Hidden fault diagnosis method of digital twin system for crane

作     者：Qi, Zhang Hui-Hui, Zhang Xing-Wang, Shen Jin-Song, Bao Dan, Zhang Sen, Wang 

作者机构：Donghua Univ Dept Mech Engn Shanghai 201620 Peoples R China Hong Kong Polytech Univ Dept Mech Engn Hong Kong Peoples R China Shanghai Baosight Software Co Ltd Shanghai 201203 Peoples R China 

出 版 物：《INTERNATIONAL JOURNAL OF MODELING SIMULATION AND SCIENTIFIC COMPUTING》 (Intl. J. Model. Simul. Sci. Comput.)

年 卷 期：2025年第16卷第1期

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Digital twin stacked denoising auto-encoder multi-class support vector machine fuzzy Bayesian network 

摘      要：The traditional fault diagnosis approach for cranes often results in unclear control status, protracted fault location times, prolonged equipment downtime, and other related challenges. To address these issues, this paper proposes embedding the stacked denoising auto-encoder, multi-class support vector machine, and fuzzy Bayesian network (SDAE-MCSVM-FBN (SMF)) hidden cascade fault diagnosis method into a digital twin model of the crane. The approach utilizes the digital twin to monitor the crane s state and identify virtual environment faults to make decisions to reduce the direct operation of complex equipment and enhance operational efficiency. This paper first constructs a digital twin model of the crane to describe its composition and interaction behavior within the system. Next, it solves the hidden cascade faults in cranes using the SMF method. Finally, this approach develops a prototype system for a digital twin of cranes with an example in a large steel mill used for verification and analysis purposes. Experimental results demonstrate that compared with traditional manual inspection methods, this paper s proposed hidden cascade fault method reduces repair time by 24.5%-32.8% while decreasing downtime by 20.5%-32.4%. The outcome highlights the effectiveness of our diagnostic approach and demonstrates digital twin technology can minimize frequent maintenance requirements by personnel while protecting crane service life overall.