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轴向柱塞泵智能化关键技术研究进展及发展趋势

Research Status and Development Trends on Intelligent Key Technology of the Axial Piston Pump
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摘要 轴向柱塞泵是航空航天、远洋船舶、工程机械等高端装备液压系统的“心脏”,为液压系统输送具有稳定压力、流量的传动“血液”。轴向柱塞泵的可靠性和安全性直接影响液压系统甚至整机的性能,因此,利用智能化技术对其实现预测性维护是近年来的研究热点。同时,装备无人化和智能化的发展趋势也使得轴向柱塞泵的智能化技术受到重点关注。为探明轴向柱塞泵智能化技术的发展方向,给出其高质量发展的可行路径,从智能状态监测、智能故障诊断、智能寿命预测和智能决策调控四个方面系统性地综述轴向柱塞泵智能化技术的发展历程和研究现状。探讨轴向柱塞泵智能化关键技术的现有问题及难点,总结智能化关键技术发展面临的挑战,并对未来发展趋势进行展望。 Axial piston pumps are the heart of the hydraulic system of aerospace,ocean ships,engineering machinery and other high-end equipment.They deliver transmission blood with stable pressure and flow to the hydraulic system.The reliability and safety of axial piston pumps have direct affects on the performance of the hydraulic system and even the complete machine.Therefore,utilizing intelligent technology to achieve predictive maintenance of axial piston pumps has been a research hotspot in recent years.At the same time,the development of unmanned and intelligent equipment has also emphasized the intelligent technology of axial piston pumps.To explore the development direction of the intelligent technology for axial piston pumps and provide a feasible path for the high-quality development,this study reviews the development history and research status of the intelligent technology of axial piston pumps from four aspects,namely,intelligent condition monitoring,intelligent fault diagnosis,intelligent life prediction and intelligent decision regulation.The existing problems and difficulties of the intelligent technologies for axial piston pumps are explored,the challenges of the existing intelligent technologies are summarized,and the future development trends are forecasted.
作者 张军辉 刘施镐 徐兵 黄伟迪 吕飞 黄晓琛 ZHANG Junhui;LIU Shihao;XU Bing;HUANG Weidi;LYU Fei;HUANG Xiaochen(State Key Lab of Fluid Power&Mechatronic Systems,Zhejiang University,Hangzhou 310027)
出处 《机械工程学报》 EI CAS CSCD 北大核心 2024年第4期32-49,共18页 Journal of Mechanical Engineering
基金 国家自然科学基金重点(51835009) 国家自然科学基金青年(52105075,52305075) 浙江省重点研发计划(2022C01039)资助项目。
关键词 轴向柱塞泵 智能化 故障诊断 寿命预测 状态监测 axial piston pump intelligent technology fault diagnosis remain useful life prediction key state monitoring
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  • 1庄解忧.世界上第一次工业革命的经济社会影响[J].厦门大学学报(哲学社会科学版),1985,35(4):54-60. 被引量:14
  • 2Wang Wenchuan, Chau Kwok-Wing, Cheng Chuntian, et al. A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series [ J ]. Journal of Hydrology, 2009,374 ( 3 - 4 ) : 294 - 306.
  • 3Hippert H S, Pedreira C E, Souza R C. Neural networks for short-term load forecasting: a review and evaluation [J]. Power Systems, 2001,16( 1 ) :44 - 55.
  • 4Cristianini N, Shawe-Taylor J. An introduction to support vector machines and other kernel-based learning method [ M ]. Beijing: China Machine Press,2005 : 1 - 124.
  • 5Peng Xinjun,Wang Yifei. A normal least squares support vector machine(NLS-SVM) and its learning algorithm [J]. Neurocomputing, 2009,72( 16 - 18) :3734 -3741.
  • 6Li Lin, Ji Hongbing. Signal feature extraction based on an improved EMD method [ J ]. Measurement, 2009,42 ( 5 ) : 796 - 803.
  • 7Osowski S, Garanty K. Forecasting of the daily meteorological pollution using wavelets and support vector machine [J]. Engineering Applications of Artificial Intelligence, 2007,20 ( 6 ) : 745 - 755.
  • 8Li Hongxing, Xu Li D. Feature space theory: a mathematical foundation for data mining [ J ]. Knowledge-Based Systems, 2001,14(5 -6) :253 -257.
  • 9黄平,J Tribology,1992年,114卷,1期,42页
  • 10Wu S F,1990年

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