The conceptual design of an aero gas turbine engine is quite complex involving many engineering disciplines such as aerothermodynamics, heat transfer, material technology, component design, engine controls to arrive at the engine configuration. The key emerging technologies for these propulsion systems are the increased component efficiencies through active control, advanced diagnostics and prognostics integrated with intelligent control and distributed control with smart sensors and actuators. All these technologies should emphasize overall engine gas path performance. The present trend is to revolutionize the aero engine industry by harnessing the Internet of Things (IoT).

The analytic software in an aero engine enables engineers to carry out analysis of voluminous data in the shortest time. In other words, the analysis which, used to take months can be carried out in minutes. Today in the aero engine industry, the emphasis is to improve the component efficiencies through online monitoring of engine data and exhaustive usage of advanced diagnostics and prognostics. The Distributed Control System with smart sensors and actuators as against the integrated control system is an advanced area of research and development.

Active Controlled Components will mitigate the challenges related to:

The effectiveness of active control has been demonstrated in lab-scale tests; however, significant R&D is required to implement these technologies. It may be emphasized that, in particular, high temperature sensors and actuators are the need of the hour.

Advanced diagnostics and prognostics

Advanced model-based control architecture overcomes the limitations of state-of-the-art engine control and provides the potential of virtual sensors. In order to adapt the engine control parameters to actual conditions and to individual engines, Tracking Filters are employed. In the existing scenario the Engine Health Monitoring (EHM) units are stand-alone units. The technology to integrate both control and monitoring is emerging. One of the challenges is the Engine Certification.

Adaptive models are opening up the possibility of adapting the control logic to maintain desired performance due to engine degradation.

Improved and new sensors are required to allow:

Having seen the importance of active control of engine components and advanced diagnostic and prognostic requirements, it will be highly useful and cost effective if these analyses could be done in real time.

In all the above the requirement is to replace the after-the fact analysis with real time analysis to drive faster and better decisions. In other words, one has to process the data as it comes in. Here IoT becomes an effective tool to achieve this.

Since IoT catches things as they are progressing instead of waiting to analyse the data afterwards, this real time tracking of data can be used to optimize

This can result in revolutionizing flight efficiency and profitability. In this context QuEST Global is engaged in the following areas among other things:

Using IoT QuEST is open to contribute in:


The author is the Director of Technology Excellence Group at QuEST Global

Sundararajan V
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