Fault diagnosis of sensors, devices, and equipment is an important topic in the nuclear industry for effective and continuous operation of nuclear power plants. All the fault diagnostic approaches depend critically on the sensors that measure important process variables. Whenever a process encounters a fault, the effect of the fault is propagated to some or all the process variables. The ability of the sensor network to detect and isolate failure modes and anomalous conditions is crucial for the effectiveness of a fault detection and isolation (FDI) system. However, the emphasis of most fault diagnostic approaches found in the literature is primarily on the procedures for performing FDI using a given set of sensors. Little attention has been given to actual sensor allocation for achieving the efficient FDI performance. This dissertation presents a graph-based approach that serves as a solution for the optimization of sensor placement to ensure the observability of faults, as well as the fault resolution to a maximum possible extent. This would potentially facilitate an automated sensor allocation procedure. Principal component analysis (PCA), a multivariate data-driven technique, is used to capture the relationships in the data, and to fit a hyper-plane to the data. The fault directions for different fault scenarios are obtained from the prediction errors, and fault isolation is then accomplished using new projections on these fault directions. The effectiveness of the use of an optimal sensor set versus a reduced set for fault detection and isolation is demonstrated using this technique. Among a variety of desalination technologies, the multi-stage flash (MSF) processes contribute substantially to the desalinating capacity in the world. In this dissertation, both steady-state and dynamic simulation models of a MSF desalination plant are developed. The dynamic MSF model is coupled with a previously developed International Reactor Innovative and Secure (IRIS) model in the SIMULINK environment. The developed sensor placement design and fault diagnostic methods are illustrated with application to the coupled nuclear desalination system. The results demonstrate the effectiveness of the newly developed integrated approach to performance monitoring and fault diagnosis with optimized sensor placement for large industrial systems.

The new approach for sensor diagnostics is presented. The approach, Enhanced Autoassociative Neural Networks (E-AANN), adds enhancement to Autoassociative Neural Networks (AANN) developed by Kramer in 1992. This enhancement allows AANN to identify faulty sensors. E-AANN uses a secondary optimization process to identify and reconstruct sensor faults. Two common types of sensor faults are investigated, drift error and shift or offset error. In the case of drift error, the sensor error occurs gradually while in the case of shift error, the sensor error occurs abruptly. EAANN catches these error types. A chiller model provided synthetic data to test the diagnostic approach under various noise level conditions. The results show that sensor faults can be detected and corrected in noisy situations with the E-AANN method described. In high noisy situations (10% to 20% noise level), E-AANN performance degrades. E-AANN performance in simple dynamic systems was also investigated. The results show that in simple dynamic situations, E-AANN identifies faulty sensors.

This thesis presents techniques for improving building HVAC system performance in existing buildings generated using simulation-based tools and real data. Therefore, one of the aims has been to research the needs and possibilities to assess and improve building HVAC system performance. In addition, this thesis aims at an advanced utilization of building energy management system (BEMS) and the provision of useful information to building operators using simulation tools. Buildings are becoming more complex systems with many elements, while BEMS provide many data about the building systems. There are, however, many faults and issues in building performance, but there are legislative and cost-benefit forces induced by energy savings. Therefore, both BEMS and the computer-based tools have to be utilized more efficiently to improve building performance. The thesis consists of four main parts that can be read separately. The first part explains the term commissioning and the commissioning tool work principal based on literature reviews. The second part presents practical experiences and issues introduced through the work on this study. The third part deals with the computer-based tools application in design and operation. This part is divided into two chapters. The first deals with improvement in the design, and the second deals with the improvement in the control strategies. The last part of the thesis gives several rules for fault diagnosis developed using simulation tools. In addition, this part aims at the practical explanation of the faults in the building HVAC systems. The practical background for the thesis was obtained though two surveys. The first survey was carried out with the aim to find the commissioning targets in Norwegian building facilities. In that way, an overview of the most typical buildings, HVAC equipment, and their related problems was obtained. An on-site survey was carried out on an example building, which was beneficial for introducing the building maintenance structure and the real hydronic heating system faults. Coupled simulation and optimization programs (EnergyPlus and GenOpt) were utilized for improving the building performances. These tools were used for improving the design and the control strategies in the HVAC systems. Buildings with a hydronic heating system were analyzed for the purpose of improving the design. Since there are issues in using the optimization tool, GenOpt, a few procedures for different practical problems have been suggested. The optimization results show that the choice of the optimization functions influences significantly the design parameters for the hydronic heating system. Since building construction and equipment characteristics are changing over time, there is a need to find new control strategies which can meet the actual building demand. This problem has been also elaborated on by using EnergyPlus and GenOpt. The control strategies in two different HVAC systems were analyzed, including the hydronic heating system and the ventilation system with the recovery wheel. The developed approach for the strategy optimization includes: involving the optimization variables and the objective function and developing information flow for handling the optimization process. The real data obtained from BEMS and the additional measurements have been utilized to explain faults in the hydronic heating system. To couple real data and the simple heat balance model, the procedure for the model calibration by use of an optimization algorithm has been developed. Using this model, three operating faults in the hydronic heating system have been elaborated. Using the simulation tools EnergyPlus and TRNSYS, several fault detection and diagnosis (FDD) rules have been generated. The FDD rules were established in three steps: testing different faults, calculating the performance indices (PI), and classifying the observed PIs. These rules have been established for the air cooling system and the hydronic heating system. The rules can diagnose the control and the component faults. Finally, analyzing the causes and the effects of the tested faults, useful information for the building maintenance has been descriptively explained. The most important conclusions are related to a practical connection of the real data and simulation-based tools. For a complete understanding of system faults, it is necessary to provide real-life information. Even though BEMS provides many building data, it was proven that BEMS is not completely utilized. Therefore, the control strategies can always be improved and tuned to the actual building demands using the simulation and optimization tools. It was proven that many different FDD rules for HVAC systems can be generated using the simulation tools. Therefore, these FDD rules can be used as manual instructions for the building operators or as a framework for the automated FDD algorithms. / Denne avhandlingen presenterer noen fremgangsmåter for forbedring av ytelser for VVS-tekniske anlegg i eksisterende bygninger basert på bruk av simuleringsverktøy og virkelige måledata. Ett av målene har vært å undersøke behov og muligheter for vurdering og forbedring av ytelser for VVS-anlegg i bygninger. I tillegg har denne avhandlingen hatt som mål å fremme bruk av SD-anlegg samt å fremskaffe nyttig informasjon til driftspersonalet. Bygninger blir stadig mer kompliserte systemer som inneholder flere og flere komponenter mens SD-anlegg håndterer en stadig større mengde data fra bygningsinstallasjoner. På den ene siden registreres det ofte feil og problemer med hensyn til ytelsene til de VVS-tekniske installasjonene. På den andre siden innføres det stadig strengere lovmessige pålegg og kost-nyttekrav motivert i energieffektiviseringen. SD-anlegg og databaserte verktøy bør derfor brukes mer effektivt for forbedring av ytelsene. Avhandlingen består av fire hoveddeler hvor hver del kan leses separat. Den første delen, som er basert på literatturstudie, forklarer funksjonskontroll som begrep og prinsipper for oppbygging av verktøy for funksjonskontroll. Den andre delen presenterer praktisk erfaring og problemstillinger utviklet og behandlet i løpet av arbeidet med avhandlingen. Den tredje delen handler om anvendelse av databaserte verktøy for forbedring av ytelsen for VVS-tekniske installasjoner. Den tredje delen er delt opp i to kapitler, hvorav et handler om forbedring av systemløsninger og et om forbedring av styringsstrategier. Den siste delen presenterer flere regler for feilsøking og diagnostisering utviklet gjennom bruk av simuleringsverktøy. I tillegg gir denne delen en praktisk forklaring av feilene i de VVS-anleggene som er behandlet i undersøkelsen. Det praktiske grunnlaget for avhandlingen er etablert gjennom to undersøkelser. Den første var en spørreundersøkelse som hadde til hensikt å kartlegge målsetninger for funksjonskontroll i norske bygninger. Gjennom dette ble det etablert en oversikt over de mest typiske bygninger med tilhørende VVS-anlegg og de mest forekommende problemene. En dypere undersøkelse ble utført på ett casebygg. Denne undersøkelsen viste seg å være nyttig både for kartlegging av betydningen av organisering av driften av bygningen og for avdekking av de virkelige feilene i det vannbårne oppvarmingssystemet. En kobling mellom et simulerings- og et optimaliseringsprogram (EnergyPlus og GenOpt) har vært benyttet for forbedring av ytelsene for de VVS-tekniske installasjonene. Disse verktøyene har vært brukt for forbedring av både systemløsningene og styringsstrategiene for VVS-anlegg. Bygninger med vannbåren oppvarmingssystem har vært analysert for å forbedre systemløsningen. På grunn av begrensninger i bruken av optimaliseringsverktøyet GenOpt, har det blitt utviklet egne prosedyrer for håndtering av visse typer problemstillinger hvor denne begrensningen opptrer. Resultatene for optimaliseringen viser at valg av objektfunksjoner påvirker betydelig parametrene i det vannbårne oppvarmingssystemet. Endringer i egenskapene til både bygningskonstruksjoner og utstyr som skjer på grunn av aldring over tiden, gjør det nødvendig med tilpassning av styringsstrategier slik at det virkelige behovet kan bli dekket. Denne problemstillingen har vært analysert ved bruk av EnergyPlus og GenOpt. Styringsstrategiene for to forskjellige VVS-anlegg, et vannbåret oppvarmingssystem og et ventilasjonsanlegg med varmegjenvinner har blitt behandlet. Den utviklete prosedyren for optimalisering av styringsstrategien består av følgende steg: innføring av optimaliseringsvariabler og objektfunksjon, samt utvikling av informasjonsflyt for behandling av optimaliseringsprosessen. De virkelige data, både fra SD-anlegg og tilleggsmålinger, har vært benyttet for praktisk forklaring av feilene i oppvarmingssystemet. En prosedyre for modellkalibrering basert på bruk av en optimaliseringsalgoritme som kobler sammen de virkelige data og en enkel varmebalansemodell har blitt foreslått. Tre konkrete driftsfeil i oppvarmingssystemet har blitt belyst gjennom bruk av denne varmebalansemodellen. Flere regler for feilsøking og diagnostisering har blitt utviklet ved hjelp av simuleringsverktøyene EnergyPlus and TRNSYS. Denne utviklingen har bestått av tre ulike steg: testing av bestemte feil, beregning av ytelsesindikatorer og til slutt klassifisering av de observerte ytelsesindikatorer. Reglene har blitt utviklet for et system av aggregater for luftkjøling og for et vannbåret oppvarmingssystem. Reglene kan diagnostisere både styringsfeil og komponentfeil. Til slutt presenteres informasjon som er nyttig for drift av VVS-tekniske installasjoner i bygninger basert på en analyse av årsakene for og virkningene av de feil som er behandlet. De viktigste konklusjonene er knyttet til praktisk kombinasjon av virkelige måleverdier og simuleringsverktøy. Informasjon fra det virkelig liv er helt nødvendig for å få en god forståelse av feil som oppstår i anlegg. Det er også vist at potensialet som ligger i alle de data som er tilgjengelige gjennom SD-anlegg, ikke er fullt utnyttet. Gjennom bruk av simuleringsverktøy kan styringsstrategiene alltid bli bedre tilpasset og innjustert til de virkelige behov i bygningen. Simuleringsverktøy kan også brukes for utvikling av prosedyrer for feilsøking og diagnostisering i VVS-tekniske anlegg. Disse prosedyrene kan brukes enten som en veileder for manuell feilsøking og detektering eller som grunnlag for utvikling av automatiserte algoritmer. / Paper II, VI and VII are reprinted with kind permission from Elsevier, sciencedirect.com

Fault diagnosis in discrete event systems is studied using a state-based framework. Faults can be either intermittent or permanent. For intermittent faults, system may recover from faulty behaviour through reset. To diagnose such intermittent faults, fault counters are introduced. Fault counters record the number of intermittent faults which must have occurred according to the output observations. This provides the main diagnosis. They also record the number of possible intermittent faults which may have occurred but cannot be confirmed. This provides auxiliary diagnostic information. Fault diagnosability is then studied. Since faults may be intermittent, they may occur repeatedly. Three different notions are studied: 1-diagnosability, 1,k-diagnosability, and 1,infty-diagnosability, and criteria for each of these notions are obtained. The criteria are expressed in terms of fault counters and extend the diagnosability criteria for permanent faults. The concept of a resonant path is introduced, which plays an important role in studying diagnosability.

Traditional diagnosis has been performed with hardware redundancy and limit checking. The development of more powerful computers have made a new kind of diagnosis possible. Todays computing power allows models of the system to be run in real time and thus making model-based diagnosis possible. The objective with this thesis is to investigate the potential of model-based diagnosis, especially when combined with active diagnosis. The diagnosis system has been applied on a model of the JAS39 Gripen fuel pressurization system. With the sensors available today no satisfying diagnosis system can be built, however, by adding a couple of sensors and using active model-based diagnosis all faults can be detected and isolated into a group of at most three components. Since the diagnosis system in this thesis only had a model of the real system to be tested at, this thesis is not directly applicable on the real system. What can be used is the diagnosis approach and the residuals and decision structure developed here.

Fault diagnosis in discrete event systems is studied using a state-based framework. Faults can be either intermittent or permanent. For intermittent faults, system may recover from faulty behaviour through reset. To diagnose such intermittent faults, fault counters are introduced. Fault counters record the number of intermittent faults which must have occurred according to the output observations. This provides the main diagnosis. They also record the number of possible intermittent faults which may have occurred but cannot be confirmed. This provides auxiliary diagnostic information. Fault diagnosability is then studied. Since faults may be intermittent, they may occur repeatedly. Three different notions are studied: 1-diagnosability, 1,k-diagnosability, and 1,infty-diagnosability, and criteria for each of these notions are obtained. The criteria are expressed in terms of fault counters and extend the diagnosability criteria for permanent faults. The concept of a resonant path is introduced, which plays an important role in studying diagnosability.

When released into the atmosphere, traditional refrigerants contribute to climate change several orders of magnitude more than a corresponding amount of carbon dioxide. For that reason, an increasing amount of interest has been paid to transcritical vapor compression systems in recent years, which use carbon dioxide as a refrigerant. Vapor compression systems also impact the environment through their consumption of energy. This can be greatly increased by faulty operation. Automated techniques for detecting and diagnosing faults have been widely tested for subcritical systems, but have not been applied to transcritical systems. These methods can involve either dynamic analysis of the vapor compression cycle or a variety of algorithms based on steady state behavior. In this thesis, the viability of dynamic fault detection is tested in relation to that of static fault detection for a transcritical refrigeration system. Step tests are used to determine that transient behavior does not give additional useful information. The same tests are performed on a subcritical air-conditioner showing little value in dynamic fault detection. A static component based method of fault detection which has been applied to subcritical systems is also tested for all pairings of four faults: over/undercharge, evaporator fouling, gas cooler fouling, and compressor valve leakage. This technique allows for low cost measurement and independent detection of individual faults even when multiple faults are present. Results of this method are promising and allow distinction between faulty and fault-free behavior.

This master’s thesis work was performed at Volvo Powertrain in Köping, Sweden, which manufactures gearboxes and integrated transmission systems for heavy vehicles. The thesis is a continuation of a previous master’s thesis performed at the Köping factory in 2009. After manufacturing and assembly, each gearbox is manually validated to ensure the gearbox quality and functionality. When validating the gearbox gears, the operator shifts the gearbox in a predefined manner and listens for irregularities. If an error sound is heard the operator must then locate the source of error. With numerous of cog wheels rotating at the same time this task requires extensive knowledge and experience of the operator. The main objective is to develop an automatic diagnostic system for detection of cog errors and assist the operator in the process of locating the faulty component. The work consists of two parts. In the first part the automatic diagnostic system is developed and a database of gearbox recordings is stored. The amounts of logged non-faulty gearboxes are significantly much larger (50) than the logged faulty gearboxes (1). Therefore, when determining thresholds needed for the diagnosis, the data obtained from the non-faulty gearboxes are used. Two statistical methods are presented to extract the thresholds. The first method uses an extremevalue distribution and the other method a Gaussian distribution. When validated, both methods did successfully detect on cog faults. In the second part an investigation is made of how shaft imbalance can be detected and implemented in the developed system. Volvo Powertrain continually follows-up all faults found at the validation station to ensure the quality of their work and eliminate the sources of error. During system testing one logged gearbox was found faulty. The automatic diagnostic system did successfully detect and locate the faulty component which later also was confirmed when the gearbox was dismounted. With only one detected error it is difficult to conclude the system performance and further testing is required. However, during the testing no false detections were made.

When flying a fighter aircraft such as the JAS 39 Gripen, the pilot is exposed to high g-loads. In order to prevent the draining of blood from the brain during this stress an anti-g protection system is used. The system consists of a pair of trousers, called the anti-g trousers, with inflatable bladders. The bladders are filled with air, pressing tightly on to the legs in order to prevent the blood from leaving the upper part of the body. The purpose of this thesis is to detect if the pressure of the anti-g trousers is deviating from the desired value. This is done by developing a detection algorithm which gives two kinds of alarm. One is given during minor deviations using a CUSUM test, and one is given at grave deviations, based on different conditions including residual, derivative and time. The thresholds, in which between the pressure should lie in a faultless system, are calculated from the g-load value. The thresholds are based upon given static guidelines for the pressure tolerance area and are modified in order to adapt to the estimated dynamics of the system. The values of the input signals, pressure and g-load, were taken from real flight sessions. The validation has been performed using both faultless and faulty flight sequences, with low false alarm rate and no missed detections. All together the detection system is considered to work well.

Diagnosis means detection and isolation of faults. A model based diagnosis system is built on a mathematical model of the system. The difficulty when constructing the diagnosis system depends om how the model is formulated. In this report, a method is described that rewrites the model on such a form that the construction of the diagnosis algoritm is easy. The model is transformed by two state space transformations and the result will be a system on state space form where one part of the system becomes easy to supervise. The main part of the report describes the procedure to create these transformations, which can be done in seven steps, based on differential geometric methods. The aim of this masters thesis was to create an implementation in Mathematica (a computer tool for symbolic formula manipulation) of the creation of the two transformations and the system transformation. The created functions are described and examples of these are given. A further aim was to evaluate if Mathematica could be a good support to rewrit a model. This was done by studying examples, and on the basis of the examples, identify difficult and easy steps. The program has shown to be a good aid. Two of the seven steps have been identified as difficult and proposals for improvements have been given.