An Adaptive Digital Twin-Driven Model Based on Consumer Internet of Things to Ensure the Safe Operation of Aero-Engine

The aero-engine, often hailed as the manufacturing’s ‘crown jewel’ presents considerable complexity in its design, manufacturing, and maintenance. To enhance safety and efficacy of the aero-engine especially through comprehensive monitoring and systematic testing, in this paper, we propose an Adaptive Cycle Engine (ACE) model, i.e., a digital twin-driven aero-engine model based on the Consumer Internet of Things (CIoT), to safely model the aero-engine. The proposed ACE model can simulate all categories of the aero-engine’s working modes by setting the regulating components that control the opening and closing of bypass ducts, including mode selection valve and variable area bypass injector. Thus, each category of the working modes can be adaptively switched to enable aero-engine flexible adjustment and control. Furthermore, in the proposed ACE model, the common working conditions and the models of each mode are determined by the corresponding analysis of iterative variables and constraint equations for achieving the comprehensive performance analysis of steady state and transient conditions. Evaluation results demonstrate that the proposed ACE model can accurately simulate the operating state of the actual aero-engine, especially when it is compared with some of the famous commercial models. This work aim at promoting the development of consumer aero-engine.