PROAD (Process Advisor): A health monitoring framework for centrifugal pumps

被引:11
作者
Dutta, Arnab [1 ,2 ]
Karimi, Iftekhar A. [1 ]
Farooq, Shamsuzzaman [1 ]
机构
[1] Natl Univ Singapore, Dept Chem & Biomol Engn, 4 Engn Dr 4, Singapore 117585, Singapore
[2] Birla Inst Technol & Sci BITS Pilani, Dept Chem Engn, Hyderabad Campus,Jawahar Nagar, Hyderabad 500078, Telangana, India
基金
新加坡国家研究基金会;
关键词
Health monitoring; Centrifugal pumps; Process data analytics; Fault diagnosis; Prescriptive maintenance; Dashboard; FAULT-DIAGNOSIS; VIBRATION; CAVITATION; SVM;
D O I
10.1016/j.compchemeng.2022.107825
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
PROAD is an automated framework developed using multi-pronged approach that integrates process, vibration, and spectral data for performance monitoring, prescriptive maintenance, and fault diagnosis of centrifugal pumps. Data input to PROAD is through robust interactive templates. A clustering algorithm is implemented within PROAD that computes deviation of pump head (as a function of flowrate) w.r.t. vendor-supplied head curve for fresh pump. Head deviations over time are analyzed using regression techniques to predict remaining useful life of pump w.r.t. threshold limits. Data from vibration sensors are analyzed to prescribe spectral checks and data obtained from spectral checks are then examined to diagnose mechanical faults. Based on performance and diagnostic metrics, color-coded health status, report, and plots are displayed for each pump. We have tested PROAD on industrial data and it successfully diagnosed a pump with severe bearing damage. PROAD can be easily implemented in industries for health monitoring of centrifugal pumps.(c) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页数:11
相关论文
共 31 条
[1]  
Al-Hashmi S., 2004, P 7 BIENN C ENG SYST, V3, P185, DOI [10.1115/esda2004-58255, DOI 10.1115/ESDA2004-58255]
[2]  
Alfayez L., 2004, DETECTION INCIPIENT, P407
[3]   Fault diagnosis of a centrifugal pump using MLP-GABP and SVM with CWT [J].
ALTobi, Maamar Ali Saud ;
Bevan, Geraint ;
Wallace, Peter ;
Harrison, David ;
Ramachandran, K. P. .
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2019, 22 (03) :854-861
[4]   Improving accuracy of cavitation severity detection in centrifugal pumps using a hybrid feature selection technique [J].
Azizi, Raziyeh ;
Attaran, Behrooz ;
Hajnayeb, Ali ;
Ghanbarzadeh, Afshin ;
Changizian, Maziar .
MEASUREMENT, 2017, 108 :9-17
[5]  
BLASHFIELD RK, 1991, J CLASSIF, V8, P277
[6]   VIBROACOUSTICAL DIAGNOSTICS OF MACHINERY - AN OUTLINE [J].
CEMPEL, C .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 1988, 2 (02) :135-151
[7]   Noise as an indicator of cavitation in a centrifugal pump [J].
Chudina, M .
ACOUSTICAL PHYSICS, 2003, 49 (04) :463-474
[8]   Cavitation Detection in Centrifugal Pump Based on Interior Flow-Borne Noise Using WPD-PCA-RBF [J].
Dong, Liang ;
Wu, Kan ;
Zhu, Jian-cheng ;
Dai, Cui ;
Zhang, Li-xin ;
Guo, Jin-nan .
SHOCK AND VIBRATION, 2019, 2019
[9]   Design and Implementation of an Online Precise Monitoring and Performance Analysis System for Centrifugal Pumps [J].
Emami, S. A. ;
Emami, M. H. .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 65 (02) :1636-1644
[10]  
globenewswire, WORLDWIDE PUMPS MARK