heat flow modeling of hvac systems for fault detection and diagnosis · heat flow modeling of hvac...

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)

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

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)

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

DataIn

DataIn DataIn

AHU exampleAHU example

RfanRductMixerMduct

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

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:

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

Mode error

Failure rulesFailure rules

Principal inequality:rule = (condition: expr1 > expr2 + threshold)rule (condition: expr1 > expr2 + threshold)

Example:M

h coutdoor

rule1 = (uhc=0: Tsa > Tma + e1)1 T T l+T T l+dTfe1 = TmaTol+TsaTol+dTfan

Possible faults: TsaSensor, TmaSensor, hcValve

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

rule=X<Y

X YYmin

Ymin ?l f l

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

Estimation uncertainties

Duct with temperature sensorDuct with temperature sensor

temperature sensor interval T:Tmax= Tsens+toleranceTmax= Tsens+toleranceTmin = Tsens-tolerance

TfwdIn TfwdOut

estimate

TrevOut TrevIn

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

TfwdIn

TfwdOutesti-mate

estimateTrevOut TrevIn

valveCtrl

Fault detection and diagnosis systemFault detection and diagnosis system

Supervisor ctrl

VAV t l

Zone ctrl

VAV ctrl Space ctrlAHU ctrl VAV ctrl Space ctrl

SpaceVAVAHU VAV Space

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

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

AHU exampleAHU example

Pla ntD

eatinPla nt

Heatin

Pla ntD

eatinPla nt

Heatin

Pla ntD

eatinPla nt

Heatin

Zo neAir

andSide

n gL oop

Wate rr

Zo neAir

andSide

n gL oop

Wate rr

Zo neAir

andSide

n gL oop

andSide

n gL oop

Wate r

Wate rr

Zo neAir

andSide

n gL oop

Zo neAir

andSide

n gL oop

Wate r

Ai l itt er

rSpli tt er

Ai l itt er

rSpli tt er

Ai l itt er

rSpli tt er

Ai l itt er

rSpli tt er

urn Hot w

ater Mixtu

rSpli tt er

Engineering ToolEngineering Tool

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

Reheat Valve Composite of ifc elementsSensor IfcSensor TEMPERATURESENSOR PRESSURESENSOR

HUMIDITYSENSORController IfcFlowController

Run-time FDDRun time FDD

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

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

heat flow modeling of hvac systems for fault detection and diagnosis · heat flow modeling of hvac...

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