首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics
【2h】

State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics

机译:从动态转子轴承系统收集的非线性振动响应的状态空间公式:将轴承诊断扩展到轴承预测

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Bearings are widely used in various industries to support rotating shafts. Their failures accelerate failures of other adjacent components and may cause unexpected machine breakdowns. In recent years, nonlinear vibration responses collected from a dynamic rotor-bearing system have been widely analyzed for bearing diagnostics. Numerous methods have been proposed to identify different bearing faults. However, these methods are unable to predict the future health conditions of bearings. To extend bearing diagnostics to bearing prognostics, this paper reports the design of a state space formulation of nonlinear vibration responses collected from a dynamic rotor-bearing system in order to intelligently predict bearing remaining useful life (RUL). Firstly, analyses of nonlinear vibration responses were conducted to construct a bearing health indicator (BHI) so as to assess the current bearing health condition. Secondly, a state space model of the BHI was developed to mathematically track the health evolution of the BHI. Thirdly, unscented particle filtering was used to predict bearing RUL. Lastly, a new bearing acceleration life testing setup was designed to collect natural bearing degradation data, which were used to validate the effectiveness of the proposed bearing prognostic method. Results show that the prediction accuracy of the proposed bearing prognostic method is promising and the proposed bearing prognostic method is able to reflect future bearing health conditions.
机译:轴承广泛用于各种行业,以支撑旋转轴。它们的故障会加速其他相邻组件的故障,并可能导致意外的机器故障。近年来,从动态转子轴承系统收集的非线性振动响应已被广泛地用于轴承诊断。已经提出了许多方法来识别不同的轴承故障。但是,这些方法无法预测轴承的未来健康状况。为了将轴承诊断扩展到轴承预测,本文报告了从动态转子轴承系统收集的非线性振动响应的状态空间公式设计,以便智能地预测轴承的剩余使用寿命(RUL)。首先,对非线性振动响应进行分析,以构建轴承健康指标(BHI),以评估当前的轴承健康状况。其次,开发了BHI的状态空间模型,以数学方式跟踪BHI的健康发展。第三,无味粒子滤波被用于预测轴承的RUL。最后,设计了一种新的轴承加速寿命测试设置,以收集自然的轴承退化数据,这些数据用于验证所提出的轴承预测方法的有效性。结果表明,所提出的轴承预测方法的预测准确性是有希望的,并且所提出的轴承预测方法能够反映未来的轴承健康状况。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号