航空学报2026，Vol.47Issue(8)：321-346,26.DOI:10.7527/S1000-6893.2025.32663
基于层级数字孪生的机电系统故障数据生成
Fault data generation for electromechanical systems based on hierarchical Digital Twin
摘要
Abstract
Multi-coupled Electromechanical Systems(MES)are the important component of modern industry,their stable operation heavily relies on effective fault diagnosis.With the development of artificial intelligence technique,suf-ficient fault data plays an important role in MES's fault diagnosis,while is quite difficult to obtain in practices.In this re-gard,there is urgent need to generate the virtual fault data through the system simulation and improve the fault diagno-sis performance,where the Digital Twin technique with superior virtual mapping capabilities for entity characteristics provides the potential opportunity.However,there is a lack of an effective method that can decouple the complicated MES entity and construct its full-system fault Digital Twin model.Aiming at the above target,we propose a hierarchical collaborative Digital Twin modeling method to implement the fault data generation.In order to structurally describe the complicated entity,MES is decoupled and identified as the multidimensional and multimodal triplet representations,namely,element,relationship,and data.Given the element and data,the hierarchical data-model combined tech-nique is proposed to develop the four-level(space,behavior,process,and status)sub-Digital Twin models,to well balance the modeling adaptability and modeling precision during the local virtualization of MES.Thanks for the pro-posed collaborative orchestration algorithm,these heterogeneous sub-Digital Twin models are further interacted and integrated into the full-system Digital Twin according to the aforementioned relationship representation,which jointly constitutes the global mirror of the MES entity under various fault modes.We conducted the experiments to validate the proposed method by using a multi-coupled electromechanical fault test bench.The experimental results show that our method improved the accuracy of fault diagnosis by an average of 11.95%,which demonstrates its superiority in the fault data generation for the complicated entity such as MES.关键词
多耦合机电系统/数字孪生/数据生成/故障诊断/协同编排算法Key words
multi-coupled electromechanical systems/Digital Twin/data generation/fault diagnosis/collaborative orchestration algorithm分类
航空航天引用本文复制引用
丁宇,宁国澳,靳凯新,孙博,李淮,苏铉元..基于层级数字孪生的机电系统故障数据生成[J].航空学报,2026,47(8):321-346,26.基金项目
科技创新2030(2021ZD0201300) STI 2030—Major Projects(2021ZD0201300) （2021ZD0201300）
