Fault Detection and Diagnostics for Rooftop Air Conditioners

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46 Fault type Table 3-1 Fault diagnosis rules Tevap Tsh Tcond Tsc Thg ∆ Tca ∆ Tea Refrigerant leakage - + - - + - - Comp. Valve Leak + - - - - - - Liquid Restriction - + - + + - - Condenser Fouling + - + - + + - Evaporator Fouling - - - - - - + Fault quadrant-2 Normal Operation Region Residual-2 Fault quadrant-1 Fault diagnosis Boundary Residual-2 Fault diagnosis Boundary M normal Σ normal Fault Detection Boundary Figure 3-4 Fault detection and diagnosis boundaries 3.2.4.2 Simple Distance Fault Diagnosis Classifier To eliminate the independence assumption and improve fault diagnosis performance, a simple distance fault diagnosis classifier, which does not require integration of the probability distributions, was developed and validated. This method is briefly illustrated in Figure 3-5 using a two-dimensional case. Based on the predefined fault points (i.e., F 1 and F 2 ) corresponding to the fault quadrants (I and II), the distance ratio of the smallest distance to the second smallest distance (as to
47 current operation point P 1, P F 1 2 ratio dist = ) is calculated, and when the distance ratio is P F 1 1 less than a preset threshold β , then a fault corresponding to the minimum distance will be indicated. In Figure 3-5, the fault point with the minimal distance for P 1 is F 2 while for P 7 is F 1, and if the distance ratio is lower than a preset threshold, fault II would be indicated for P 1 while fault I for P 7 . The performance of the method is good in that the distance ratio monotonously decreases with increasing fault level ( P 1 has the same fault level as P 2 and P 4 but a higher fault level than P 5 and lower fault level than P 3 and P 6 ), and is relatively insensitive to the choice of parameters c ( P 6 can be classified correctly in Figure 3-5) and different operating conditions over a wide range (refer to Deliverables 2.1.3, 2.1.4 & 2.1.5 and Li & Braun (2003) for details). Model Residual-2 True Residual-2 Fault Quadrant II Fault Quadrant I F 2 (-c, c) F 1 ( c, c) P 6 P 3 P 5 P 1 (0,0) P 4 P 2 M norma P 7 Model Residual-1 True Residual-1 Normal Operation Region Figure 3-5 Distance method for fault diagnosis
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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
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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
Page 299 and 300: 108 Mass flow rate Local linearizat
Page 301 and 302: 110 temperature on the RTD is unifo
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Page 305 and 306: 1 ACKNOWLEDGEMENTS The research tha
Page 307 and 308: 3 2.2.3 Todd Harms’ Data ........
Page 309 and 310: 5 LIST OF FIGURES Figure E-1. FDD d
Page 311 and 312: 7 LIST OF TABLES Table E-1 FDD resu
Page 313 and 314: 9 IA = Independence Assumption λ i
Page 315 and 316: 11 EXECUTIVE SUMMARY Packaged air c
Page 317 and 318: 13 current values of the fault indi
Page 319 and 320: 15 Figure E-4 Histogram of the EER
Page 321 and 322: 17 2. Operational cost savings, whi
Page 323 and 324: 19 Table E-5 Conservative Lifetime
Page 325 and 326: 21 constraints. Economic constraint
Page 327 and 328: 23 Paper statistics in HVAC FDD 35
Page 329 and 330: 25 on directional changes to identi
Page 331 and 332: 27 fault levels at different operat
Page 333 and 334: 29 was concluded that the method wa
Page 335 and 336: 31 However, several improvements ar
Page 337 and 338: 33 point sensor placement is genera
Page 339 and 340: 35 2 DATA SOURCES USED FOR EVALUATI
Page 341 and 342: 37 The fives types of faults are re
Page 343 and 344: 39 Occupation Type Climate Location
Page 345 and 346: 41 The SRB FDD method determines wh
Page 347 and 348: 43 The following sections describe
Page 349: 45 points rather than on a distribu
Page 353 and 354: 49 4 A DECOUPLING-BASED FDD TECHNIQ
Page 355 and 356: 51 This approach overcomes the draw
Page 357 and 358: 53 ⎡ ∆T ⎢ ⎢ ∆T 2 ⎢ ∆
Page 359 and 360: 55 improving the compressor model p
Page 361 and 362: 57 Condenser Air Mass Flow Rate (lb
Page 363 and 364: 59 Evaporator Air Mass Flow Rate (l
Page 365 and 366: 61 Liquid-Line Pressure Drop (PSI)
Page 367 and 368: 63 4.2.2 Purdue Field Emulation Sit
Page 369 and 370: 65 1. Evacuated the system, and the
Page 371 and 372: 67 normal _ value − current _ val
Page 373 and 374: 69 Figure 4-16 shows one frame afte
Page 375 and 376: 71 Figure 4-18 shows one frame afte
Page 377 and 378: 73 valve position can be seen from
Page 379 and 380: Figure 4-22 Outputs of the FDD demo
Page 381 and 382: 77 Figure 4-23 Histogram bar plot o
Page 387 and 388: 83 4.2.3.2 Summarized Results for O
Page 389 and 390: 85 5 ECONOMIC ASSESSMENTS Since the
Page 391 and 392: 87 inspection savings would be $2,0
Page 393 and 394: 89 Q & Cap = W & × EER (5-2) The e
Page 395 and 396: 91 4. electricity costs ( C e ). Ut
Page 397 and 398: 93 Table 5-3 lists estimates of equ
Page 399 and 400: 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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