Model-Based and Data-Driven Fault Detection and Isolation

1. Generation of fault indicators

• Parity space approach to the generation of fault indicators (or residuals)

• Observer-based approach to residual generation

Both methods are developed in a deterministic and in a stochastic framework

2. Statistical change detection algorithms for decision system design

• Introduction for statistical process control

• Shewart and exponentially weighted moving average (EWMA) control chart

• Cumulative sum (CUSUM) algorithm and generalized likelihood ration algorithm

3. Change detection based on parameter estimation methods

• To master the principles of the design of fault detection and isolation systems, based on an mathematical model of the supervised process.

• To get acquainted with some on-line change detection algorithms and to be able to use them in a decision system

The lectures alternate with implementation of the methods on simple case studies using the MATLAB/SIMULINK software.

Contribution to the teaching profile

This teaching unit contributes to the following competences:

• In-depth knowledge and understanding of the advanced methods and theories to schematize and model complex problems or processes

• Reformulate complex engineering problems in order to solve them (simplifying assumptions, reducing complexity)

• Correctly report on research or design results in the form of a technical report or in the form of a scientific paper

• Present and defend results in a scientifically sound way, using contemporary communication tools, for a national as well as for an international professional or lay audience

• Work in an industrial environment with attention to safety, quality assurance, communication and reporting

• Think critically about and evaluate projects, systems and processes, particularly when based on incomplete, contradictory and/or redundant information

• A creative, problem-solving, result-driven and evidence-based attitude, aiming at innovation and applicability in industry and society

• A critical attitude towards one’s own results and those of others

• Consciousness of the ethical, social, environmental and economic context of his/her work and strives for sustainable solutions to engineering problems including safety and quality assurance aspects

• The flexibility and adaptability to work in an international and/or intercultural context

• An attitude of life-long learning as needed for the future development of his/her career

• Has an active knowledge of the theory and applications of electronics, information and communication technology, from component up to system level.

• Is able to analyse, specify, design, implement, test and evaluate individual electronic devices, components and algorithms, for signal-processing, communication and complex systems.

References, bibliography, and recommended reading

• M. Basseville et I.V. Nikiforov (1993). Detection of Abrupt Changes: Theory and Applications, Prentice-Hall.

• T. Soderstrom and P. Stoica (1989) System Identification. Prentice-Hall International.

• M. Blanke, M. Kinnaert, J. Lunze et M. Staroswiecki (2015) Diagnosis and Fault Tolerant Control, 3rd Edition, Springer.

Contacts

Service d'Automatique et d'Analyse des Systèmes, Buidling L, Door E, 2nd floor, email : michel.kinnaert@ulb.ac.be

Method(s) of evaluation

• Oral examination

Oral examination

Oral examination

Mark calculation method (including weighting of intermediary marks)

• Report on the practical work: 50%

• Oral examination :50%

Language(s) of evaluation

• english