Fault detection and diagnosis based on improved PCA with JAA method in VAV systems

被引：85
|
作者：
Du, Zhimin [1 ]
Jin, Xinqiao [1 ]
Wu, Lizhou [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Mech Engn, Shanghai 200030, Peoples R China
来源：
BUILDING AND ENVIRONMENT | 2007年 / 42卷 / 09期
关键词：
VAV systems; fault characteristic; principal component analysis; joint angle analysis; sensor; fixed and drifting biases;
D O I：
10.1016/j.buildenv.2006.08.011
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
In this paper, improved principal component analysis (PCA) with joint angle analysis (JAA) is presented to detect and diagnose both fixed and drifting biases of sensors in variable air volume (VAV) systems. Fault characteristic concerned in PID controller in the VAV systems is analyzed and discussed. The squared prediction error (SPE) plot based on PCA is used to detect the sensor fixed and drifting biases. Then the JAA plot instead of conventional contribution plot is used to diagnose the faults. And they are tested and evaluated online in a simulated centralized VAV air-conditioning systems. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码：3221 / 3232
页数：12
相关论文
共 50 条
  • [41] A Fault Diagnosis Method for Information Systems Based on Weighted Fault Diagnosis Tree
    Duan, Liming
    Wang, Fenghai
    Guo, Ruifeng
    Gai, Rongli
    2017 IEEE 19TH INTERNATIONAL CONFERENCE ON E-HEALTH NETWORKING, APPLICATIONS AND SERVICES (HEALTHCOM), 2017,
  • [42] Online model-based fault detection and diagnosis strategy for VAV air handling units
    Wang, Haitao
    Chen, Youming
    Chan, Cary W. H.
    Qin, Jianying
    Wang, Jinhua
    ENERGY AND BUILDINGS, 2012, 55 : 252 - 263
  • [43] Power transformer fault diagnosis using FCM and improved PCA
    Kari, Tusongjiang
    Gao, Wensheng
    Journal of Engineering, 2017, 2017 (14): : 2605 - 2608
  • [44] Bearing fault diagnosis based on PCA and SVM
    Shuang, Lu
    Meng, Li
    2007 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS I-V, CONFERENCE PROCEEDINGS, 2007, : 3503 - +
  • [45] On PCA-based fault diagnosis techniques
    Yin, Shen
    Ding, Steven X.
    Naik, Amol
    Deng, Pengcheng
    Haghani, Adel
    2010 CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL'10), 2010, : 179 - 184
  • [46] A Method for Aileron Actuator Fault Diagnosis Based on PCA and PGC-SVM
    Qin, Wei-Li
    Zhang, Wen-Jin
    Lu, Chen
    SHOCK AND VIBRATION, 2016, 2016
  • [47] Fault Diagnosis Method of PV Array Based on Fast OS-PCA
    Li Y.
    Ding K.
    Chen F.
    Ding H.
    Dianwang Jishu/Power System Technology, 2019, 43 (01): : 308 - 315
  • [48] A Fault Diagnosis Method for Rotating Machinery Based on PCA and Morlet Kernel SVM
    Dong, Shaojiang
    Sun, Dihua
    Tang, Baoping
    Gao, Zhenyuan
    Yu, Wentao
    Xia, Ming
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2014, 2014
  • [49] Roller Bearing Fault Diagnosis Method Based on LMD-CM-PCA
    Fu Y.
    Jia L.
    Qin Y.
    Yang J.
    1600, Nanjing University of Aeronautics an Astronautics (37): : 249 - 255
  • [50] Fault diagnosis based on PCA method with multi-block information extraction
    Gu B.
    Xiong W.
    Huagong Xuebao/CIESC Journal, 2019, 70 (02): : 736 - 749
12345