Trend Regeneration of Health Parameter in a Developmental Aero Gas Turbine Engine
Usha Srinivasan1, K. R. Sudhindra2, N. Muthuveerappan3

1Usha Srinivasan*, Technical Director, Gas Turbine Research Establishment, Bangalore, India.
2Dr. K.R. Sudhindra, Associate Professor, Department of Electronics and Communication Engineering, university in Mysore, Karnataka, India.
3Dr. N. Muthuveerapan, Associate Director, Gas Turbine Research Establishment, Bangalore, India
Manuscript received on December 16, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 296-304 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8983019320/2020©BEIESP | DOI: 10.35940/ijitee.C8983.019320
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Abstract: Health parameters play a vital role in determining the remaining useful life of engine components, ensuring safe and confident continual test trials during the development phase. Although enough care is taken to obtain the health parameter data throughout the engine test duration, there are chances of missing out a few for reasons beyond control. This paper aims at providing a feasible solution to mitigate the data loss by regenerating the health parameter trend. Least square approximation, data mapping with threshold and interpolation techniques have been attempted via software development for trend regeneration. Two tier data fusion software has been developed to gather the data required for trend regeneration. Considering strain for case study, using actual test trial data, software has been verified. Interpolation technique with the least error emerged as an optimal choice and ensuring acceptance of its estimated strain trend resulted in its confident usage enabling intended progressive research. 
Keywords:  Interpolation, Least Square Method, Remaining Useful Life, Root Mean Square Error, Sensor Data Fusion
Scope of the Article:  Healthcare Informatics