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Model variables identification of a gas turbine using a subspace approach based on input/output data measurements

Control Theory and Technology 2021年第2期19卷 183-196页

作者： Hakim Bagua Ahmed Hafaifa Abdelhamid Iratni mouloud guemana Applied Automation and Industrial Diagnostics Laboratory Faculty of Science and TechnologyUniversity of Djelfa17000DjelfaAlgeria Gas Turbine Joint Research Team University of Djelfa17000DjelfaAlgeria Faculty of Science and Technology University of Bordj Bou Arreridj34000Bordj Bou ArreridjAlgeria

This paper deals with a state model identification of a gas turbine used for gas transport, using a subspace approach of the state space model. This method provides a reliable and robust state representation of the model, taking advantage of its benefits in the control, monitoring, and supervision of this machine. The model for each variable is set so that the state matrices associated with the gas turbine model are determined from their real input/output data. The comparison of the obtained identification results with those of the actual turbine operation serves to validate the proposed model in this work. This numerical algorithm of the subspace identification method is full of information and more accurate in terms of residual modeling error, and expresses a very high level of confidence in the identified turbine system dynamics. Hence, the controllability and observability tests of turbine operation for different input/output variables allowed to validate the real-time operating stability of the turbine.

关键词： System identification Subspace identification State space model Gas turbine N4SID algorithm

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Fault Detection and Isolation in Industrial Systems Based on Spectral Analysis Diagnosis

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Intelligent Control and Automation 2013年第1期4卷 36-41页

作者： Ahmed Hafaifa mouloud guemana Attia Daoudi Electrical Engineering Field Faculty of Science and Technology University of Djelfa DZ Djelfa Algeria Faculty of Science and Technology University of Medea Medea Algeria

The diagnoses in industrial systems represent an important economic objective in process industrial automation area. To guarantee the safety and the continuity in production exploitation and to record the useful events with the feedback experience for the curative maintenance. We propose in this work to examine and illustrate the application ability of the spectral analysis approach, in the area of fault detection and isolation industrial systems. In this work, we use a combined analysis diagram of time-frequency, in order to make this approach exploitable in the proposed supervision strategy with decision making module. The obtained results, show clearly how to guarantee a reliable and sure exploitation in industrial system, thus allowing better performances at the time of its exploitation on the supervision strategy.

关键词： Diagnosis Spectral Analyzes Faults Detection and Isolation Condition Monitoring

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