Fault Detection and Diagnostics for Rooftop Air Conditioners

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HEATING / AIR CONDITIONING EQUIPMENT: Each building (room) has a sidewall-mounted heat pump as described in the table below. Manufacturer Bard Manufacturing Model WH 421-A Nominal Cooling Capacity Number of Stages 1 3½ Tons SEER / HSPF 10.0 / 6.8 Supplemental Heating Capacity Electrical 10 kW nominal electric resistance heater. Single phase, 220 V Supply Fan Rating 1400 cfm @ 0.3” TEST INSTRUMENTATION: Table 1 lists the input data channels used at the modular schoolrooms. The same data list is used at both the Woodland and Oakland school sites. 11
Table 1 – Data List for Modular School Room Field Test Sites Channel # Data Point Power Transducer Channels 1 Unit voltage 2 Compressor 1 voltage 3 Common 4 Unit total current 5 Compressor 1 current 6 - 8 Spare - Not Used Other Analog Input Data 9 Suction line pressure, Stage 1 10 Liquid line pressure, Stage 1 11 - 14 Spare - Not Used 15 Mixed air temperature 16 Return air temperature 17 Supply air temperature, before heater 18 Supply air temperature, after heater 19 Condenser inlet air temperature 20 Condenser outlet air temperature 21 Suction line temperature, Stage 1 22 Discharge line temperature, Stage 1 23 SPARE - Used as additional ambient T 24 SPARE - Used as additional ambient T 25 Evaporation temperature, Stage 1 26 Condensation temperature, Stage 1 27- 32 Spare - Not Used Calculated Data Channels 33-50 NOT USED 51 Honeywell DCV indoor (and outdoor) CO2 conc. 52 Honeywell DCV mixed air temperature 53 Honeywell DCV return air temperature 54 Honeywell DCV return / outdoor humidity 55 Honeywell DCV outdoor air temp & damper position 56 Honeywell DCV minimum damper position 57 superheat, stage 1 58 subcooling, stage 1 59 evaporating temperature, stage 1 60 condensing temperature, stage 1 61 condensing temperature over ambient (CT-AIC), stage 1 62 superheat, stage 2 63 subcooling, stage 2 64 evaporating temperature, stage 2 65 condensing temperature, stage 2 66 condensing temperature over ambient (CT-AIC), stage 2 12
Page 1 and 2: CALIFORNIA ENERGY COMMISSION Final
Page 3 and 4: Acknowledgements Jim Braun and Haor
Page 5 and 6: Abstract Project 2.1, Fault Detecti
Page 7 and 8: TABLE OF CONTENTS LIST OF TABLES LI
Page 9 and 10: LIST OF FIGURES Page 1 - Field Test
Page 11 and 12: The report “Description of Labora
Page 13 and 14: mounted heat pumps for heating and
Page 15 and 16: The retail stores are in Southern C
Page 17 and 18: Figure 1 - Field Test Sites Data Co
Page 19: Gibson School (Cont’d) Woodland S
Page 23 and 24: BUILDING TYPE: Modular School Rooms
Page 25 and 26: HEATING / AIR CONDITIONING EQUIPMEN
Page 27 and 28: Sacramento Area McDonalds PlayPlace
Page 29 and 30: Bradshaw Road (Sacramento Area) McD
Page 31 and 32: TEST INSTRUMENTATION: Tables 2 and
Page 33 and 34: Table 2 - Data List for Inland Rest
Page 39 and 40: Castro Valley (San Francisco Bay Ar
Page 41 and 42: Castro Valley McDonalds PlayPlace P
Page 43 and 44: more or less custom design, publish
Page 45 and 46: BUILDING TYPE: Retail Store ADDRESS
Page 47 and 48: TEST INSTRUMENTATION: Similar test
Page 49 and 50: • Temperature and humidity levels
Page 51 and 52: November 2001 - December/January 20
Page 53 and 54: Table of Contents 1. Introduction..
Page 55 and 56: 1. Introduction All the thermodynam
Page 57 and 58: Table 1.1 Comparisons of Three Mode
Page 59 and 60: solution procedure involves the non
Page 61 and 62: independent of the moisture content
Page 63 and 64: function, f ( X , y) , if it can be
Page 65 and 66: Figure 2.1 Neural-Network Implement
Page 67 and 68: prototype was developed by using th
Page 69 and 70: 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
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12 with a fixed-orifice as the expa
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14 (residuals) should have a zero m
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16 expected distribution of the res
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18 operation. Another advantage is
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20 1.1.2.1 Original SRB Fault Diagn
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22 Corresponding to the SRB fault d
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24 integration of the probability d
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26 1. Simplifies fault detection fr
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28 Step i Do FDD on fault i . After
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30 ROOFTOP UNIT FAULTS COMPONENT-LE
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32 has two possible causes: refrige
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34 1.2.3 Decoupling of Component Fa
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36 1.2.3.2 Condenser-Related Faults
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38 mixture, χ ref is known as the
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40 Table 1-3 also lists the refrige
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42 Refrigerant Property T cond, pre
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44 as an independent feature only f
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46 evaporator air flow rate reducti
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48 5. 2 Pll ∆ deviates drasticall
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50 System-Level Faults RefUnder Ref
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52 1.2.5 Summary of Decoupling Sche
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54 noise, system disturbances and m
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56 compressor data. When there is a
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58 Figure 2-5 Decoupling evaporator
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60 Total Pressure Drop of Liquid- L
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62 Figure 2-11 Illustration of Demo
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64 bypass the compressor. At this t
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66 for T dis because there is no ov
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68 Figure 2-14 Outputs of the FDD d
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70 the system requires more refrige
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72 recommended that: the system req
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74 Figure 2-20 Outputs of the FDD d
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76 Figure 2-21 Histogram bar plot o
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82 2.3.2 Summarized Results for Oth
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84 3 CONCLUSIONS AND RECOMMENDATION
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86 Breuker, M.S. and Braun, J. E.,
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88 Lee, W., House, J.M. and Shin, D
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90 APPENDIX 1 PHYSICAL MODELS OF EX
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92 A1.1.2 Short-Tube Models Many re
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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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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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