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- 저자 : Wenliao Du (검색결과 2 건)
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Hongchao Wang,Zhiqiang Guo,Wenliao Du 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.8
The conventional signal processing based methods are difficult to achieve satisfactory results for rolling element bearings (REBs)’ weak fault due to the serious influence of interference signal. Intelligent classification technology and the arising popular monitoring technology-performance evaluation assessment (PDA) are the research hotspots of fault diagnosis of REB in recent years, which could resolve the above problem to some extent. Especially the latter could reflect the operating status of the equipment more comprehensively. Effective feature extraction basing on signal processing methods and intelligent algorithm are the two key aspects for the above two technologies which will determine their effectiveness to great extent. Multifractal detrended fluctuation analyses (MDFA) is an effective non-stationary signal processing method which could reveal the multifractality buried in nonlinear and nonstationary vibration signals of REB, and continuous hidden markov model (CHMM) is a mature intelligent algorithm with solid theoretical basis and rich mathematical structure. So a diagnosis method basing on combination of MDFA with CHMM is proposed in the paper, and it could deal with both fault classification and PDA tasks for the diagnosis of REBs. Effectiveness of the proposed method is validated by two different diagnosis experiments, one for fault classification and another for lifecycle performance evaluation of REBs. Compared to state-of-the-art peer methods, the proposed method has the best performance when dealing with fault diagnosis tasks for REBs.
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Guizhong Xie,Shixin Zhang,Hao Li,Liangwen Wang,Wenliao Du,Chongmao Zhao,Hangqi Jia 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.10
A double-layer optimization method for the forging process parameters of a hinge beam structure and the design of intermediate billet structure is proposed. First, a primary optimization system for the forging process parameters of hinge beam was established based on orthogonal experiments and range analysis method, and the optimal combination of forging process parameters was selected. On this basis, a mathematical model of the secondary optimization of the final forging of the hinge beam was established. Through radial basis function (RBF) agent model and multi-island genetic algorithm, the secondary optimization of intermediate billet structure of hinge beam was carried out, which improved the grain refinement degree of final forging and reduced the forming load required for forging. Through numerical simulation and optimization design of forging process, the quality and performance of final forging of hinge beam were improved, which has certain guiding significance for the actual production of hinge beam.
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