Monitoring structural aspects of pastes undergoing continuous extrusion using signal processing of pressure data

被引:10
|
作者
Russell, BD
Lasenby, J
Blackburn, S
Wilson, DI
机构
[1] Univ Cambridge, Dept Chem Engn, Cambridge CB2 3RA, England
[2] Univ Cambridge, Dept Engn, Signal Proc Lab, Cambridge CB2 3RA, England
[3] Univ Birmingham, IRC Mat Proc, Birmingham, W Midlands, England
来源
基金
英国工程与自然科学研究理事会;
关键词
paste; extrusion; control; signal processing; quality de-noising;
D O I
10.1205/026387604774196055
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
On-line monitoring of fluctuations in pressure measurements recorded near the die offer significant potential for tracking paste quality in continuous paste extrusion systems. Several signal processing techniques, developed previously for ram extrusion applications, have been applied to a continuous, twin-screw paste extruder processing a clay-based detergent paste. These techniques include the removal of corrupting equipment noise; outlier analysis to detect pockets of entrapped air and large agglomerates in the paste; and quantification of the signal noise, either by fractal analysis or standard error analysis. The signal noise is related to the overall homogeneity of the paste, which can be influenced by factors including dry powder mixing, particle size distribution and paste hold-up within the barrel. The signal processing results are compared with physical measures of extrudate quality, and show a good correlation. Fractal analysis proved a less suitable quantitative tool than the other approaches for this application. The methods are compared with traditional statistical process control techniques and future application is discussed.
引用
收藏
页码:770 / 783
页数:14
相关论文
共 50 条
  • [31] A computational framework for modeling complex sensor network data using graph signal processing and graph neural networks in structural health monitoring
    Bloemheuvel, Stefan
    van den Hoogen, Jurgen
    Atzmueller, Martin
    APPLIED NETWORK SCIENCE, 2021, 6 (01)
  • [32] Computing continuous load rating factors for bridges using structural health monitoring data
    Al-Khateeb, Hadi T.
    Shenton, Harry W.
    Chajes, Michael J.
    JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING, 2018, 8 (05) : 721 - 735
  • [33] Computing continuous load rating factors for bridges using structural health monitoring data
    Hadi T. Al-Khateeb
    Harry W. Shenton
    Michael J. Chajes
    Journal of Civil Structural Health Monitoring, 2018, 8 : 721 - 735
  • [34] Signal processing for fault monitoring using acoustic emissions
    Venkatesan, GT
    Zhang, DL
    Kaveh, M
    Tewfik, AH
    Buckley, KM
    AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 1999, 53 (06) : 333 - 338
  • [35] Relationship of blood pressure with the electrical signal of the heart using signal processing
    Monroy Estrada, Gendy
    Enrique Mendoza, Luis
    Molina, Valentin
    TECCIENCIA, 2014, 9 (17) : 9 - 14
  • [36] Data and signal processing using photochromic molecules
    Gust, Devens
    Andreasson, Joakim
    Pischel, Uwe
    Moore, Thomas A.
    Moore, Ana L.
    CHEMICAL COMMUNICATIONS, 2012, 48 (14) : 1947 - 1957
  • [37] Distributed Cyberinfrastructure Tools for Automated Data Processing of Structural Monitoring Data
    Zhang, Yilan
    Kurata, Masahiro
    Lynch, Jerome P.
    van der Linden, Gwendolyn
    Sadarat, Hassan
    Prakash, Atul
    NONDESTRUCTIVE CHARACTERIZATION FOR COMPOSITE MATERIALS, AEROSPACE ENGINEERING, CIVIL INFRASTRUCTURE, AND HOMELAND SECURITY 2012, 2012, 8347
  • [38] Signal Processing Techniques for IoT-based Structural Health Monitoring
    Mahmud, Md Anam
    Abdelgawad, Ahmed
    Yelamarthi, Kumar
    Ismail, Yasser A.
    2017 29TH INTERNATIONAL CONFERENCE ON MICROELECTRONICS (ICM), 2017, : 137 - 141
  • [39] Toward Data-Driven Structural Health Monitoring: Application of Machine Learning and Signal Processing to Damage Detection
    Ying, Yujie
    Garrett, James H., Jr.
    Oppenheim, Irving J.
    Soibelman, Lucio
    Harley, Joel B.
    Shi, Jun
    Jin, Yuanwei
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2013, 27 (06) : 667 - 680
  • [40] Fast and robust strain signal processing for aircraft structural health monitoring
    Cong Wang
    Xin Tan
    Xiaobin Ren
    Xuelong Li
    Journal of Automation and Intelligence, 2024, 3 (03) : 160 - 168