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HEAT FLOW MODELING OF HVAC SYSTEMS FOR FAULT DETECTION AND DIAGNOSIS
Yan Lu, Siemens Corporation, Corporate Researchp pGerhard Zimmermann, University of KaiserslauternGeorge Lo, Siemens Corporation, Corporate Research
University of Kaiserslautern Siemens Corporation, Corporate Research
OutlineOutline
1.Introduction2.Heat flow modeling method3 Fault detection and diagnosis system3.Fault detection and diagnosis system4.System tests5.Conclusion
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 2 SimBuild 2010
MotivationMotivation
Complex HVAC systems lack sufficient fault detection and diagnostic (FDD) capabilities leading to(FDD) capabilities, leading to
Decreased energy efficiencyReduced lifetime of the systemLoss of occupant comfort and productivityLoss of occupant comfort and productivity
Run-time FDD for building HVAC systems improves building operation
Because of building diversity a large diversity of HVAC systems existsBecause of building diversity a large diversity of HVAC systems existsMany solutions for FDD exist, but development and adaptation to
different HVAC systems is expensive
-> Goal: Automatic generation of FDD systems from formal HVAC system building information models (BIM), especially: Industry Foundation Classes (IFC)
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 3 SimBuild 2010
Classes (IFC)
Existing solutionsExisting solutions
Multi Flow Models (MFM), Larsson 2002─ Mass energy information flow graph─ Mass, energy, information flow graph
─ Conservation laws
─ Flow measurements
P f t (f il ) l f HVAC tPerformance assessment (failure) rules for HVAC systems, Castro et.al. 2003Simulation based qualitative and quantitative methods for fault detectionAssociative networks for diagnosisRule based systemsRule based systemsFuzzy modelsNeural networks
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 4 SimBuild 2010
…
Definitions and approachDefinitions and approach
Detection: Defects cause faults that are detected as failures
Diagnosis tries to trace failures back to faults (many-to-many relation)
Our Approach: FDD based on Heat Flow Model (HFM)Our Approach: FDD based on Heat Flow Model (HFM)
− A HFM is a graph model.− The HFM is closely related to the HVAC system structure− The HFM is closely related to the HVAC system structure.− The HFM can be derived from HVAC BIMs.− HFM nodes have generic functions for flow simulation and failure rules.− HFM is object-oriented modeling, the key to automatic generation of FDD.HFM is object oriented modeling, the key to automatic generation of FDD.− Diagnosis is based on associative networks (to be developed)
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 5 SimBuild 2010
Heat flow modeling methodHeat flow modeling method
Graph model:─ flow nodes represent HVAC components─anti-parallel edges represent flows between nodes─ input edges transmit dynamic data from HVAC system
o tp t edges transmit fail re r le res lts─output edges transmit failure rule results
R l O t R l O t
N d 1RevOut RevIn
FwdIn FwdOut
RulesOut
N d 2RevOut RevIn
FwdIn FwdOut
RulesOut
Node1
DataIn
Node2
DataIn
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 6 SimBuild 2010
DataIn DataIn
AHU exampleAHU example
AHU
RfanRductMixerMduct
AHU
Hcoil Ccoil Sfan Sduct
AHU itself can be encapsulated in a blue box and treated as a flow node at the next higher level of the hierarchy
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 7 SimBuild 2010
Flow node typesFlow node types
Air flow nodes:E l F i i b h l h h d d iExamples: Fan, mixing box, wheel, heat exchanger, duct, damper, air sensor, …flow variables: air temperature, humidity, flow, pressure
Water flow nodes:Water flow nodes:Examples: pump, valve, pipe, boiler, water sensor, …flow variables: water temperature, flow, pressure
Mixed flow nodes:Mixed flow nodes:Examples: heating coil, cooling coil, …flow variables: air flow + water flow
Special nodes:Coils without water supply modelingElectric heating coils
Complex nodes:
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 8 SimBuild 2010
Examples: AHU, VAV, FCU, …
Basic fault typesBasic fault types
SensorStuck at a fixed valueDrift
DamperStuck openStuck open Stuck closedLeakage
ValveStuck openStuck closed Leakage
ControlControlOscillation Set point Control error
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 9 SimBuild 2010
Mode error
Failure rulesFailure rules
Principal inequality:rule = (condition: expr1 > expr2 + threshold)rule (condition: expr1 > expr2 + threshold)
Example:M
h coutdoor
c c
Tsa
air
Tma
Toa
psa
rule1 = (uhc=0: Tsa > Tma + e1)1 T T l+T T l+dTfe1 = TmaTol+TsaTol+dTfan
Possible faults: TsaSensor, TmaSensor, hcValve
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 10 SimBuild 2010
Problem: distributed variables
SolutionSolution
Flow variable propagation by estimation (simulation)Forward and backward propagationForward and backward propagationInterval calculation: X=[Xmin,Xmax]Inclusion of tolerancesInclusion of uncertaintiesInclusion of thresholdsGeneric interval overlap failure rules
XmaxYmax
YYmax
YYmax
rule=X<Y
Xmin
X YYmin
YmaxY
Ymin
Y
Ymin ?l f l
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 11 SimBuild 2010
Yminrule=X>Yrule=false
Forward temperature interval propagationForward temperature interval propagation
MductTmaSens
Hcoiluhc=0.5
Ccoilucc=0 SFan Sduct
The value of the threshold depends on features of several nodes.A solution is to calculate the state variables intervals within each node and
prop-agate this value pair forward and backward from node to node with flow p p g pvectors.
The tolerance is a function of ─ Sensor accuracy─ Estimation uncertainties
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 12 SimBuild 2010
Estimation uncertainties
Duct with temperature sensorDuct with temperature sensor
temperature sensor interval T:Tmax= Tsens+toleranceTmax= Tsens+toleranceTmin = Tsens-tolerance
rules
TfwdIn TfwdOut
estimate
r1 r2
TrevOut TrevIn
Tsens
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 13 SimBuild 2010
Tsens
Heating coil without water supply modelHeating coil without water supply model
Simplified physics:temperature increase independent of air flow ratetemperature increase independent of air flow ratetemperature increase between min and max parameterstemperature increase linear to valveCtrl value
rules
esti-
TfwdIn
r1 r2
TfwdOutesti-mate
estimateTrevOut TrevIn
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 14 SimBuild 2010
valveCtrl
Fault detection and diagnosis systemFault detection and diagnosis system
FDD
Supervisor ctrl
VAV t l
Zone ctrl
S t l
Zone ctrl
VAV ctrl Space ctrlAHU ctrl VAV ctrl Space ctrl
SpaceVAVAHU VAV Space
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 15 SimBuild 2010
Engineering phaseEngineering phase
Goal: minimize engineer time to create specific FDD systemUse IFC BIM as far as possiblep
Java HFM class library
IFC of HVAC system and
spacesXML J
library
graphical interface for
additional data
compilerXML HFM
Java generator
additional data
Java FDD run-time
t
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 16 SimBuild 2010
system
Rum-time phaseRum time phase
graphicalJava FDD run-time system
graphical output for
fault hypotheses
sensor valuescontrol valuesset points
HVAC and
set points
HVAC system and
spaces
HVAC and space control system
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 17 SimBuild 2010
AHU exampleAHU example
Pla ntD
eH
eatinPla nt
De
Heatin
Pla ntD
eH
eatinPla nt
De
Heatin
Pla ntD
eH
eatinPla nt
De
Heatin
rM
ixer
Zo neAir
Sp
em
andSide
n gL oop
Hot
Wate rr
Mix
er
Zo neAir
Sp
em
andSide
n gL oop
Hot
Wate rr
Mix
er
Zo neAir
Spr
Mix
er
Zo neAir
Sp
em
andSide
n gL oop
em
andSide
n gL oop
Hot
Wate r
Hot
Wate rr
Mix
er
Zo neAir
Sp
em
andSide
n gL oop
rM
ixer
Zo neAir
Sp
em
andSide
n gL oop
Hot
Wate r
Retu
Hot
Wate r
Ret
urn
Ai l itt er
rSpli tt er
Ret
urn
Ai l itt er
rSpli tt er
Ret
urn
Ai l itt er
Ret
urn
Ai l itt er
rSpli tt er
rSpli tt er
Ret
urn
Ai l itt er
Ret
urn
Ai l itt er
rSpli tt er
urn Hot w
ater Mixtu
rSpli tt er
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 18 SimBuild 2010
ure
Engineering ToolEngineering Tool
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 19 SimBuild 2010
IFC to HFMIFC to HFM
• IFC provides a set of definitions for all object element types encountered in HVAC ypmechanical and control system and a text-based structure for storing those definitions in a data file. • It consists of two major parts:
HFM Node Type IFC HVAC Element IFC type
• It consists of two major parts: •IfcElement—define node properties•IfcPort– define connectivity
HFM Node Type IFC HVAC Element IFC typeDuct ifcDuctSegmentDuctFork IfcDuctFitting JUNCTIONDuctJoint IfcDuctFitting JUNCTIONFan IfcFanDamper IfcDamper CONTROLDAMPERHeating Coil IfcCoil ELECTRICHEATINGCOILgCooling Coil IfcCoil WATERCOOLINGCOILPump IfcPumpValve IfcValve REGULATINGBoiler IfcBoilerChiller IfcChillerMixingBox Composite of ifc elementsR h V l C i f if l
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 20 SimBuild 2010
Reheat Valve Composite of ifc elementsSensor IfcSensor TEMPERATURESENSOR PRESSURESENSOR
HUMIDITYSENSORController IfcFlowController
Run-time FDDRun time FDD
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 21 SimBuild 2010
System testsSystem tests
Simulink HFM fault detection systemSimulink HFM fault detection systemSimulink HVAC system simulator with graphical fault insertion interface Data output for Simulink FDD experimentsData file for other tests
SDL model-based automatic code generation for HFM fault detectionExperiments with data from Simulink simulatorExperiments with real data from HVAC system
Java based FDD system generation from IFC BIME i t ith Si li k d t iExperiments with Simulink data ongoing
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 22 SimBuild 2010
ConclusionConclusion
New Heat Flow Model shows very generic capabilities for automatic FDDNew Heat Flow Model shows very generic capabilities for automatic FDD system generation
New extensions of IFC promise complete HVAC system descriptions for FDD system generation in the futureFDD system generation in the future
FDD systems can supplement existing and new HVAC control systems
with acceptable engineering effortwith acceptable engineering effort
help to considerably reduce maintenance efforts
find faults before critical failures occur
avoid suboptimal system performance in regard to energy consumption and user satisfaction
Aug. 2010 Gerhard Zimmermann, Yan Lu and George LoPage 23 SimBuild 2010