Diagnosis, isolation and corrective action of incipient faults in a developmental Aero Gas Turbine Engine, mandates advanced warning of the emerging faults by apt and timely degradation monitoring in order to mitigate catastrophic failure. This calls for cautious performance monitoring during the test runs by instrumenting the engine under test with multiple sensors to acquire the physical parameters like temperature, pressure, flow and speed which are indicative of the engine degradation. Sensor reliability is critical to engine control and performance monitoring. Sensor data which serves as the primary key for assessing the engine behaviour needs to be validated before its use in determining the degradation. Particularly in a developmental engine under test, the accuracy and reliability of measurements creates the basis for understanding the engine behaviour, in order to evaluate its performance. This paper targets to develop validation tool to ensure that only trusted sensor measurements are used for engine performance computation by weeding out the erroneous data. The pre-processing of data to ensure its accuracy also serves as a “need for maintenance indicator” to warn the operator for sensor breakdowns, wearing or deterioration and detect calibration needs. Development and validation of the LabVIEW based “Sensor Data Validation Tool (SDVT)” using the actual test run data constitutes the main body of this paper along with concluding remarks which brings out the validation results and the required maintenance action.

This content is only available via PDF.
You do not currently have access to this content.