Fault Detection and Diagnostics for Rooftop Air Conditioners

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45 is extremely low. However, it is possible for the refrigerant at this point to have a small degree of subcooling if there is a severe liquid line restriction or a refrigerant overcharge fault. Even so, a small subcooling would not have a big impact. On the contrary, 1-2 F subcooling would compensate for the error resulting from neglecting the pressure drop in the liquid-line and condenser subcooling section. 4 F subcooling may result in around a - 3 psi error. Another more approximate approach to estimating P 3 is to assume constant pressure drop across condenser, which may result in a ± 10 psi error. An estimate of P up can be obtained by modeling the expansion device. There are rather mature techniques available for modeling fixed orifices including short tube and capillary tube (see Appendix 1). For a TXV or EXV system, Appendix 1 develops a practical and useful modeling approach to estimate the upstream pressure using factory performance map data. The models for estimating pressures work as a virtual sensor for pressure drop. The decoupling scheme is shown in Figure 1-11. Liquid-Line Restriction Liquid Line Virtual Sensor P up + ∆ P ll , meas T T φ aic aie aie Rooftop System Virtual Sensor _ P ( T 3 cond ) + _ 2 ∆ Pll Other Faults Constant P ≈ 0 ∆ ll Figure 1-11 Liquid-Line Restriction Decoupling Scheme 1.2.3.4 Evaporator Fouling Fault Similar to condenser fouling, evaporator or evaporator filter fouling also develops on the air side and the dominant impact is a reduction of air flow rate. Therefore, the 45
46 evaporator air flow rate reduction can be chosen as an independent feature for evaporator fouling. Applying the first thermodynamic law to the evaporator, where, m& ea ( haie( Taie, φ aie) − haoe ( Taoe, φaoe )) = m& ref ( hsuc ( Psuc , Tsuc ) − hll ( Pll , Tll )) (1-21) mref ( hsuc( Psuc, Tsuc) − hll( Pll, Tll)) m& ea = & (1-22) ( h ( T , φ ) − h ( T , φ )) aie aie aie aoe aoe aoe m& ea is evaporator air mass flow rate, h aoe is the evaporator outlet air enthalpy, φ aoe is the relative humidity of evaporator outlet air, T aoe is evaporator outlet air temperature, h aie is evaporator air inlet enthalpy, T aie is evaporator inlet air temperature, φ aie is the relative humidity of evaporator inlet air, h suc is suction line refrigerant enthalpy, P suc is suction line pressure, and T suc is suction line temperature. All the parameters on the right side of equation (1-22) are measured or estimated, so equation (1-22) is a virtual sensor or observer for measuring illustrates the above decoupling scheme. & . Figure 1-12 m ea , meas Evaporator Fouling Fault T T φ aic aie aie Rooftop System Other Faults Evaporator h ( P h ll m& suc ref Speed Setting dis ( P , T , T ) suc aoe Virtual Sensor ll , T suc , T aie ) ,φ Blower aie & m ea , meas + _ ∆ m& ea Figure 1-12 Evaporator Fouling Decoupling Scheme Unlike condenser air mass flow rate, & normally has more than one speed m ea , pred setting, but it is constant for a given setting. So, the block ‘blower’ acts as a normal model, whose input is the setting control signal and output is a constant air mass flow rate 46
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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
Page 185 and 186: Load 20% 40% 60% 80% 100% 3 4 Fault
Page 187 and 188: 3 4 0 0 0 0 0.4173 0 0.0010 0 0.000
Page 189 and 190: .44(' $ () ) ) - $
Page 191 and 192: ∆P Restrictio n Level=100%* ∆P
Page 193 and 194: 2 TABLE OF CONTENTS TABLE OF CONTEN
Page 195 and 196: 4 A1.2.3 Valve Position Expression
Page 197 and 198: 6 Figure 2-10 Decoupling refrigeran
Page 199 and 200: 8 LIST OF TABLES Table 1-1 Fault di
Page 201 and 202: 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: 44 as an independent feature only f
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 and 254: 62 Figure 2-11 Illustration of Demo
Page 255 and 256: 64 bypass the compressor. At this t
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) (
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96 The abrupt change of CA for the
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98 These equations can be combined
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100 H h T sh , max opening T sh , s
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102 A1.2.5 Parameter Estimation Met
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104 T (2 T sh, ratingopening , sh,m
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106 Harms’Result Harms plotted al
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108 Mass flow rate Local linearizat
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110 temperature on the RTD is unifo
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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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