SCI和EI收录∣中国化工学会会刊

Chinese Journal of Chemical Engineering ›› 2021, Vol. 29 ›› Issue (1): 253-265.DOI: 10.1016/j.cjche.2020.08.035

• Process Systems Engineering and Process Safety • Previous Articles     Next Articles

Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework

Muhammad Nawaz1, Abdulhalim Shah Maulud1,2, Haslinda Zabiri1, Syed Ali Ammar Taqvi3, Alamin Idris4   

  1. 1 Department of Chemical Engineering, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia;
    2 Centre of Contaminant Control&Utilization(CenCoU), Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia;
    3 Department of Chemical Engineering, NED University of Engineering&Technology, Karachi 75270, Pakistan;
    4 Department of Chemical and Engineering Sciences, Karlstad University, Karlstad, Sweden
  • Received:2020-06-03 Revised:2020-07-30 Online:2021-04-02 Published:2021-01-28
  • Contact: Abdulhalim Shah Maulud
  • Supported by:
    The authors would like to acknowledge the Universiti Teknologi PETRONAS (UTP), Chemical Engineering Department for the technical and administrative support and the financial support from the Yayasan UTP grant (Cost centre: 015LC0-132).

Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework

Muhammad Nawaz1, Abdulhalim Shah Maulud1,2, Haslinda Zabiri1, Syed Ali Ammar Taqvi3, Alamin Idris4   

  1. 1 Department of Chemical Engineering, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia;
    2 Centre of Contaminant Control&Utilization(CenCoU), Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia;
    3 Department of Chemical Engineering, NED University of Engineering&Technology, Karachi 75270, Pakistan;
    4 Department of Chemical and Engineering Sciences, Karlstad University, Karlstad, Sweden
  • 通讯作者: Abdulhalim Shah Maulud
  • 基金资助:
    The authors would like to acknowledge the Universiti Teknologi PETRONAS (UTP), Chemical Engineering Department for the technical and administrative support and the financial support from the Yayasan UTP grant (Cost centre: 015LC0-132).

Abstract: Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety. Small or incipient irregularities may lead to severe degradation in complex chemical processes, and the conventional process monitoring techniques cannot detect these irregularities. In this study to improve the performance of monitoring, an online multiscale fault detection approach is proposed by integrating multiscale principal component analysis (MSPCA) with cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts. The new Hotelling's T2 and square prediction error (SPE) based fault detection indices are proposed to detect the incipient irregularities in the process data. The performance of the proposed fault detection methods was tested for simulated data obtained from the CSTR system and compared to that of conventional PCA and MSPCA based methods. The results demonstrate that the proposed EWMA based MSPCA fault detection method was successful in detecting the faults. Moreover, a comparative study shows that the SPE-EWMA monitoring index exhibits a better performance with lower values of missed detections ranging from 0% to 0.80% and false alarms ranging from 0% to 21.20%.

Key words: Chemical process system, CSTR, Fault detection, Multiscale, Principal component analysis, Process monitoring

摘要: Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety. Small or incipient irregularities may lead to severe degradation in complex chemical processes, and the conventional process monitoring techniques cannot detect these irregularities. In this study to improve the performance of monitoring, an online multiscale fault detection approach is proposed by integrating multiscale principal component analysis (MSPCA) with cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts. The new Hotelling's T2 and square prediction error (SPE) based fault detection indices are proposed to detect the incipient irregularities in the process data. The performance of the proposed fault detection methods was tested for simulated data obtained from the CSTR system and compared to that of conventional PCA and MSPCA based methods. The results demonstrate that the proposed EWMA based MSPCA fault detection method was successful in detecting the faults. Moreover, a comparative study shows that the SPE-EWMA monitoring index exhibits a better performance with lower values of missed detections ranging from 0% to 0.80% and false alarms ranging from 0% to 21.20%.

关键词: Chemical process system, CSTR, Fault detection, Multiscale, Principal component analysis, Process monitoring