Intelligent marine engines health assessment system based on digital twins and data driven models (i-HEATS)

i-HEATS项目旨在开发基于第一原理数字孪生模型和数据驱动模型的智能发动机状态监测和诊断系统。该项目直接应用于船舶和陆地发电厂，致力于为内燃机的状态监测提供一个游戏规则。I4.0技术将用于智能工具的开发，包括数字孪生、深度学习、传感器融合和云计算。该项目的新领域包括使用独特的定制数据采集系统来测量瞬时轴扭矩，并在本地和云上存储和分析采集的数据（边缘/云计算），基于第一原理的发动机数字孪生模型，集成了热力学和曲轴/轴系系统动力学模型，基于深度学习技术的数据驱动模型补充了数字孪生模型，以提供实时预测能力，开发了数据驱动模型，以识别和纠正测量参数的关键传感器的不准确性（传感器融合），数据驱动算法，以监测发动机状况，并根据测量的瞬时扭矩和其他关键参数提供诊断。原型i-HEATS系统将通过将上述工具与适当的硬件和用户界面相结合来开发和测试，随后将在实验室和全尺寸条件下进行广泛测试，从而产生商业前版本。开发的系统将能够监测发动机状况，并根据与性能、维护、排放和运营成本相关的指标提供及时的诊断。i-HEATS系统将用于船舶动力装置使用的两种典型发动机类型。该项目提供了一个先进和创新的发动机状态监测和诊断系统，在燃油效率、减少环境足迹、提高发动机可靠性以及减少运行燃油和维护成本方面具有切实的好处。i-HEATS项目的进步和创新将为未来智能船舶系统的发展铺平道路。

The i-HEATS project aims to develop an intelligent engine condition monitoring and diagnostics system based on first-principles digital twins and data-driven models. The project has direct application to ship and land power plants, endeavouring to provide a game-change in the condition monitoring of internal combustion engines. I4.0 technologies will be employed leading to the development of intelligent tools, including digital twins, deep learning, sensors fusion, and cloud computing.The novel areas of the project include the use of a unique, custom made, data acquisition system for measuring the instantaneous shaft torque, storage and analysis of acquired data locally and on cloud (edge/cloud computing), a first-principle based engine digital twin integrating thermodynamic and crankshaft/shafting system dynamics models, data-driven models based on deep learning techniques complementing the digital twins to offer real-time predictive capabilities, developed data-driven model to identify and rectify inaccuracies of critical sensors of the measured parameters (sensor fusion), data-driven algorithms to monitor engine condition and provide diagnostics based on the measured instantaneous torque and other critical parameters. The prototype i-HEATS system will be developed and tested by integrating the above tools with appropriate hardware and user interfaces and subsequently will be extensively tested in lab and full-scale conditions leading to a pre-commercial version. The developed system will be capable of monitoring engine condition and providing timely diagnostics based on indicators relevant to performance, maintenance, emissions, and operating costs. The i-HEATS system will be implemented for the two typical engine types used for ship power plants. This project provides a sophisticated and innovative engine condition monitoring and diagnostics system with tangible benefits on fuel efficiency, environmental footprint reduction, engine reliability improvement, and the reduction of the operating fuel and the maintenance costs. The i-HEATS project advances and innovation will pave the way towards the development of future smart ship systems.