
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>Fault Detection and Isolation Based on Dynamic Observers Applied to Gas Turbine Control Sensors
doi: 10.1115/98-gt-158
handle: 11380/1249151 , 11380/1249152 , 11392/1195644
In order to prevent machine malfunctions and to determine the machine operating state, it is necessary to use correct measurements from actual system inputs and outputs. This requires the use of techniques for the detection and isolation of sensor faults. In this paper an approach based on analytical redundancy which uses dynamic observers is suggested to solve the sensor fault detection and isolation problem for a single-shaft industrial gas turbine. The proposed technique requires the generation of classical residual functions obtained with different observer configurations. The diagnosis is performed by checking fluctuations of these residuals caused by faults.
machine malfunction monitoring; fault detection and isolation; sensor faults; analytical redundancy; dynamic observers; single-shaft industrial gas turbine.
machine malfunction monitoring; fault detection and isolation; sensor faults; analytical redundancy; dynamic observers; single-shaft industrial gas turbine.
