A review of fault detection and diagnosis methods for residential air conditioning systems

Abstract The fault detection and diagnosis (FDD) for air conditioning systems has been an active area of research for over two decades. However, the majority of methods have been developed for commercial buildings. While much of this work applies to the residential market, this market has unique challenges and opportunities that should be considered separate from the commercial heating, ventilation, and air conditioning (HVAC) and industrial refrigeration systems. This paper reviews and evaluates state-of-the-art methods for performing FDD for air conditioning systems. In the field of applying these methods to the residential market, the opportunities for development include: (a) Considering the level of fault diagnosis that is most cost-effective in the residential market. (b) Simplifying the set of required sensors for FDD. This paper also reviews the emerging field of fault detection of residential air conditioning systems by using cloud-based thermostat data. Publishers have only recently started releasing large-scale analyses of thermostat data, but experts predict considerable growth in this field.

[1]  Woohyun Kim,et al.  A review of fault detection and diagnostics methods for building systems , 2018 .

[2]  James E. Braun,et al.  Decoupling features and virtual sensors for diagnosis of faults in vapor compression air conditioners , 2007 .

[3]  P. Domanski,et al.  Heating Mode Performance Measurements For A Residential Heat Pump With Single-Faults Imposed , 2009 .

[4]  Biswajit Basu,et al.  Residential HVAC fault detection using a system identification approach , 2017 .

[5]  Michel C. A. Klein,et al.  Methods for a Smart Thermostat to Estimate the Characteristics of a House Based on Sensor Data , 2016 .

[6]  Michael R. Brambley,et al.  A Novel, Low-Cost, Reduced-Sensor Approach for Providing Smart Renote Monitoring and Diagnostics for Packaged Air Conditioners and Heat Pumps , 2009 .

[7]  K.R. Pattipati,et al.  Fault diagnosis in HVAC chillers , 2005, IEEE Instrumentation & Measurement Magazine.

[8]  Jonathan A. Wright,et al.  Demonstration of Fault Detection and Diagnosis Methods for Air-Handling Units , 2002 .

[9]  Piotr A. Domanski,et al.  Effect of heat pump commissioning faults on energy use in a slab-on-grade residential house , 2015 .

[10]  Piotr A. Domanski,et al.  Sensitivity Analysis of Installation Faults on Heat Pump Performance , 2014 .

[11]  Piotr A. Domanski,et al.  Development of the reference model for a residential heat pump system for cooling mode fault detection and diagnosis , 2010 .

[12]  Min-Soo Kim,et al.  Performance investigation of a variable speed vapor compression system for fault detection and diagnosis , 2005 .

[13]  Steven B. Leeb,et al.  Non-intrusive electrical load monitoring in commercial buildings based on steady-state and transient load-detection algorithms , 1996 .

[14]  James E. Braun,et al.  A figure of merit for overall performance and value of AFDD tools , 2017 .

[15]  Hans P. Geering,et al.  Fault diagnosis for heat pumps with parameter identification and clustering , 2006 .

[16]  Piotr A. Domanski,et al.  Design of a steady-state detector for fault detection and diagnosis of a residential air conditioner , 2008 .

[17]  Krishna R. Pattipati,et al.  Data-Driven Modeling, Fault Diagnosis and Optimal Sensor Selection for HVAC Chillers , 2007, IEEE Transactions on Automation Science and Engineering.

[18]  Youming Chen,et al.  Fault-tolerant control and data recovery in HVAC monitoring system , 2005 .

[19]  Marianne F Touchie,et al.  Residential HVAC runtime from smart thermostats: characterization, comparison, and impacts , 2018, Indoor air.

[20]  James E. Braun,et al.  Common faults and their impacts for rooftop air conditioners , 1998 .

[21]  Srinivas Katipamula,et al.  Review Article: Methods for Fault Detection, Diagnostics, and Prognostics for Building Systems—A Review, Part I , 2005 .

[22]  Piotr A. Domanski,et al.  Residential Heat Pump Heating Performance with Single Faults Imposed , 2011 .

[23]  Krishna R. Pattipati,et al.  Fault detection, diagnosis, and data-driven modeling in HVAC chillers , 2005, SPIE Defense + Commercial Sensing.

[24]  Fu Xiao,et al.  A diagnostic tool for online sensor health monitoring in air-conditioning systems , 2006 .

[25]  Srinivas Katipamula,et al.  Automated Proactive Techniques for Commissioning Air-Handling Units , 2003 .

[26]  Yonghua Zhu,et al.  Fault diagnosis for sensors in air handling unit based on neural network pre-processed by wavelet and fractal , 2012 .

[27]  R. Radhakrishnan,et al.  A Comparison between Polynomial and Locally Weighted Regression for Fault Detection and Diagnosis of HVAC Equipment , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[28]  James E. Braun,et al.  Evaluating the Performance of a Fault Detection and Diagnostic System for Vapor Compression Equipment , 1998 .

[29]  J. Klein Woud,et al.  On-line failure diagnosis for compression refrigeration plants , 1995 .

[30]  Zhimin Du,et al.  Fault detection and diagnosis based on improved PCA with JAA method in VAV systems , 2007 .

[31]  Shengwei Wang,et al.  Sensor fault detection and validation of VAV terminals in air conditioning systems , 2005 .

[32]  Zhiwei Lian,et al.  Data mining based sensor fault diagnosis and validation for building air conditioning system , 2006 .

[33]  Woohyun Kim,et al.  Evaluation of the impacts of refrigerant charge on air conditioner and heat pump performance , 2010 .

[34]  Raghunathan Rengaswamy,et al.  A review of process fault detection and diagnosis: Part II: Qualitative models and search strategies , 2003, Comput. Chem. Eng..

[35]  Jin Wen,et al.  A model-based fault detection and diagnostic methodology based on PCA method and wavelet transform , 2014 .

[36]  Raghunathan Rengaswamy,et al.  A review of process fault detection and diagnosis: Part III: Process history based methods , 2003, Comput. Chem. Eng..

[37]  Steven B. Leeb,et al.  Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements , 2006 .

[38]  Woohyun Kim,et al.  Rooftop unit embedded diagnostics: Automated fault detection and diagnostics (AFDD) development, field testing and validation , 2015 .

[39]  Haorong Li,et al.  A virtual supply airflow rate meter for rooftop air-conditioning units , 2011 .

[40]  Fu Xiao,et al.  AHU sensor fault diagnosis using principal component analysis method , 2004 .

[41]  Andrew G. Alleyne,et al.  Dynamic Modeling, Control, and Fault Detection in Vapor Compression Systems , 2006 .

[42]  Ian Beausoleil-Morrison,et al.  Development and implementation of a thermostat learning algorithm , 2018 .

[43]  Kamin Whitehouse,et al.  The smart thermostat: using occupancy sensors to save energy in homes , 2010, SenSys '10.

[44]  James E. Braun,et al.  Development, Evaluation, and Demonstration of a Virtual Refrigerant Charge Sensor , 2009 .

[45]  Scott Sanner,et al.  A longitudinal study of thermostat behaviors based on climate, seasonal, and energy price considerations using connected thermostat data , 2018, Building and Environment.

[46]  Bryan P. Rasmussen,et al.  Opportunities for consumer-driven load shifting in commercial and industrial buildings , 2018, Sustainable Energy, Grids and Networks.

[47]  G.W. Hart,et al.  Residential energy monitoring and computerized surveillance via utility power flows , 1989, IEEE Technology and Society Magazine.

[48]  P. Gruber,et al.  Qualitative model-based fault detection in air-handling units , 1995 .

[49]  Piotr A. Domanski,et al.  Performance of a Residential Heat Pump Operating in the Cooling Mode With Single Faults Imposed | NIST , 2006 .

[50]  Raghunathan Rengaswamy,et al.  A review of process fault detection and diagnosis: Part I: Quantitative model-based methods , 2003, Comput. Chem. Eng..

[51]  Xinhua Xu,et al.  Enhanced chiller sensor fault detection, diagnosis and estimation using wavelet analysis and principal component analysis methods , 2008 .

[52]  James E. Braun Automated Fault Detection and Diagnostics for Vapor Compression Cooling Equipment , 2003 .

[53]  Srinivas Katipamula,et al.  Automated Proactive Fault Isolation: A Key to Automated Commissioning , 2007 .

[54]  Todd M. Rossi,et al.  A Statistical, Rule-Based Fault Detection and Diagnostic Method for Vapor Compression Air Conditioners , 1997 .

[55]  G. W. Hart,et al.  Nonintrusive appliance load monitoring , 1992, Proc. IEEE.

[56]  James E. Braun,et al.  A Methodology for Diagnosing Multiple Simultaneous Faults in Vapor-Compression Air Conditioners , 2007 .

[57]  Haorong Li A decoupling-based unified fault detection and diagnosis approach for packaged air conditioners , 2004 .