The impulsive components induced by bearing faults are key features for assessing gear-box bearing faults.However,because of heavy background noise and the interferences of other vibrations,it is difficult to extract ...The impulsive components induced by bearing faults are key features for assessing gear-box bearing faults.However,because of heavy background noise and the interferences of other vibrations,it is difficult to extract these impulsive components caused by faults,particularly early faults,from the measured vibration signals.To capture the high-level structure of impulsive components embedded in measured vibration signals,a dictionary learning method called shift-invariant K-means singular value decomposition(SI-K-SVD)dictionary learning is used to detect the early faults of gear-box bearings.Although SI-K-SVD is more flexible and adaptable than existing methods,the improper selection of two SI-K-SVD-related parameters,namely,the number of iterations and the pattern lengths,has an adverse influence on fault detection performance.Therefore,the sparsity of the envelope spectrum(SES)and the kurtosis of the envelope spectrum(KES)are used to select these two key parameters,respectively.SI-K-SVD with the two selected optimal parameter values,referred to as optimal parameter SI-K-SVD(OP-SI-K-SVD),is proposed to detect gear-box bearing faults.The proposed method is verified by both simulations and an experiment.Compared to the state-of-the-art methods,namely,empirical model decomposition,wavelet transform and K-SVD,OP-SI-K-SVD has better performance in diagnosing the early faults of a gear-box bearing.展开更多
In the proximity of an active fault, spatial variation of peak ground motion is significantly affected by the faulting mechanism. It has been observed that near fault ground motions consists of different characteristi...In the proximity of an active fault, spatial variation of peak ground motion is significantly affected by the faulting mechanism. It has been observed that near fault ground motions consists of different characteristics compared to the far fault ground motions. Near fault records, in the distance range of less than 100 m from the faults are not available except for few cases. Therefore numerical simulation of ground motions for such near-fault situations is necessary. In addition to the understanding of the phenomenon of near fault ground motion there is a need to enhance our understanding of the possible potential hazard that can be caused due to the future rupture activity by understanding the phenomenon of surface faulting. In this paper we propose numerical simulation based on discrete modeling to investigate the fault rupture propagation and its effect on the surface peak ground acceleration. In the present two dimensional study rupture propagation due to bedrock motion has been observed for different shear wave velocity. A model of size 1000× 150 m is selected for this purpose. It has been observed that as the stiffness of the media is decreasing, the affected surface is decreasing and also width of the shear crack zone is decreasing. Secondly, we attempted to study the ground motion on the surface due to the bedrock motion in presence of boulders in the soil media by keeping the boulder at different positions. We find that there is an increase in the shear zone as well as the PGA on the surface when the boulder is present on the foot wall and in the vicinity of the rupture zone. Finally, we performed the analysis using layered media and studied the affect of crack propagation and also the variation of peak accelerations. Findings from the study can be utilized to assess the damage potential of the near fault areas.展开更多
基金Project(51875481) supported by the National Natural Science Foundation of ChinaProject(2682017CX011) supported by the Fundamental Research Foundations for the Central Universities,China+2 种基金Project(2017M623009) supported by the China Postdoctoral Science FoundationProject(2017YFB1201004) supported by the National Key Research and Development Plan for Advanced Rail Transit,ChinaProject(2019TPL_T08) supported by the Research Fund of the State Key Laboratory of Traction Power,China
文摘The impulsive components induced by bearing faults are key features for assessing gear-box bearing faults.However,because of heavy background noise and the interferences of other vibrations,it is difficult to extract these impulsive components caused by faults,particularly early faults,from the measured vibration signals.To capture the high-level structure of impulsive components embedded in measured vibration signals,a dictionary learning method called shift-invariant K-means singular value decomposition(SI-K-SVD)dictionary learning is used to detect the early faults of gear-box bearings.Although SI-K-SVD is more flexible and adaptable than existing methods,the improper selection of two SI-K-SVD-related parameters,namely,the number of iterations and the pattern lengths,has an adverse influence on fault detection performance.Therefore,the sparsity of the envelope spectrum(SES)and the kurtosis of the envelope spectrum(KES)are used to select these two key parameters,respectively.SI-K-SVD with the two selected optimal parameter values,referred to as optimal parameter SI-K-SVD(OP-SI-K-SVD),is proposed to detect gear-box bearing faults.The proposed method is verified by both simulations and an experiment.Compared to the state-of-the-art methods,namely,empirical model decomposition,wavelet transform and K-SVD,OP-SI-K-SVD has better performance in diagnosing the early faults of a gear-box bearing.
文摘In the proximity of an active fault, spatial variation of peak ground motion is significantly affected by the faulting mechanism. It has been observed that near fault ground motions consists of different characteristics compared to the far fault ground motions. Near fault records, in the distance range of less than 100 m from the faults are not available except for few cases. Therefore numerical simulation of ground motions for such near-fault situations is necessary. In addition to the understanding of the phenomenon of near fault ground motion there is a need to enhance our understanding of the possible potential hazard that can be caused due to the future rupture activity by understanding the phenomenon of surface faulting. In this paper we propose numerical simulation based on discrete modeling to investigate the fault rupture propagation and its effect on the surface peak ground acceleration. In the present two dimensional study rupture propagation due to bedrock motion has been observed for different shear wave velocity. A model of size 1000× 150 m is selected for this purpose. It has been observed that as the stiffness of the media is decreasing, the affected surface is decreasing and also width of the shear crack zone is decreasing. Secondly, we attempted to study the ground motion on the surface due to the bedrock motion in presence of boulders in the soil media by keeping the boulder at different positions. We find that there is an increase in the shear zone as well as the PGA on the surface when the boulder is present on the foot wall and in the vicinity of the rupture zone. Finally, we performed the analysis using layered media and studied the affect of crack propagation and also the variation of peak accelerations. Findings from the study can be utilized to assess the damage potential of the near fault areas.
