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

Figures & data

Fig. 1. A typical supermarket equipment schematic and locations of common faults.

Fig. 2. Interaction among external entities and internal supermarket systems.

Fig. 3. Architecture of AFDD methods used in refrigeration and building systems.

Fig. 4. Data-driven AFDD method—First level of the detection on the left branch, and second level of the detection on the right branch.

Fig. 5. SARIMA-based data-driven AFDD method.

Fig. 6. AFDD method for performance monitoring of refrigeration system.

Fig. 7. Physical model-based AFDD method for cabinet cases.

Table 1. Fault characteristics of two AFDD protocols for unitary air-conditioning systems with TEV and EEV.

Faults/performance parameters	Te (evaporating temperature)		Tra – Te (return air and evaporating temperature difference)		Tc (condensing temperature)		Tc – Tamb (condenser split)		Tsc (sub-cooling temperature)
Source	1	2	1	2	1	2	1	2	1	2
Compressor fault	↑	↑	—	↓	↓	↓	—	—	↓	↓
Refrigerant leakage	↓ (>15%)	= (↓ at leakage >=30%)	—	—	↓	= (↓ at leakage >=20%)	—	—	(<15%)	↓
Condenser fault	↓	=	—	—	↑	↑	—	↑	—	↑
Evaporator fault	↓	↓	—	↑	↓	↓	—	—	↑	=
Non-condensable gas	—	↑ (At higher fault levels)	—	—	—	↑	—	—	—	↑

Source 1: (Kim and Kim 2005) Water to water heat pump with EEV.

Source 2: (Chen and Braun 2001) Rooftop air-conditioning unit with TXV.

Fig. 8. Store 4 System A. Outdoor air temperature, condensing temperature, and condenser split over a 1-year period.

Table 2. Refrigeration system properties.

Store	System ID	System type	Primary refrigerant	Secondary refrigerant
1	A, B, C	Centralized DX rack	R404A	—
	D	Distributed	R404A	—
2	A	Centralized DX rack	R404A	—
3	A, B, C	Indirect CO2 system	R404A	CO2
4	A, B, C, D, E, F, G, H, I, J	Distributed	R404A	—

Fig. 9. Ninety-five percent confidence intervals for condenser split for 18 different systems in four stores.

Fig. 10. Store 4 System A. Condensing temperature, drop-leg temperature, and sub-cooling for a 1-year period.

Fig. 11. Store 1 and 4 sub-cooling 95% confidence intervals.

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.

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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.

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