Engines of Navy's MiG-29K fighter aircraft to be maintained using AI : The Tribune India

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Engines of Navy's MiG-29K fighter aircraft to be maintained using AI

Engines of Navy's MiG-29K fighter aircraft to be maintained using AI

Photo for representation. File photo



Tribune News Service

New Delhi, February 11

Engines of the fleet of MiG-29K fighter jets of the Navy will now be maintained by using artificial intelligence (AI).

Termed the health usage and monitoring system, it will use AI to reduce the time needed for data analysis, resulting in faster turnaround of aircraft and having better projection for preventive maintenance.

The AI-based programme has been included in the “launch of new technology” by Defence Research and Development Organisation (DRDO) at the biennial Aero India 2023, scheduled to be held at Air Force Station Yelahanka, Bengaluru, from February 13-17.

The MiG 29K jets take off and land on the two sea-going aircraft carriers of the Navy — the INS Vikramaditya and INS Vikrant.

Earlier this week, the Navy landed the LCA (Navy), the indigenous technology demonstrator fighter, on the deck of the INS Vikrant.

The landing was part of the development of a twin-engine deck-based fighter jet for the Navy. The LCA Navy is a single-engine jet and the under-development twin-engine variant is the one slated to be inducted.

At the Aero India 2023, the Navy helicopter, the ALH, will be part of the flying display while the maritime reconnaissance aircraft, the Boeing P8I will participate in the static display. In keeping with the emphasis on self-reliance, a customised graphic, compiled by Hindustan Aeronautics Limited (HAL), for use as a reference document for undertaking repairs of engines of MiG 29K aircraft, would be presented to the Indian Navy Chief.

The Navy is also conducting a seminar on the topic “Aero armament sustenance”. This will look at the way forward for sustenance of missiles held with the armed forces.

Data analysis

The health usage and monitoring system will use AI to reduce the time needed for data analysis, resulting in faster turnaround of aircraft and having better projection for preventive maintenance.

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