DT-MAS architecture for smart maintenance of aircraft fuel distribution systems 核心 · 已核验

doi:10.17632/pbkn43bgjc.1

Project Goal: Develop a digital twin architecture using a multi-agent system and AI for smart maintenance of aircraft distribution systems. Objective: Build a reliable model that accurately represents the real system in an offline environment. Methodology : Developed a simulation based on an aircraft distribution system model, mimicking real system behavior. Created a dataset with four runs, five scenarios per run, and five operating points per scenario. Simulated healthy and faulty conditions using MATLAB-injected faults across various categories. Focused on four system components: hydraulic pump, tanks, engines, and pumps. Generated data for 11 healthy and faulty scenarios, including six fault types: Noise on instruments Abnormal instrument readings Minor service problems External leakage Parameter deviation Structural deficiency Features used for analysis: Pump flow for pumps Pump motor speed for hydraulic pumps Driver power Tank volume and temperature Expected Results: Compare performance of different asset health estimation models. Develop new predictive maintenance strategies. Predict and emulate complex aircraft behavior through multi-agent systems and AI.

落地页

https://doi.org/10.17632/pbkn43bgjc.1

许可证

CC-BY-4.0 (判读置信:inferred)

国内可访问性

国内直连:可达 (2026-07-11 检测) 代理通道:可达 (2026-07-11 检测)
检测口径:lychee 双通道单轮探测;「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。

设备类型

pump aero_engine

PHM 任务

health_state_assessment

故障工况