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滚动轴承振动性能因素分析的定性融合理论

Qualitative Fusion Theory for Factors Analysis on Vibration Performance of Rolling Bearings
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摘要 滚动轴承振动性能受复杂因素影响属于乏信息范畴,以灰色定性融合方法分析滚动轴承振动因素为例,提出定性融合理论解决滚动轴承的乏信息问题,定性融合理论可以融合方法的优点扩充信息量,从不同侧面揭示事物的信息,通过融合信息特征,推断其总体特征,为滚动轴承的制造、性能分析及选择提供可靠依据。 The vibration performance of rolling bearings affected by complex factors belongs to poor information category. The vibration factors of rolling bearings are analyzed by using grey qualitative fusion method,and the qualitative fusion theory is proposed to solve poor information problem about rolling bearings. The results show that the qualitative fusion theory is able to fuse advantages of method,expanding amount of information and discovering information of things from different aspects. The overall characteristics is inferred by fusing information characteristics,which provides reliable basis for manufacture,performance analysis and selection of rolling bearings.
出处 《轴承》 北大核心 2016年第8期27-35,共9页 Bearing
基金 国家自然科学基金项目(51475144)
关键词 圆锥滚子轴承 定性融合 定量融合 本征融合 参数非参数融合 tapered roller bearing qualitative fusion quantitative fusion intrinsic fusion parameter-nonparametric fusion
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参考文献12

  • 1夏新涛,陈晓阳,张永振,王中宇,孙立明.基于乏信息的滚动轴承振动与噪声的模糊预报[J].吉林大学学报(工学版),2007,37(6):1341-1345. 被引量:6
  • 2Srividya A,Verma A K,Sreejith B. Automated Diagnosisof Rolling Element Bearing Defects Using Time -Domain Features and Neural Networks[J] . InternationalJournal of Mining, Reclamation and Environment,2009, 23(3) : 363 -366.
  • 3Castejon C, Lara 0 ,Carcia - Prada J C. AutomatedDiagnosis of Rolling Bearings Using MRA and NeuralNetworks [J]. Mechanical Systems and Signal Processing,2010, 24(1) : 289 -199.
  • 4Antoni J. Cyclic Spectral Analysis of Rolling - ElementBearing Signal : Facts and Fictions [J]. Journal ofSound and Vibration, 2007, 304: 497 -529.
  • 5熊卫华,赵光宙.基于希尔伯特-黄变换的轴承振动特性分析[J].传感技术学报,2006,19(3):655-657. 被引量:14
  • 6夏新涛,陈晓阳,张永振,王中宇,朱孔敏,李建华.航天轴承摩擦力矩的最大熵概率分布与bootstrap推断[J].宇航学报,2007,28(5):1395-1400. 被引量:18
  • 7Banda N. Noise and Vibration in Rolling Bearings[J] .Journal of Japanese Society of Tribologists, 2003, 48(1) . 43 -48.
  • 8王平,廖明夫.滚动轴承故障诊断的自适应共振解调技术[J].航空动力学报,2005,20(4):606-612. 被引量:57
  • 9Arenas J P. Enhancing the Vibration Signal from RollingContact Bearing Using an Adaptive Closed - LoopFeed - Back Control for Wavelet De - Noising [J].Journal of Mechanical Engineering, 2005,51(4) : 184-193.
  • 10Estocq P, Bolaers F, Dro J P. Method of De - Noisingby Spectral Subtraction Applied to the Detection of RollingBearing Defects [J]. Journal of Vibration and Control,2006, 12(2) : 197 -211.

二级参考文献36

  • 1马东雄,陆爽,张子达,张永明.现代信号分析在滚动轴承故障诊断中的应用[J].哈尔滨轴承,2004,25(4):7-10. 被引量:4
  • 2卢艳辉,尹泽勇.基于小波包分析方法的航空发动机滚动轴承故障诊断[J].燃气涡轮试验与研究,2005,18(1):35-37. 被引量:9
  • 3王家忠,王龙山,李国发,丁宁.外圆纵向磨削表面粗糙度的模糊预测与控制[J].吉林大学学报(工学版),2005,35(4):386-390. 被引量:7
  • 4[1]Tallian L D,Gustafsson O G.Progress in Rolling Bearing Vibration Research and Tontrol[J].ASLE Trans,1965,8(3):195-207.
  • 5[3]Oswald B.Noise and Vibrational Behaviour of Rolling Bearing,Ball and Roller Engineering [J].Industrial Engineering(FAG),1989,28(2):4-11.
  • 6[7]Tandon N,Choudhury A.A Review of Vibration and Acoustic Measurement Methods for the Detection of Defects in Rolling Element Bearings [J].Tribology International,1999,32(1):469-480.
  • 7[9]Zandbergen T,Nijen G.Less Noise & Vibration by Proper Rolling Bearing Accuracy,Design and Installation [J].Shock and Vibration Digest,2000,32(1):40-44.
  • 8[10]Tandon N,Choudhury A.Theoretical Model to Predict the Vibration Response of Rolling Bearings in a Rotor Bearing System to Distributed Defects under Radial Load[J].Journal of Tribology,Transactions of the ASME,2000,122(3):609-615.
  • 9[11]Deng Julong.Introduction to Grey System Theory[J].The Journal of Grey System.1989,1(1):1-24.
  • 10[1]Gan K G,Zaitov L M.Investigation into the dependence of the friction moment of high-speed self-lubrication ball bearings on the duration of work,rotational speed and load[J].Soviet Engineering Research,1990,10(2):41-46

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