Fault diagnosis for heat pumps with parameter identification and clustering

被引：36

作者：

Zogg, D. ^{[1
]}

Shafai, E. ^{[1
]}

Geering, H. P. ^{[1
]}

机构：

[1] ETH, Measurement & Control Lab, Swiss Fed Inst Technol Zurich, CH-8092 Zurich, Switzerland

来源：

CONTROL ENGINEERING PRACTICE | 2006年 / 14卷 / 12期

关键词：

fault detection and diagnosis; model-based techniques; parameter identification; classification; clustering techniques; heat pumps;

D O I：

10.1016/j.conengprac.2005.11.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For reducing the energy consumption of heat pumps, fault detection and diagnosis (FDD) is fundamental. The FDD system presented is based on a gray-box process model, the parameters of which are identified online. The faults are classified from the parameters using clustering methods. Known clustering techniques have been simplified and new "vector clustering" techniques have been developed for classifying gradual faults. The FDD system has been tested in various real applications, for one of which the results are presented in this work. The contribution lies on the application side with a software tool developed for the fully automated training process. (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：1435 / 1444

页数：10

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