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1.5 Outline of the Thesis Introduction This work explores the possible benefits of automated fault diagnosis of the most recent Cardio- Vascular X-Ray Systems at Philips Medical Systems. In particular, the problem that is encountered in the work for this thesis is to improve fault diagnosis of Philips Cardio-Vascular X-Ray Systems with respect to higher dependability. An improved fault diagnosis approach is able to increase dependability of the system, because timely and accurate identification of root causes of failures enables system recovery. Fault diagnosis is only successful when produced diagnoses agree with reality, so the result could be used to recover the system. Accuracy is the extent to which diagnoses agree with reality, and is considered to be the most important criterion for diagnostic performance. This thesis presents a proof-of-concept of the model-based approach to fault diagnosis, aimed at Philips Cardio-Vascular X-Ray Systems. In order to achieve this, the aim of the project is to 1. uncover the drawbacks of today’s practice to fault diagnosis. 2. show which automated techniques to fault diagnosis could possibly increase diagnostic performance. 3. motivate the choice for the model-based approach by criteria for diagnostic performance. 4. apply the model-based approach to an example system. This is a subsystem of the Philips Cardio-Vascular X-Ray System. This case study elicits modeling issues that typically occur when MBD is applied in the industrial domain. 5. study the applicability of LYDIA to model specific dynamics, as well as the use of the accompanying tool set in a real-life scenario. The modeling issues that are discussed in the case study include a discussion of an approach to modeling, the use of entropy to estimate the diagnostic performance of a model, and the use of entropy to determine next best measurements. Beyond the scope of this thesis is to deal with multiple and dependent faults. In this thesis it is shown that the current practice at PMS is not optimal with respect to criteria for diagnostic performance, and that model-based diagnosis is likely to improve the fault diagnosis process at PMS. However, it is not possible to conclude that MBD improves fault diagnosis with respect to higher dependability of Philips Cardio-Vascular X-Ray Systems. The experimental methodology that should be used to establish this conclusion requires that the diagnostic accuracy can be determined for both the current practice as the proposed MBD approach. Despite the fact that it is possible at PMS to know what observations caused a failure, it is impossible to determine the adjudged diagnosis that explains these observations. Consequently, it is not possible to conclude that MBD improves fault diagnosis with respect to higher dependability of Philips Cardio-Vascular X-Ray Systems (see Chapter 6). It is shown that entropy is a valuable metric to show the improvement of different MBD implementations. This way, it is established that an MBD approach is able to achieve the same accuracy and entropy as fault diagnosis applied by experts. Furthermore, entropy is also able to suggest various alternative MBD implementations that lead to higher accuracy. 1.5 Outline of the Thesis The outline of the thesis is as follows. In the next chapter, the current approach at PMS to fault diagnosis is reviewed and analyzed by means of an example. The final section of Chapter 2 presents 6
Introduction 1.5 Outline of the Thesis criteria to estimate diagnostic performance of approaches to fault diagnoses. This enables an evaluation of the current approach, and a precise definition of the problem. This problem is solved in the remainder of this thesis. Chapter 3 presents possible solutions to the problem. It presents automated approaches to fault diagnosis, and uses the criteria of Chapter 2, as a motivation for developing a model-based approach. Then, Chapter 4 introduces the theory of model-based fault diagnosis. Chapter 5 elaborates the technique on a subsystem of the Philips Cardio-Vascular X-Ray System, the so-called beam propeller movement of the frontal stand. This chapter presents MBD as a solution that improves fault diagnosis with respect to higher dependability. Chapter 6 concludes this thesis with a discussion on the solution, conclusions and recommendations. 7
Page 1: Automated Fault Diagnosis at Philip
Page 4 and 5: © 2006 W.M. Lindhoud. Document gen
Page 7: Preface The work presented in this
Page 10 and 11: CONTENTS 4.4 Modeling . . . . . . .
Page 13: List of Tables 3.1 Evaluation appro
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Page 25 and 26: State-of-the-Practice Fault diagnos
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Page 58 and 59: 4.5 Entropy Gain Model-Based Fault
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Diagnosing the Beam Propeller Movem
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Chapter 6 Conclusions and Recommend
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Conclusions and Recommendations 6.2
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BIBLIOGRAPHY [12] Johan de Kleer an
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Appendix A Glossary of terms In thi
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Glossary of terms • Diagnostic Pe
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Glossary of terms • Model: an abs
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Glossary of terms • System: an en
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B.2 System Data Case Study Details
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B.4 Full List of Examined Fault Sce
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B.5 Discretization of Implementatio
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C.1 The Synthetic Models that are U
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C.2 Model of the Power Supply Examp
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C.3 The Models Constructed for the
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Appendix D State-of-the-Future Faul
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