To decrease breakdown time and improve machine operation reliability,accurate residual useful life(RUL) prediction has been playing a critical role in condition based monitoring.A data fusion method was proposed to ac...To decrease breakdown time and improve machine operation reliability,accurate residual useful life(RUL) prediction has been playing a critical role in condition based monitoring.A data fusion method was proposed to achieve online RUL prediction of slewing bearings,which consisted of a reliability based RUL prediction model and a data driven failure rate(FR) estimation model.Firstly,an RUL prediction model was developed based on modified Weibull distribution to build the relationship between RUL and FR.Secondly,principal component analysis(PCA) was introduced to process multi-dimensional life-cycle vibration signals,and continuous squared prediction error(CSPE) and its time-domain features were employed as equipment performance degradation features.Afterwards,an FR estimation model was established on basis of the degradation features and relevant FRs using simplified fuzzy adaptive resonance theory map(SFAM) neural network.Consequently,real-time FR of equipment can be obtained through FR estimation model,and then accurate RUL can be calculated through the RUL prediction model.Results of a slewing bearing life test show that CSPE is an effective indicator of performance degradation process of slewing bearings,and that by combining actual load condition and real-time monitored data,the calculation time is reduced by 87.3%and the accuracy is increased by 0.11%,which provides a potential for online RUL prediction of slewing bearings and other various machineries.展开更多
A calculation method of fatigue life for slewing bearings under combined radial, axial and tilting moment loads was proposed. Single row four-point contact ball slewing bearing being used as a case, the statics model ...A calculation method of fatigue life for slewing bearings under combined radial, axial and tilting moment loads was proposed. Single row four-point contact ball slewing bearing being used as a case, the statics model of the slewing bearing was established and a set of equilibrium equations were obtained. By solving the equilibrium equatioas, the rolling element loads were obtained and the equivalent rolling element loads were calculated further. By using the geometrical parameters of the bearing, the rating rolling element loads were calculated, and the fa- tigue life of the bearing was calculated by using the rating rolling element loads and the equivalent rolling element loads. A calculation example shows the feasibility of the proposed method.展开更多
Bearing condition monitoring and fault diagnosis (CMFD) can investigate bearing faults in the early stages, preventing the subsequent impacts of machine bearing failures effectively. CMFD for low-speed, non-continuous...Bearing condition monitoring and fault diagnosis (CMFD) can investigate bearing faults in the early stages, preventing the subsequent impacts of machine bearing failures effectively. CMFD for low-speed, non-continuous operation bearings, such as yaw bearings and pitch bearings in wind turbines, and rotating support bearings in space launch towers, presents more challenges compared to continuous rolling bearings. Firstly, these bearings have very slow speeds, resulting in weak collected fault signals that are heavily masked by severe noise interference. Secondly, their limited rotational angles during operation lead to a restricted number of fault signals. Lastly, the interference from deceleration and direction-changing impact signals significantly affects fault impact signals. To address these challenges, this paper proposes a method for extracting fault features in low-speed reciprocating bearings based on short signal segmentation and modulation signal bispectrum (MSB) slicing. This method initially separates short signals corresponding to individual cycles from the vibration signals based on encoder signals. Subsequently, MSB analysis is performed on each short signal to generate MSB carrier-slice spectra. The optimal carrier frequency and its corresponding modulation signal slice spectrum are determined based on the carrier-slice spectra. Finally, the MSB modulation signal slice spectra of the short signal set are averaged to obtain the overall average feature of the sliced spectra.展开更多
内齿式回转支承兼有滚动轴承的回转支承特点和齿轮啮合传动特点,在联合载荷作用下其动态性能的影响因素众多,容易出现轮齿磨损或断齿、套圈滚道磨损和运行精度变差等问题。综合考虑钢球与内外套圈滚道、保持架兜孔的动态接触作用及内齿...内齿式回转支承兼有滚动轴承的回转支承特点和齿轮啮合传动特点,在联合载荷作用下其动态性能的影响因素众多,容易出现轮齿磨损或断齿、套圈滚道磨损和运行精度变差等问题。综合考虑钢球与内外套圈滚道、保持架兜孔的动态接触作用及内齿圈轮齿间的啮合传动作用,建立了内齿式回转支承参数化多体接触动力学模型。分析了沟道曲率半径、保持架兜孔孔径、初始接触角和轮齿变位系数等关键设计参数对回转支承齿轮啮合力、1号钢球与N1滚道的接触力、内齿圈质心轴向和径向振动位移的影响规律。在此基础上,采用试验设计(design of experiment,DOE)方法,对内齿式回转支承的关键设计参数进行全因子试验设计及计算,获得了多参数影响下回转支承的动态性能。结合线性加权法,运用统一量纲法和权系数法构造新的多目标优化函数,提出了回转支承动态性能的多变量多目标优化设计方法,得到回转支承的轮齿啮合力下降了49.27%,1号钢球与N1滚道的接触力下降了29.6%,内齿圈质心轴向振动位移减小了5.41%,内齿圈质心径向位移减小了15.88%,回转支承的性能得到了优化。研究结果为回转支承的动态设计提供了参考。展开更多
基金Projects(51375222,51175242)supported by the National Natural Science Foundation of China
文摘To decrease breakdown time and improve machine operation reliability,accurate residual useful life(RUL) prediction has been playing a critical role in condition based monitoring.A data fusion method was proposed to achieve online RUL prediction of slewing bearings,which consisted of a reliability based RUL prediction model and a data driven failure rate(FR) estimation model.Firstly,an RUL prediction model was developed based on modified Weibull distribution to build the relationship between RUL and FR.Secondly,principal component analysis(PCA) was introduced to process multi-dimensional life-cycle vibration signals,and continuous squared prediction error(CSPE) and its time-domain features were employed as equipment performance degradation features.Afterwards,an FR estimation model was established on basis of the degradation features and relevant FRs using simplified fuzzy adaptive resonance theory map(SFAM) neural network.Consequently,real-time FR of equipment can be obtained through FR estimation model,and then accurate RUL can be calculated through the RUL prediction model.Results of a slewing bearing life test show that CSPE is an effective indicator of performance degradation process of slewing bearings,and that by combining actual load condition and real-time monitored data,the calculation time is reduced by 87.3%and the accuracy is increased by 0.11%,which provides a potential for online RUL prediction of slewing bearings and other various machineries.
文摘A calculation method of fatigue life for slewing bearings under combined radial, axial and tilting moment loads was proposed. Single row four-point contact ball slewing bearing being used as a case, the statics model of the slewing bearing was established and a set of equilibrium equations were obtained. By solving the equilibrium equatioas, the rolling element loads were obtained and the equivalent rolling element loads were calculated further. By using the geometrical parameters of the bearing, the rating rolling element loads were calculated, and the fa- tigue life of the bearing was calculated by using the rating rolling element loads and the equivalent rolling element loads. A calculation example shows the feasibility of the proposed method.
文摘Bearing condition monitoring and fault diagnosis (CMFD) can investigate bearing faults in the early stages, preventing the subsequent impacts of machine bearing failures effectively. CMFD for low-speed, non-continuous operation bearings, such as yaw bearings and pitch bearings in wind turbines, and rotating support bearings in space launch towers, presents more challenges compared to continuous rolling bearings. Firstly, these bearings have very slow speeds, resulting in weak collected fault signals that are heavily masked by severe noise interference. Secondly, their limited rotational angles during operation lead to a restricted number of fault signals. Lastly, the interference from deceleration and direction-changing impact signals significantly affects fault impact signals. To address these challenges, this paper proposes a method for extracting fault features in low-speed reciprocating bearings based on short signal segmentation and modulation signal bispectrum (MSB) slicing. This method initially separates short signals corresponding to individual cycles from the vibration signals based on encoder signals. Subsequently, MSB analysis is performed on each short signal to generate MSB carrier-slice spectra. The optimal carrier frequency and its corresponding modulation signal slice spectrum are determined based on the carrier-slice spectra. Finally, the MSB modulation signal slice spectra of the short signal set are averaged to obtain the overall average feature of the sliced spectra.
文摘内齿式回转支承兼有滚动轴承的回转支承特点和齿轮啮合传动特点,在联合载荷作用下其动态性能的影响因素众多,容易出现轮齿磨损或断齿、套圈滚道磨损和运行精度变差等问题。综合考虑钢球与内外套圈滚道、保持架兜孔的动态接触作用及内齿圈轮齿间的啮合传动作用,建立了内齿式回转支承参数化多体接触动力学模型。分析了沟道曲率半径、保持架兜孔孔径、初始接触角和轮齿变位系数等关键设计参数对回转支承齿轮啮合力、1号钢球与N1滚道的接触力、内齿圈质心轴向和径向振动位移的影响规律。在此基础上,采用试验设计(design of experiment,DOE)方法,对内齿式回转支承的关键设计参数进行全因子试验设计及计算,获得了多参数影响下回转支承的动态性能。结合线性加权法,运用统一量纲法和权系数法构造新的多目标优化函数,提出了回转支承动态性能的多变量多目标优化设计方法,得到回转支承的轮齿啮合力下降了49.27%,1号钢球与N1滚道的接触力下降了29.6%,内齿圈质心轴向振动位移减小了5.41%,内齿圈质心径向位移减小了15.88%,回转支承的性能得到了优化。研究结果为回转支承的动态设计提供了参考。
