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Haorong Li, Ph.D.

Affiliations: 
2004 Purdue University, West Lafayette, IN, United States 
Area:
Mechanical Engineering
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"Haorong Li"
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James E. Braun grad student 2004 Purdue
 (A decoupling-based unified fault detection and diagnosis approach for packaged air conditioners.)

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Publications

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Li G, Chen H, Hu Y, et al. (2018) An improved decision tree-based fault diagnosis method for practical variable refrigerant flow system using virtual sensor-based fault indicators Applied Thermal Engineering. 129: 1292-1303
Guo Y, Li G, Chen H, et al. (2017) Development of a virtual variable-speed compressor power sensor for variable refrigerant flow air conditioning system International Journal of Refrigeration-Revue Internationale Du Froid. 74: 73-85
Guo Y, Li G, Chen H, et al. (2017) An enhanced PCA method with Savitzky-Golay method for VRF system sensor fault detection and diagnosis Energy and Buildings. 142: 167-178
Guo Y, Li G, Chen H, et al. (2017) Modularized PCA method combined with expert-based multivariate decoupling for FDD in VRF systems including indoor unit faults Applied Thermal Engineering. 115: 744-755
Woradechjumroen D, Li H, Promwattanapakee T. (2016) Fault Detection and Diagnosis Process for Oversizing Design on Multiple Packaged Air-conditioning Units Procedia Computer Science. 86: 341-344
Woradechjumroen D, Li H, Deesiri A. (2016) Development of Coordination Control for Multiple Rooftop Units Procedia Computer Science. 86: 176-179
Hu Y, Li G, Chen H, et al. (2016) Sensitivity analysis for PCA-based chiller sensor fault detection International Journal of Refrigeration. 63: 133-143
Li G, Hu Y, Chen H, et al. (2016) A sensor fault detection and diagnosis strategy for screw chiller system using support vector data description-based D-statistic and DV-contribution plots Energy and Buildings. 133: 230-245
Li G, Hu Y, Chen H, et al. (2016) An improved fault detection method for incipient centrifugal chiller faults using the PCA-R-SVDD algorithm Energy and Buildings. 116: 104-113
Hu Y, Chen H, Li G, et al. (2016) A statistical training data cleaning strategy for the PCA-based chiller sensor fault detection, diagnosis and data reconstruction method Energy and Buildings. 112: 270-278
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