20147

  17. A New Nonparametric EWMA Control Chart for Monitoring Process Variability

    Quality and Reliability Engineering International

    Abdul Haq

    Version of Record online : 16 JAN 2017, DOI: 10.1002/qre.2121

  18. Performance evaluation of fault detection methods for wastewater treatment processes

    Biotechnology and Bioengineering

    Volume 108, Issue 2, February 2011, Pages: 333–344, Lluís Corominas, Kris Villez, Daniel Aguado, Leiv Rieger, Christian Rosén and Peter A. Vanrolleghem

    Version of Record online : 10 NOV 2010, DOI: 10.1002/bit.22953

  19. Improved PCA methods for process disturbance and failure identification

    AIChE Journal

    Volume 45, Issue 8, August 1999, Pages: 1688–1700, Amir Wachs and Daniel R. Lewin

    Version of Record online : 16 APR 2004, DOI: 10.1002/aic.690450808

  20. You have free access to this content
    An Area-based Methodology for the Monitoring of General Linear Profiles

    Quality and Reliability Engineering International

    Volume 33, Issue 1, February 2017, Pages: 159–181, Abed Motasemi, Adel Alaeddini and Changliang Zou

    Version of Record online : 27 APR 2016, DOI: 10.1002/qre.1998