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COMPUTER-AIDED BLOCK ASSEMBLY PROCESS PLANNING IN SHIPBUILD-ING BASED ON rule-reasoning

Chinese Journal of Mechanical Engineering 2008年第2期21卷 99-103页

作者： ZHANG Zhiying LI Zhen JIANG Zhibin School of Mechanical Engineering Tongji University Shanghai 200092 China State Key Laboratory of Estuarine and Coastal Science East China Normal University Shanghai 200062 China School of Mechanical Engineering Shanghai Jiaotong University Shanghai 200240 China

Computer-aided block assembly process planning based on rule-reasoning are developed in order to improve the assembly efficiency and implement the automated block assembly process planning generation in shipbuilding. First, weighted directed liaison graph （WDLG） is proposed to represent the model of block assembly process according to the characteristics of assembly relation, and edge list （EL） is used to describe assembly sequences. Shapes and assembly attributes of block parts are analyzed to determine the assembly position and matched parts of parts used frequently. Then, a series of assembly rules are generalized, and assembly sequences for block are obtained by means of rule reasoning. Final, a prototype system of computer-aided block assembly process planning is built. The system has been tested on actual block, and the results were found to be quite efficiency. Meanwhile, the fundament for the automation of block assembly process generation and integration with other systems is established.

关键词： Assembly process planning rule reasoning Shipbuilding

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Attribute-driven Fuzzy Fault Tree Model for Adaptive Lubricant Failure Diagnosis

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Journal of Dynamics, Monitoring and Diagnostics 2024年第3期3卷 207-215页

作者： Shuo Wang Yishi Chang Tonghai Wu Zhidong Han Yaguo Lei Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi’an Jiaotong UniversityXi’an710049ShaanxiChina

Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in ***,the accuracy of traditional end-to-end diagnosis models is often limited by the inconsistency and random fluctuations in multiple monitoring *** address this,an attribute-driven adaptive diagnosis method is developed,involving three attributes:physicochemical,contamination,and ***,a fuzzy fault tree(termed FFT)-based model is constructed containing the logic correlations from monitoring indicators to attributes and to lubricant *** particular,inference rules are integrated to mitigate conflicts arising from the reverse degradation of multiple *** this model,the lubricant conditions can be accurately assessed through rule-based ***,to enhance its intelligence,the model is dynamically optimized with lubricant analysis knowledge and monitoring *** verification,the developed model is tested with lubricant samples from both the fatigue experiment and actual *** experiments reveal that the proposed model can improve the lubricant diagnosis accuracy from 73.4%to 92.6%compared with the existing *** for the engine lubricant test,a high accuracy of 90%was achieved.

关键词： lubricant failure diagnosis fuzzy fault tree attribute guidance rule reasoning

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