DOIONLINE

DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-3089

Publish In
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN
Journal Home
Volume Issue
Issue
Volume-3, Issue-10  ( Oct, 2015 )
Paper Title
Condition Based Maintenance Using Artificial Intelligence For Structural Health Monitoring In Aviation Industry
Author Name
Raghunathan Abhilash, Mahesh M Sucheendran
Affilition
Wing Commander, IAF, Aerospace Engineering Department, Defence Institute of Advanced Technology, Pune, India Assistant Professor, Aerospace Engineering Department, Defence Institute of Advanced Technology, Pune, India
Pages
25-28
Abstract
This paper does a study on using structural health monitoring for condition based maintenance in aviation industry. Also, use of latest innovative advancements in Artificial Intelligence has been explained in this paper for dovetailing in the aviation sector. The Indian Air Force being the fourth largest Air force in the world has a large number of assets that is non indigenous. These highly expensive military aircraft, missiles, early warning systems, aerostats etc are susceptible to failure over a long run of operation or storage. Unfortunately we generally come to know about damage only after it has reached a significant level after which we are forced to further purchase spares or go for expensive refits. Either way, the optimum option of having early damage detection and to get the rectifications done under warranty period itself is not being implemented. In this scenario, the necessity of implementing structural health monitoring systems for the purpose of damage detection is quintessential. The results to a large extent need human interpretation for effective cost saving and to ensure condition based maintenance rather than schedule based maintenance. With the present pattern recognition systems that have been developed, it will be feasible to have an artificial intelligence program to scan through the large amount of data generated and give predicted results on impending failures. Keywords- Structural Health Monitoring, Condition Based Maintenance, Defect Investigation, Artificial Intelligence
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