NDLI: Automatic Feature Selection Using Multiobjective Cluster Optimization for Fault Detection in a Heating Ventilation and Air Conditioning System

Content Provider	IEEE Xplore Digital Library
Author	Yuwono, M. Su, S.W. Ying Guo Jiaming Li West, S. Wall, J.
Copyright Year	2013
Description	Author affiliation: Fac. of Eng. & Inf. Technol., Univ. of Technol., Sydney, NSW, Australia (Yuwono, M.; Su, S.W.) \|\| Commonwealth Sci. & Ind. Res. Organ. (CSIRO), Newcastle, NSW, Australia (West, S.; Wall, J.) \|\| Commonwealth Sci. & Ind. Res. Organ. (CSIRO), Marsfield, NSW, Australia (Ying Guo; Jiaming Li)
Abstract	The performance of Automatic Fault Detection and Diagnostics (AFDD) algorithms to identify faults in complex building Heating Ventilation and Air-Conditioning (HVAC) systems depend on the appropriateness of features. This paper proposes a knowledge-discovery approach for discovering characteristic features using Multi-Objective Clustering Rapid Centroid Estimation (MOC-RCE). The proposed method has been tested on experimental fault data from the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) research project 1312-RP Winter 2008 dataset. An experiment involving 100 clustering trials shows that using the proposed method, on average 15 characteristic features have been selected from the original 320 features. Sensitivity, specificity, accuracy, precision, and F-score values of greater than 95% are achieved with the provided features.
Starting Page	171
Ending Page	176
File Size	672445
Page Count	6
File Format	PDF
e-ISBN	9781479932511
DOI	10.1109/AIMS.2013.34
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-03
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Coils Temperature sensors Heating ventilation and air-conditioning Automatic Fault Detection and Diagnostics Feature selection Buildings Water heating Feature extraction Multiobjective clustering Sensor systems
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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