Article | REF: MT9134 V1

Data-based methods for fault diagnosis and prognosis – State of the art

Author: Gilles ZWINGELSTEIN

Publication date: August 10, 2020

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3. Application examples

To illustrate data-driven diagnostic and prognostic approaches, this section presents three examples of experiments on industrial equipment: an aircraft engine, a lithium battery and a wind turbine speed multiplier.

3.1 Aircraft reactor

The diagnosis and prognosis of failures in the aeronautics industry is a critical issue, not only because of the economic stakes involved, but also because of the safety of passengers. In an aircraft, the engines and their equipment are the most important systems, providing the power needed for propulsion. Aircraft maintenance is subject to regulations, and airlines are looking for ways to avoid and prevent failures, to improve engine availability and optimize maintenance costs.

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