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Diagnosis and Supervision, 6 credits
Diagnos och övervakning, 6 hp
TSFS06
Main field of study
Electrical EngineeringCourse level
Second cycleCourse type
Programme courseExaminer
Erik FriskDirector of studies or equivalent
Johan LöfbergEducation components
Preliminary scheduled hours: 54 hRecommended self-study hours: 106 h
ECV = Elective / Compulsory / Voluntary
Main field of study
Electrical EngineeringCourse level
Second cycleAdvancement level
A1XCourse offered for
- Computer Science and Engineering, M Sc in Engineering
- Industrial Engineering and Management - International, M Sc in Engineering
- Industrial Engineering and Management, M Sc in Engineering
- Mechanical Engineering, M Sc in Engineering
- Applied Physics and Electrical Engineering, M Sc in Engineering
- Information Technology, M Sc in Engineering
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
- Computer Science and Software Engineering, M Sc in Engineering
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Automatic Control, Probability
Intended learning outcomes
To give both a theoretical and practical basis for how to design systems that automatically detect and isolate faulty components in technical processes.
After the course is finished, the student shall:
- know why diagnosis systems are used in different industrial application areas.
- know how to analyze which faults in a complex process that need to be supervised to achieve the overall goals.
- from a case description be able to structure the problem and develop principle and architechture for a complete implementation of a diagnosis system.
- given a formal model description be able to choose suitable mathemematical methods to solve the problem.
- know advantages and disadvantages of the different methods that are included in the course.
- be able to apply mathematical tools and methods from a variety of previous courses to solve diagnosis problems.
- be able to value and verify functionality and performance of a complete diagnosis system.
- have a broad theoretical insight in the subject, deep enough to be able to understand and utilize new research results developed by the research community.
Course content
- Introduction: history and overview, practical application examples.
- Principles for model based diagnosis: mathematical modelling of faults, detection and isolation of faults by means of models, consistency relations, analytical redundancy, decisions with structured hypothesis tests.
- Control theory methods: linear and non-linear residual generation, observers and Kalman filters for diagnosis, residual evaluation, adaptive thresholding, statistical methods.
- Logic based AI methods: basic principles, fault isolation algorithms.
- Probability based diagnosis and Bayesian networks.
- Other: fault trees and FMEA, statistical methods/change detection.
Teaching and working methods
The course is organized in lectures, problem solving sessions, and laborations.
Examination
| LAB1 | Laboratory Work | 1.5 credits | U, G |
| TEN1 | Written Examination | 4.5 credits | U, 3, 4, 5 |
See also course homepage for further practical course information.
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för systemteknikDirector of Studies or equivalent
Johan LöfbergExaminer
Erik FriskCourse website and other links
Education components
Preliminary scheduled hours: 54 hRecommended self-study hours: 106 h
Course literature
Kompendium "Model Based Diagnosis of Technical Processes" av Mattias Nyberg och Erik Frisk med tillhörande lektionskompendium. Utdrag ur boken "Detection of abrupt changes" av Michele Basseville och Igor Nikiforov. Laborations-PM.| Code | Name | Scope | Grading scale |
|---|---|---|---|
| LAB1 | Laboratory Work | 1.5 credits | U, G |
| TEN1 | Written Examination | 4.5 credits | U, 3, 4, 5 |
See also course homepage for further practical course information.
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Course literature is preliminary.
Kompendium "Model Based Diagnosis of Technical Processes" av
Mattias Nyberg och Erik Frisk med tillhörande lektionskompendium.
Utdrag ur boken "Detection of abrupt changes" av Michele Basseville och Igor Nikiforov.
Laborations-PM.
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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X
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| 1.2 Fundamental engineering knowledge (G1X level) |
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X
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
|
X
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
|
X
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| 2.2 Experimentation, investigation, and knowledge discovery |
|
X
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X
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| 2.3 System thinking |
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X
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X
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| 2.4 Attitudes, thought, and learning |
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X
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| 2.5 Ethics, equity, and other responsibilities |
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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X
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| 3.2 Communications |
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X
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| 3.3 Communication in foreign languages |
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X
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
X
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
X
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X
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| 4.4 Designing |
X
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X
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| 4.5 Implementing |
X
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X
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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