Automated fault detection and diagnosis methods for supermarket equipment (RP-1615)

References

• Arias, J., and P. Lundqvist. 2006. Heat recovery and floating condensing in supermarkets. Energy and Buildings 38(2):73–81.
   Web of Science ®Google Scholar
• ASHRAE. 2015. Advanced energy design guide for grocery stores—Achieving 50% energy savings toward a net zero energy building. Atlanta: ASHRAE.
   Google Scholar
• Assawamartbunlue, K., and M.J. Brandemuehl. 2006. Refrigerant leakage detection and diagnosis for a distributed refrigeration system. HVAC&R Research 12(3):389–405.
   Web of Science ®Google Scholar
• Bahman, A., L. Rosario, and M.M. Rahman. 2012. Analysis of energy savings in a supermarket refrigeration/HVAC system. Applied Energy 98:11–21.
   Web of Science ®Google Scholar
• Brambley, M.R., D. Hansen, P. Haves, D.R. Holmberg, S.C. McDonald, K.W. Roth, and P. Torcellini. 2005. Advanced sensors and controls for building applications: Market assessment and potential R&D pathways. Report PNNL-15149. Pacific Northwest National Laboratory, Washington, DC, USA.
   Google Scholar
• Breuker, M.S., and J.E. Braun. 1998. Common faults and their impacts for rooftop air conditioners. HVAC&R Research 4(3):303–18.
   Web of Science ®Google Scholar
• CBECS. 2006. Table C3A. Consumption and Gross Energy Intensity for Sum of Major Fuels for All Buildings. Forms EIA-871A, C, and E of the 2003 Commercial. Washington, DC: Energy Information Administration, Office of Energy Markets and End Use.
   Google Scholar
• Chen, B., and J.E. Braun. 2001. Simple rule-based methods for fault detection and diagnostics applied to packaged air conditioners. ASHRAE Transactions 107:847–57.
   Google Scholar
• Cole, P. 2013. Balancing latent heat load between display cases and store comfort cooling. Report ASHRAE 1467-RP. ASHRAE.
   Google Scholar
• Datta, D., S. A. Tassou, and D. Marriott. 1997. Application of neural networks for the prediction of the energy consumption in a supermarket. Proceedings of the International Conference CLIMA 2000, 29 August to 2 September, 1997, Brussels, Belgium, 98–107.
   Google Scholar
• DOE. 2012. 2011 Building Energy Data Book. Washington, DC: United States Department of Energy.
   Google Scholar
• Dong, B., M. Gorbounov, S. Yuan, T. Wu, A. Srivastav, T. Bailey, and Z. O'Neill. 2013. Integrated energy performance modeling for a retail store building. Building Simulation—Tsinghua University Press 6(3):283–95.
   Web of Science ®Google Scholar
• EnergyStar. 2008. Energy Star building manual-Facility Type: Supermarkets and Grocery Stores. Washington, DC: United States Environmental Protection Agency.
   Google Scholar
• Fisera, R., and M. Hrncar. 2012. System and method for performance monitoring of commercial refrigeration. U.S. Patent Application 12/976,088.
   Google Scholar
• Fisera, R., and P. Stluka. 2012. Performance monitoring of the refrigeration system with minimum set of sensors. World Academy of Science, Engineering and Technology 6(7):396–401.
   Google Scholar
• FMI. 2013. Grocery Store Chains Net Profit—Percent of Sales. Arlington, VA: Food Marketing Institute.
   Google Scholar
• Ge, Y.T., and S.A. Tassou. 2011. Performance evaluation and optimal design of supermarket refrigeration systems with supermarket model “SuperSim.” Part II: Model applications. International Journal of Refrigeration 34(2):540–9.
   Web of Science ®Google Scholar
• Hamlett, J., A. Alexander, A. Bailey, and G. Shaw. 2008. Regulating UK supermarkets: An oral-history perspective. History & Policy. http://www.historyandpolicy.org/policy-papers/papers/regulating-uk-supermarkets-an-oral-history-perspective
   Google Scholar
• Isermann, R. 1984. Process fault detection based on modeling and estimation methods—A survey. Automatica 20(4):387–404.
   Web of Science ®Google Scholar
• Isermann, R. 2011. Fault-diagnosis applications: Model-based condition monitoring: Actuators, drives, machinery, plants, sensors, and fault-tolerant systems. London: Springer.
   Google Scholar
• Katipamula, S., and M.R. Brambley. 2005. Review article: Methods for fault detection, diagnostics, and prognostics for building systems—A review. HVAC&R Research 11:3–25.
   Web of Science ®Google Scholar
• Keres, S.L., A.D. Litch, and A.R. Gomes. 2013. Fault detection and diagnosis for refrigerator from compressor sensor. U.S. Patent Application No. 13/531, 707.
   Google Scholar
• Kim, M., and M.S. Kim. 2005. Performance investigation of a variable speed vapor compression system for fault detection and diagnosis. International Journal of Refrigeration 28(4):481–8.
   Web of Science ®Google Scholar
• Larsen, L.F., R. Izadi-Zamanabadi, and R. Wisniewski. 2007. Supermarket refrigeration system-benchmark for hybrid system control. Proceedings of the European Control Conference, July 2-5, 2007, Kos, Greece, pp. 113–20.
   Google Scholar
• Li, H., and J. Braun. 2009. Development, evaluation, and demonstration of a virtual refrigerant charge sensor. HVAC&R Research 15(1):117–36.
   Web of Science ®Google Scholar
• Mavromatidis, G., S. Acha, and N. Shah. 2013. Diagnostic tools of energy performance for supermarkets using artificial neural network algorithms. Energy and Buildings 62:304–14.
   Web of Science ®Google Scholar
• O'Neill, Z., M. Shashanka, P. Haves, and T. Bailey. 2014. Model-based real-time whole building energy performance monitoring and diagnostics. Journal of Building Performance Simulation 7(2):83–99.
   Web of Science ®Google Scholar
• Porter, M.R., J.J. Rozsnaki, and O. Ahmed. 2008. Refrigeration system fault detection and diagnosis using distributed microsystems. U.S. Patent Application No. 11/786,033.
   Google Scholar
• Reindl, D.T. 2013. Sequencing and control of compressors. ASHRAE Journal 55(11):14–29.
   Web of Science ®Google Scholar
• Rossi, T.M., D. Rossi, J.D. Douglas, and T.P. Stockman. 2006. Apparatus and method for detecting faults and providing diagnostics in vapor compression cycle equipment. U.S. Patent No. 6,658,373.
   Google Scholar
• Srinivasan, S., A. Vasan, V. Sarangan, and A. Sivasubramaniam. 2015. Bugs in the freezer: Detecting faults in supermarket refrigeration systems using energy signals. Proceedings of the 2015 ACM Sixth International Conference on Future Energy Systems, July 14-17, Bangalore, India, pp. 101–10.
   Google Scholar
• Taylor, D., and D. Corne. 2002. Refrigerant leak prediction in supermarkets using evolved neural networks. Proceedings of the 4th Asia Pacific Conference on Simulated Evolution and Learning (SEAL), November 18-22, 2002, Orchid Country Club, Singapore.
   Google Scholar
• Taylor, D.W., D.W. Corne, D.L. Taylor, and J. Harkness. 2002. Predicting alarms in supermarket refrigeration systems using evolved neural networks and evolved rulesets. Congress on Evolutionary Computation, May 12-17, 2002, Honolulu, HI, 1988–1993.
   Google Scholar
• Thybo, C., and R. Izadi-Zamanabadi. 2004. Development of fault detection and diagnosis schemes for industrial refrigeration systems-Lessons learned. Control Applications, 2004. Proceedings of the 2004 IEEE International Conference, September 2-4, Taipei, Taiwan, 2:1248–53.
   Google Scholar
• Walker, D.H., and C. Awarded. 2001. Development and demonstration of an advanced supermarket refrigeration/HVAC system. Report ORL-970163, Oak Ridge, TN: Oak Ridge National Laboratory.
   Google Scholar
• Wichman, A., and J. Braun. 2009. Fault detection and diagnostics for commercial coolers and freezers. HVAC&R Research 15(1):77–99.
   Web of Science ®Google Scholar
• Wirz, D. 2009. Commercial Refrigeration: For Air Conditioning Technicians. Clifton Park, NY: Delmar, Cengage Learning.
   Google Scholar
• Yang, Z., K. Rasmussen, A. Kieu, and R. Izadi-Zamanabadi. 2011b. Fault detection and isolation for a supermarket refrigeration system—Part two: Unknown-input-observer method and its extension. IFAC Proceedings Volumes 44(1):4238–43.
   Google Scholar
• Yang, Z., K.B. Rasmussen, A.T. Kieu, and R. Izadi-Zamanabadi. 2011a. Fault detection and isolation for a supermarket refrigeration system-part one: Kalman-filter-based methods. IFAC Proceedings Volumes 44(1):13233–8.
   Google Scholar
• Yuill, D.P., and J.E. Braun. 2013. Evaluating the performance of fault detection and diagnostics protocols applied to air-cooled unitary air-conditioning equipment. HVAC&R Research 19(7):882–91.
   Web of Science ®Google Scholar
• Yuill, D.P., and J.E. Braun. 2016. Effect of the distribution of faults and operating conditions on AFDD performance evaluations. Applied Thermal Engineering 106:1329–36.
   Web of Science ®Google Scholar
• Yuill, D.P., H. Cheung, and J.E. Braun. 2014. Validation of a fault-modeling equipped vapor compression system model using a fault detection and diagnostics evaluation tool. International Refrigeration and Air Conditioning Conference, July 14-17, 2014, West Lafayette, IN, 15:1–10.
   Google Scholar