After excavation,some of the surrounding rock mass is in a state of triaxial extension,exhibiting tensile or shear fracture modes.To study the energy mechanism of tensile fracture turning to shear fracture,a series of...After excavation,some of the surrounding rock mass is in a state of triaxial extension,exhibiting tensile or shear fracture modes.To study the energy mechanism of tensile fracture turning to shear fracture,a series of triaxial extension tests were conducted on sandstone under confining pressures of 10,30,50 and 70 MPa.Elastic energy and dissipated energy were separated by single unloading,the input energy u_(t),elastic energy u_(e),and dissipated energy u_(d)at different unloading stress levels were calculated by the integrating stress−strain curves.The results show that tensile cracks dominate fracture under lower confining pressure(10 MPa),and shear cracks play an increasingly important role in fracture as confining pressure increases(30,50 and 70 MPa).Based on the phenomenon that u_(e)and u_(d)increase linearly with increasing u_(t),a possible energy distribution mechanism of fracture mode transition under triaxial extension was proposed.In addition,it was found that peak energy storage capacity is more sensitive to confining pressure compared to elastic energy conversion capacity.展开更多
Rock fracture warning is one of the significant challenges in rock mechanics.Many true triaxial and synchronous acoustic emission(AE)tests were conducted on granite samples.The investigation focused on the characteris...Rock fracture warning is one of the significant challenges in rock mechanics.Many true triaxial and synchronous acoustic emission(AE)tests were conducted on granite samples.The investigation focused on the characteristics of AE signals preceding granite fracture,based on the critical slowing down(CSD)theory.The granite undergoes a transition from the stable phase to the fracture phase and exhibits a clear CSD phenomenon,characterized by a pronounced increase in variance and autocorrelation coefficient.The variance mutation points were found to be more identifiable and suitable as the primary criterion for predicting precursor information related to granite fracture,compared to the autocorrelation coefficient.It is noteworthy to emphasize that the CSD factor holds greater potential in elucidating the underlying mechanisms responsible for the critical transition of granite fracture,in comparison to the AE timing parameters.Furthermore,a novel multi-parameter collaborative prediction method for rock fracture was developed by comprehensively analyzing predictive information,including abnormal variation modes and the CSD factor of AE characteristic parameters.This method enhances the understanding and prediction of rock fracture-related geohazards.展开更多
The bearing fault information is often interfered or lost in the background noise after the vibration signal being transferred complicatedly, which will make it very difficult to extract fault features from the vibrat...The bearing fault information is often interfered or lost in the background noise after the vibration signal being transferred complicatedly, which will make it very difficult to extract fault features from the vibration signals. To avoid the problem in choosing and extracting the fault features in bearing fault diagnosing, a novelty fault diagnosis method based on sparse decomposition theory is proposed. Certain over-complete dictionaries are obtained by training, on which the bearing vibration signals corresponded to different states can be decomposed sparsely. The fault detection and state identification can be achieved based on the fact that the sparse representation errors of the signal on different dictionaries are different. The effects of the representation error threshold and the number of dictionary atoms used in signal decomposition to the fault diagnosis are analyzed. The effectiveness of the proposed method is validated with experimental bearing vibration signals.展开更多
Deformation and failure of deep clay samples are closely related to energy changes.Investigating the energy conversion and damage behavior of deep clay during loading and unloading tests has important significance for...Deformation and failure of deep clay samples are closely related to energy changes.Investigating the energy conversion and damage behavior of deep clay during loading and unloading tests has important significance for prevention-control of soil destabilization damage caused by mine shaft excavation.In the present work,triaxial tests of consolidated clay under different stress paths and stress rates were conducted.The results reveal that the mechanical properties of soils have strong stress rate effects and the samples mainly experience energy storage in the elastic stage,after that,the energy conversion mainly undergoes an increase of dissipative energy and release of elastic energy,which is also confirmed by the results of the analysis in the subsequent CT tests.Two damage indicators were compared,finding that the indicator based on dissipative energy has more obvious differences in two stress paths and can be used as a better indicator to describe the damage evolution of soils.Finally,in the triaxial shear test,due to the unloading effect of confining pressure,the damage of soils increased more rapidly near breaking than in the triaxial compression test,which indicates that the damage caused by unloading on deep soil is more abrupt than that caused by loading.展开更多
The stochastic resonance behavior of coupled stochastic resonance(SR)system with time-delay under mass and frequency fluctuations was studied.Firstly,the approximate system model of the time-delay system was obtained ...The stochastic resonance behavior of coupled stochastic resonance(SR)system with time-delay under mass and frequency fluctuations was studied.Firstly,the approximate system model of the time-delay system was obtained by the theory of small time-delay approximation.Then,the random average method and Shapiro-Loginov algorithm were used to calculate the output amplitude ratio of the two subsystems.The simulation analysis shows that increasing the time-delay and the input signal amplitude appropriately can improve the output response of the system.Finally,the system is applied to bearing fault diagnosis and compared with the stochastic resonance system with random mass and random frequency.The experimental results show that the coupled SR system taking into account the actual effect of time-delay and couple can more effectively extract the frequency of the fault signal,and thus realizing the diagnosis of the fault signal,which has important engineering application value.展开更多
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
基金Project(52074352)supported by the National Natural Science Foundation of ChinaProject(2023JJ30680)supported by the National Science and Technology Major Project of China。
文摘After excavation,some of the surrounding rock mass is in a state of triaxial extension,exhibiting tensile or shear fracture modes.To study the energy mechanism of tensile fracture turning to shear fracture,a series of triaxial extension tests were conducted on sandstone under confining pressures of 10,30,50 and 70 MPa.Elastic energy and dissipated energy were separated by single unloading,the input energy u_(t),elastic energy u_(e),and dissipated energy u_(d)at different unloading stress levels were calculated by the integrating stress−strain curves.The results show that tensile cracks dominate fracture under lower confining pressure(10 MPa),and shear cracks play an increasingly important role in fracture as confining pressure increases(30,50 and 70 MPa).Based on the phenomenon that u_(e)and u_(d)increase linearly with increasing u_(t),a possible energy distribution mechanism of fracture mode transition under triaxial extension was proposed.In addition,it was found that peak energy storage capacity is more sensitive to confining pressure compared to elastic energy conversion capacity.
基金Project(52074294)supported by the National Natural Science Foundation of ChinaProject(2022YJSNY16)supported by the Fundamental Research Funds for the Central Universities,China。
文摘Rock fracture warning is one of the significant challenges in rock mechanics.Many true triaxial and synchronous acoustic emission(AE)tests were conducted on granite samples.The investigation focused on the characteristics of AE signals preceding granite fracture,based on the critical slowing down(CSD)theory.The granite undergoes a transition from the stable phase to the fracture phase and exhibits a clear CSD phenomenon,characterized by a pronounced increase in variance and autocorrelation coefficient.The variance mutation points were found to be more identifiable and suitable as the primary criterion for predicting precursor information related to granite fracture,compared to the autocorrelation coefficient.It is noteworthy to emphasize that the CSD factor holds greater potential in elucidating the underlying mechanisms responsible for the critical transition of granite fracture,in comparison to the AE timing parameters.Furthermore,a novel multi-parameter collaborative prediction method for rock fracture was developed by comprehensively analyzing predictive information,including abnormal variation modes and the CSD factor of AE characteristic parameters.This method enhances the understanding and prediction of rock fracture-related geohazards.
基金Projects(51375484,51475463)supported by the National Natural Science Foundation of ChinaProject(kxk140301)supported by Interdisciplinary Joint Training Project for Doctoral Student of National University of Defense Technology,China
文摘The bearing fault information is often interfered or lost in the background noise after the vibration signal being transferred complicatedly, which will make it very difficult to extract fault features from the vibration signals. To avoid the problem in choosing and extracting the fault features in bearing fault diagnosing, a novelty fault diagnosis method based on sparse decomposition theory is proposed. Certain over-complete dictionaries are obtained by training, on which the bearing vibration signals corresponded to different states can be decomposed sparsely. The fault detection and state identification can be achieved based on the fact that the sparse representation errors of the signal on different dictionaries are different. The effects of the representation error threshold and the number of dictionary atoms used in signal decomposition to the fault diagnosis are analyzed. The effectiveness of the proposed method is validated with experimental bearing vibration signals.
基金Project(2016YFC0600904)supported by the National Key Research and Development Program of ChinaProject(BK20200653)supported by the Natural Science Foundation of Jiangsu,ChinaProject(2020M681768)supported by the China Postdoctoral Science Foundation。
文摘Deformation and failure of deep clay samples are closely related to energy changes.Investigating the energy conversion and damage behavior of deep clay during loading and unloading tests has important significance for prevention-control of soil destabilization damage caused by mine shaft excavation.In the present work,triaxial tests of consolidated clay under different stress paths and stress rates were conducted.The results reveal that the mechanical properties of soils have strong stress rate effects and the samples mainly experience energy storage in the elastic stage,after that,the energy conversion mainly undergoes an increase of dissipative energy and release of elastic energy,which is also confirmed by the results of the analysis in the subsequent CT tests.Two damage indicators were compared,finding that the indicator based on dissipative energy has more obvious differences in two stress paths and can be used as a better indicator to describe the damage evolution of soils.Finally,in the triaxial shear test,due to the unloading effect of confining pressure,the damage of soils increased more rapidly near breaking than in the triaxial compression test,which indicates that the damage caused by unloading on deep soil is more abrupt than that caused by loading.
基金Project(61771085)supported by the National Natural Science Foundation of ChinaProject(KJQN 201900601)supported by the Research Project of Chongqing Educational Commission,China。
文摘The stochastic resonance behavior of coupled stochastic resonance(SR)system with time-delay under mass and frequency fluctuations was studied.Firstly,the approximate system model of the time-delay system was obtained by the theory of small time-delay approximation.Then,the random average method and Shapiro-Loginov algorithm were used to calculate the output amplitude ratio of the two subsystems.The simulation analysis shows that increasing the time-delay and the input signal amplitude appropriately can improve the output response of the system.Finally,the system is applied to bearing fault diagnosis and compared with the stochastic resonance system with random mass and random frequency.The experimental results show that the coupled SR system taking into account the actual effect of time-delay and couple can more effectively extract the frequency of the fault signal,and thus realizing the diagnosis of the fault signal,which has important engineering application value.
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.
