Failures within complex engineering systems, such as gas turbine engines, can have high-consequences in terms of safety.
In collaboration with Siemens Industrial Turbomachinery, this project focuses on predictive monitoring of gas turbine engines to continuously assess the health of the system, understanding and anticipating failures. We are developing probabilistic tools to dynamically quantify the risk of failure based on a limited number of sensors located within the engine.
This project is producing the knowledge and tools to deliver more efficient maintenance schedules, avoiding the consequences related to unexpected failures, and improving the resilience of these complex engineering structures for a safer society.
This project is developing as part of the Turing Summer Internship programme.
Part of The Alan Turing Institute-Lloyd’s Register Foundation Programme for Data-Centric Engineering.