Fault Detection and Diagnostics for Rooftop Air Conditioners

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63 Refrigerant Low-charge Refrigerant Low-charge Condenser Fouling Refrigerant Low-charge Condenser Fouling Liquid-line Restriction 1 31 61 91 211 181 151 121 Refrigerant Low-charge Condenser Fouling Liquid-line Restriction Compressor Leakage Refrigerant Low-charge Fault Free Refrigerant Low-charge Compressor Leakage Refrigerant Low-charge Liquid-line Restriction Compressor Leakage 241 Figure 2-12 Timeline of the fault simulation in minutes. The following steps describe the addition of faults, 1. Evacuated the system, and then charged the system up to eighty per cent of nominal refrigerant charge. The system ran for half an hour to reach steady state and then data were logged. 2. After logging half an hour of low charge data, the condenser fouling fault was added, by covering thirty per cent of condenser area using paper. At this time, there were two simultaneous faults in the system: refrigerant low charge and condenser fouling. 3. Half an hour later, a liquid line restriction fault was introduced by closing the restriction valve until a twenty psi pressure drop was caused. Three faults existed in the system simultaneously: refrigerant low charge, condenser fouling and liquid line restriction. 4. Half an hour later, a compressor leakage fault was introduced by opening the compressor bypass valve to let fifteen per cent of refrigerant mass flow rate 63
64 bypass the compressor. At this time, four faults existed simultaneously in the system: refrigerant low charge, condenser fouling, liquid line restriction, and compressor leakage. The following steps describe the removal of faults, 5. After the system ran for half an hour under four faults, the paper covering the condenser was removed. There existed three simultaneous faults in the system: refrigerant low charge, liquid line restriction, and compressor leakage, which is a different combination than step three. 6. Half an hour later, the liquid line restriction fault was removed by fully opening the liquid line restriction valve. At this time, refrigerant low charge and compressor leakage existed in the system, which is a different combination than step two. 7. Half an hour later, the compressor bypass valve was closed to remove compressor leakage fault. There was only refrigerant low charge fault in the system. 8. Finally, half an hour later, the system was charged up to a nominal refrigerant level. The system was supposed to run normally. 2.2.2 Fault Detection and Diagnosis Window This window plots the normalized fault indicator for four individual faults using color bars: refrigerant low charge (Low-Charge), condenser fouling (Cond-Foul), liquid line restriction (LL-Restr), and compressor leakage (Comp-Leak). The normalized fault indicator is the ratio of the current feature value to the predefined value, which is defined at an individual fault level causing 20% cooling capacity degradation. Normalized _ Fault _ Indicator = current _ feature − value predefined _ feature _ value 64
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CALIFORNIA ENERGY COMMISSION Final
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Acknowledgements Jim Braun and Haor
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Abstract Project 2.1, Fault Detecti
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TABLE OF CONTENTS LIST OF TABLES LI
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LIST OF FIGURES Page 1 - Field Test
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The report “Description of Labora
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mounted heat pumps for heating and
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The retail stores are in Southern C
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Figure 1 - Field Test Sites Data Co
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Gibson School (Cont’d) Woodland S
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Table 1 - Data List for Modular Sch
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BUILDING TYPE: Modular School Rooms
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HEATING / AIR CONDITIONING EQUIPMEN
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Sacramento Area McDonalds PlayPlace
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Bradshaw Road (Sacramento Area) McD
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TEST INSTRUMENTATION: Tables 2 and
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Table 2 - Data List for Inland Rest
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Castro Valley (San Francisco Bay Ar
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Castro Valley McDonalds PlayPlace P
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more or less custom design, publish
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BUILDING TYPE: Retail Store ADDRESS
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TEST INSTRUMENTATION: Similar test
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• Temperature and humidity levels
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November 2001 - December/January 20
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Table of Contents 1. Introduction..
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1. Introduction All the thermodynam
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Table 1.1 Comparisons of Three Mode
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solution procedure involves the non
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independent of the moisture content
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function, f ( X , y) , if it can be
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Figure 2.1 Neural-Network Implement
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prototype was developed by using th
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3. Comparison of black-box modeling
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which is more accurate than the exp
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Similar to GRNN, RBF has very good
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Table 3.2 RMS error (Polynomial,GRN
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Table 3.4 Contrast of Black-box mod
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Polynomial plus GRNN Training Desir
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interpolation(poly+GRNN) extrapolat
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used to build the steady-state mode
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α , ρ, τ I t t s h o A t a Figur
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Temperature (F) 82 79 76 73 Condens
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0.050 0.045 Pressure = 101.3 [kPa]
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T T − T − T W = W −W −W m =
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Figure 4.8 Output of three steady-s
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will be calculated to represent the
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180 175 RMS error = 0.3984 (F) Pred
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180 175 RMS error =1.1472 (F) Predi
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51 50 RMS error=0.3860 (F) Predicte
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4.4 California field site results S
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105 100 RMS error =0.5982 (F) Predi
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Since air conditioners always cycle
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6. Conclusions and future work So f
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Lee, W., House, J.M. and Shin, D.R.
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Table of Contents 1 Introduction...
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AHU α β 2 d i EER ∆ ∆ η v T
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$ !! !! )
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Paper statistics in HVAC FDD Number
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011>" - , ?" 8?"
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+ : 6336" ,
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+ :: !!- :: !!
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6 24 122 7) 6 3++, ) . !! /011
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)
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336 F / s $ S
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N $ V v1
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Figure 3-4 2-dimensional residual d
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10 5 Normal and current operation p
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7 N Ω f N N Ω = Ω X ,
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0 + α 6 d χ ( )
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Normal operation region Residual-2
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Table 3-2 Refrigerant Leak at 20% l
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ratio dist = P F 1 P F 1 2 1 9.0
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$ , " - (
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)(( 0( 04 ) 6330" /
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Table 4-2 Polynomial plus GRNN mode
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4.2 m r,predict (kg/min) 4 3.8 3.6
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6 1)( ( ( 6 1)( ) , ( )
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- )
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? "J> *"J060 #"J083 *$"J670 #"J08<
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Table 4-17 Detected (normal, fault)
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c=1 c=10 c=20 1 0.8 Distance ratio
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$ /) $ 0111" .. !!
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Chen, Bin and Braun, J.E, 2000. Sim
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Ventilating, Air-Conditioning and R
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1.T amb 2.T ra 3.RH ra Plant Prepro
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F) $
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+: + $ 5
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.44(' * 5 09( ( 0( F N ( M , Σ)
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Load 20% 40% 60% 80% 100% 3 4 Fault
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Load 20% 40% 60% 80% 100% 3 4 Fault
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3 4 0 0 0 0 0.4173 0 0.0010 0 0.000
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.44(' $ () ) ) - $
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∆P Restrictio n Level=100%* ∆P
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2 TABLE OF CONTENTS TABLE OF CONTEN
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4 A1.2.3 Valve Position Expression
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6 Figure 2-10 Decoupling refrigeran
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8 LIST OF TABLES Table 1-1 Fault di
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10 N = Number of generated sample p
Page 203 and 204: 12 with a fixed-orifice as the expa
Page 205 and 206: 14 (residuals) should have a zero m
Page 207 and 208: 16 expected distribution of the res
Page 209 and 210: 18 operation. Another advantage is
Page 211 and 212: 20 1.1.2.1 Original SRB Fault Diagn
Page 213 and 214: 22 Corresponding to the SRB fault d
Page 215 and 216: 24 integration of the probability d
Page 217 and 218: 26 1. Simplifies fault detection fr
Page 219 and 220: 28 Step i Do FDD on fault i . After
Page 221 and 222: 30 ROOFTOP UNIT FAULTS COMPONENT-LE
Page 223 and 224: 32 has two possible causes: refrige
Page 225 and 226: 34 1.2.3 Decoupling of Component Fa
Page 227 and 228: 36 1.2.3.2 Condenser-Related Faults
Page 229 and 230: 38 mixture, χ ref is known as the
Page 231 and 232: 40 Table 1-3 also lists the refrige
Page 233 and 234: 42 Refrigerant Property T cond, pre
Page 235 and 236: 44 as an independent feature only f
Page 237 and 238: 46 evaporator air flow rate reducti
Page 239 and 240: 48 5. 2 Pll ∆ deviates drasticall
Page 241 and 242: 50 System-Level Faults RefUnder Ref
Page 243 and 244: 52 1.2.5 Summary of Decoupling Sche
Page 245 and 246: 54 noise, system disturbances and m
Page 247 and 248: 56 compressor data. When there is a
Page 249 and 250: 58 Figure 2-5 Decoupling evaporator
Page 251 and 252: 60 Total Pressure Drop of Liquid- L
Page 253: 62 Figure 2-11 Illustration of Demo
Page 257 and 258: 66 for T dis because there is no ov
Page 259 and 260: 68 Figure 2-14 Outputs of the FDD d
Page 261 and 262: 70 the system requires more refrige
Page 263 and 264: 72 recommended that: the system req
Page 265 and 266: 74 Figure 2-20 Outputs of the FDD d
Page 267 and 268: 76 Figure 2-21 Histogram bar plot o
Page 273 and 274: 82 2.3.2 Summarized Results for Oth
Page 275 and 276: 84 3 CONCLUSIONS AND RECOMMENDATION
Page 277 and 278: 86 Breuker, M.S. and Braun, J. E.,
Page 279 and 280: 88 Lee, W., House, J.M. and Shin, D
Page 281 and 282: 90 APPENDIX 1 PHYSICAL MODELS OF EX
Page 283 and 284: 92 A1.1.2 Short-Tube Models Many re
Page 285 and 286: 94 m& = CA ρ P up − P ) (A1-5) (
Page 287 and 288: 96 The abrupt change of CA for the
Page 289 and 290: 98 These equations can be combined
Page 291 and 292: 100 H h T sh , max opening T sh , s
Page 293 and 294: 102 A1.2.5 Parameter Estimation Met
Page 295 and 296: 104 T (2 T sh, ratingopening , sh,m
Page 297 and 298: 106 Harms’Result Harms plotted al
Page 299 and 300: 108 Mass flow rate Local linearizat
Page 301 and 302: 110 temperature on the RTD is unifo
Page 303 and 304: 112 in cold water application, it i
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1 ACKNOWLEDGEMENTS The research tha
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3 2.2.3 Todd Harms’ Data ........
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5 LIST OF FIGURES Figure E-1. FDD d
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7 LIST OF TABLES Table E-1 FDD resu
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9 IA = Independence Assumption λ i
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11 EXECUTIVE SUMMARY Packaged air c
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13 current values of the fault indi
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15 Figure E-4 Histogram of the EER
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17 2. Operational cost savings, whi
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19 Table E-5 Conservative Lifetime
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21 constraints. Economic constraint
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23 Paper statistics in HVAC FDD 35
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25 on directional changes to identi
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27 fault levels at different operat
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29 was concluded that the method wa
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31 However, several improvements ar
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33 point sensor placement is genera
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35 2 DATA SOURCES USED FOR EVALUATI
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37 The fives types of faults are re
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39 Occupation Type Climate Location
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41 The SRB FDD method determines wh
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43 The following sections describe
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45 points rather than on a distribu
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47 current operation point P 1, P F
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49 4 A DECOUPLING-BASED FDD TECHNIQ
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51 This approach overcomes the draw
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53 ⎡ ∆T ⎢ ⎢ ∆T 2 ⎢ ∆
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55 improving the compressor model p
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57 Condenser Air Mass Flow Rate (lb
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59 Evaporator Air Mass Flow Rate (l
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61 Liquid-Line Pressure Drop (PSI)
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63 4.2.2 Purdue Field Emulation Sit
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65 1. Evacuated the system, and the
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67 normal _ value − current _ val
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69 Figure 4-16 shows one frame afte
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71 Figure 4-18 shows one frame afte
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73 valve position can be seen from
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Figure 4-22 Outputs of the FDD demo
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77 Figure 4-23 Histogram bar plot o
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83 4.2.3.2 Summarized Results for O
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85 5 ECONOMIC ASSESSMENTS Since the
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87 inspection savings would be $2,0
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89 Q & Cap = W & × EER (5-2) The e
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91 4. electricity costs ( C e ). Ut
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93 Table 5-3 lists estimates of equ
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95 5.4 Smart Service Schedule Savin
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97 7. A 6-ton RTU having a cost of
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99 Location North California South
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101 5. Three case studies were inve
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103 REFERENCES Aaron, D. A., and P.
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105 Davis, Coby. 1993. Comparison o
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107 Rossi, T.M., 1995. Detection, D
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Fault Detection and Diagnostics for Rooftop Air Conditioners

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