| 1. |
- Armengol Llobet, J., et al.
(författare)
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Minimal Structurally Overdetermined Sets for Residual Generation: A Comparison of Alternative Approaches
- 2009
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Ingår i: <em>Proceedings of IFAC Safeprocess'09</em>. - Barcelona, Spain. - 9783902661463 ; , s. 1480-1485
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Konferensbidrag (refereegranskat)abstract
- The issue of residual generation using structural analysis has been studied by several authors. Structural analysis does not permit to generate the analytical expressions of residuals since the model of the system is abstracted by its structure. However, it determines the set of constraints from which residuals can be generated and it provides the computation sequence to be used. This paper presents and compares four recently proposed algorithms that solve this problem.
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| 2. |
- Frisk, Erik, 1971-, et al.
(författare)
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A toolbox for design of diagnosis systems
- 2006
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Ingår i: IFAC Safeprocess06,2006. - Beijing, China : IFAC. ; , s. 703-
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Konferensbidrag (refereegranskat)abstract
- Design of diagnosis systems is a complex task that involves many different steps. Full understanding of all different parts of the design procedure requires deep knowledge on theory from a wide variety of subjects. Thus, to encourage the use of results from diagnosis research it is highly desirable to have software support in the design process. This paper describes ongoing work for determining an architecture for such a toolbox. The paper also describes software solutions in the toolbox. In industry as well as in universities, Matlab is probably the most widespread tool used by control engineers. Therefore the toolbox is primarily based upon Matlab but also some computer algebraic tools such as Mathematica and Maple are used.
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| 3. |
- Krysander, Mattias, 1977-, et al.
(författare)
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An Efficient Algorithm for Finding Minimal Overconstrained Subsystems for Model-Based Diagnosis
- 2008
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Ingår i: IEEE transactions on systems, man and cybernetics. Part A. Systems and humans. - 1083-4427 .- 1558-2426. ; 38:1, s. 197-206
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Tidskriftsartikel (refereegranskat)abstract
- In model based diagnosis, the diagnostic system construction is based on a model of the technical system to be diagnosed. To handle large differential algebraic models and to achieve fault isolation, a common strategy is to pick out small over-constrained parts of the model and to test these separately against measured signals. A new algorithm for computing all minimal over-constrained sub-systems in a model is proposed. For complexity comparison, previous algorithms are recalled. It is shown that the time complexity under certain conditions is much better for the new algorithm. This is illustrated using a truck engine model.
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| 4. |
- Krysander, Mattias, 1977-, et al.
(författare)
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An Efficient Algorithm for Finding Over-constrained Sub-systems for Construction of Diagnostic Tests
- 2005
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Ingår i: 16th International Workshop on Principles of Diagnosis DX-05,2005. - Pacific Grove, California, USA. ; , s. 55-60
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Konferensbidrag (refereegranskat)abstract
- In this paper, a new algorithm for computing all minimal over-constrained sub-systems in a structural model is proposed. To handle large differential algebraic models in diagnosis, systematic structural approaches to find testable sub-systems have been suggested. It is shown how the algorithm can be incorporated and improve some of them. Previous algorithms are recalled and it is shown that the new algorithm is 14000 times faster when applied to a Scania truck engine model.
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| 5. |
- Krysander, Mattias, 1977-
(författare)
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Design and Analysis of Diagnosis Systems Using Structural Methods
- 2006
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In complex and automated technological processes the effects of a fault can quickly propagate and lead to degradation of process performance or even worse to a catastrophic failure. This means that faults have to be found as quickly as possible and decisions have to be made to stop the propagation of their effects and to minimize process performance degradation. The behavior of the process is affected in different ways by different faults and the fault can be found by ruling out faults for which the expected behavior of the process is not consistent with the observed behavior. In model-based diagnosis, a model describes the expected behavior of the process for the different faults.A device for finding faults is called a diagnosis system. In the diagnosis systems considered here, a number of tests check the consistency of different parts of the model, by using observations of the process. To be able to identify which fault that has occurred, the set of tests that is used must be carefully selected. Furthermore, to reduce the on-line computational cost of running the diagnosis system and to minimize the in general difficult and time-consuming work of tests construction, it is also desirable to use few tests.A two step design procedure for construction of a diagnosis systems is proposed and it provides the means for selecting which tests to use implicitly by selecting which parts of the model that should be tested with each test. Then, the test design for each part can be done with any existing technique for model-based diagnosis.Two different types of design goals concerning the capability of distinguishing faults is proposed. The first goal is to design a sound and complete diagnosis system, i.e., a diagnosis system with the following property. For any observation, the diagnosis system computesexactly the faults that together with the observation are consistent with the model. The second goal is specified by which faults that should be distinguished from other faults, and this is called the desired isolability.Given any of these two design goals, theory and algorithms for selecting a minimum cardinality set of parts of the model are presented. Only parts with redundancy can be used for test construction and a key result is that there exists a sound and complete diagnosis system based on the set of all minimal parts with redundancy in the model. In differentialalgebraic models, it is in general difficult to analytically identify parts with redundancy, because it corresponds to variable elimination or projection. It is formally shown that redundant parts can be found by using a structural approach, i.e., to use only which variables that are included in each equation. In the structural approach, parts with more equations than unknowns are identified with efficient graph-theoretical tools. A key contribution is a new algorithm for finding all minimal parts with redundancy of the model. The efficiency of the algorithm is demonstrated on a truck engine model and compared to the computational complexity of previous algorithms.In conclusion, tools for test selection have been developed. The selection is based on intuitive requirements such as soundness or isolability requirements specified by the diagnosis system designer. This leads to a more straightforward design of diagnosis systems, valuable engineering time can be saved, and the resulting diagnosis systems use minimum number of tests, i.e., the on-line computational complexity of the resulting diagnosis systems become low.
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| 6. |
- Krysander, Mattias, et al.
(författare)
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Fault Diagnosis utilizing Structural Analysis
- 2002
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Konferensbidrag (refereegranskat)abstract
- When designing model-based fault-diagnosis systems, the use of consistency relations (also called e.g. parity relations) is a common choice. Different subsets are sensitive to different subsets of faults, and thereby isolation can be achieved. This paper presents an algorithm for finding a small set of submodels that can be used to derive consistency relations with highest possible diagnosis capability. The algorithm handles differential algebraic models and is based on graph theoretical reasoning about structure of the model. An important step, towards finding these submodels and therefore also towards finding consistency relations, is to find all minimal structurally singular (MSS) sets of equations. These sets characterize the fault diagnosability.
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| 7. |
- Krysander, Mattias, 1977-, et al.
(författare)
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Fault Isolability Prediction of Diagnostic Models
- 2005
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Ingår i: 16th International Workshop on Principles of Diagnosis DX-05,2005. - Pacific Grove, California, USA. ; , s. 163-168
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Konferensbidrag (refereegranskat)abstract
- Fault isolability plays a significant role and could be critical with respect to many aspects such as safety and maintenance for a process to be diagnosed. In the development of processes including diagnosis, design decisions are taken, e.g. sensor configuration selection, which affects the fault isolability possibilities. In this paper an algorithm for predicting fault isolability possibilities using a structural model describing the process is proposed. Since only a structural model is needed as input, the algorithm can easily predict fault isolability possibilities of different design concepts. In contrast to previous algorithms using structural models no assumption is imposed on the model. The algorithm computes faults that cannot be distinguished from other faults, which can be used to exclude design alternatives with insufficient isolability possibility.
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| 8. |
- Krysander, Mattias, 1977-, et al.
(författare)
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Statistical Properties and Design Criterions for Fault Isolation in Noisy Systems
- 2008
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Ingår i: 19th International Workshop on Principles of Diagnosis, DX,2008. - Sydney, Australia : DX.
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Konferensbidrag (refereegranskat)abstract
- Fault diagnosis in the presence of noise and model errors is of fundamental importance. In the paper, the meaning of fault isolation performance is formalized by using the established notion of coverage and false coverage from the field of statistics. Then formal relations describing the relationship between fault isolation performance and the residual related design parameters are derived. For small faults, the measures coverage and false coverage are not applicable so therefore, a different performance criteria, called sub-coverage, is proposed. The performance of different AI-based fault isolation schemes is evaluated and it is notably shown that the well known principle of minimal cardinality diagnosis gives a bad performance. Finally, some general design guidelines that guarantee and maximize the fault isolation performance are proposed.
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| 9. |
- Krysander, Mattias, 1977-, et al.
(författare)
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Structural Analysis for Fault Diagnosis of DAE Systems Utilizing Graph Theory and MSS Sets
- 2002
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- When designing model-based fault-diagnostic systems, the use of consistency relations (also called e.g. parity relations) is a common choice. Different consistency relations are sensitive to different subsets of faults, and thereby isolation can be achieved. This report presents an algorithm for finding a small set of submodels that can be used to derive consistency relations with highest possible diagnosis capability. The algorithm handles differential-algebraic models and is based on graph theoretical reasoning about the structure of the model. An important step towards finding these submodels, and therefore also towards finding consistency relations, is to find all minimal structurally singular (MSS) sets of equations. These sets characterize the fault diagnosability. The algorithm is applied to a large nonlinear industrial example, a part of a paper plant. In spite of the complexity of this process, a small set of consistency relations with high diagnosis capability is successfully derived.
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| 10. |
- Krysander, Mattias, et al.
(författare)
-
Structural Analysis for Fault Diagnosis of DAE Systems Utilizing MSS Sets
- 2002
-
Konferensbidrag (refereegranskat)abstract
- When designing model-based fault-diagnosis systems, the use of consistency relations (also called e.g. parity relations) is a common choice. Different subsets are sensitive to different subsets of faults, and thereby isolation can be achieved. This paper presents an algorithm for finding a small set of submodels that can be used to derive consistency relations with highest possible diagnosis capability. The algorithm handles differential algebraic models and is based on graph theoretical reasoning about structure of the model. An important step, towards finding these submodels and therefore also towards finding consistency relations, is to find all minimal structurally singular (MSS) sets of equations. These sets characterize the fault diagnosability. The algorithm is successfully applied to a large nonlinear industrial example, a paper plant.
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