In Fused Filament Fabrication(FFF),the state of material flow significantly influences printing outcomes.However,online monitoring of these micro-physical processes within the extruder remains challenging.The flow sta...In Fused Filament Fabrication(FFF),the state of material flow significantly influences printing outcomes.However,online monitoring of these micro-physical processes within the extruder remains challenging.The flow state is affected by multiple parameters,with temperature and volumetric flow rate(VFR)being the most critical.The study explores the stable extrusion of flow with a highly sensitive acoustic emission(AE)sensor so that AE signals generated by the friction in the annular region can reflect the flow state more effectively.Nevertheless,the large volume and broad frequency range of the data present processing challenges.This study proposes a method that initially selects short impact signals and then uses the Fast Kurtogram(FK)to identify the frequency with the highest kurtosis for signal filtration.The results indicate that this approach significantly enhances processing speed and improves feature extraction capabilities.By correlating AE characteristics under various parameters with the quality of extruded raster beads,AE can monitor the real-time state of material flow.This study offers a concise and efficient method for monitoring the state of raster beads and demonstrates the potential of online monitoring of the flow states.展开更多
A slight uneven settlement of the foundation may cause the wind turbine to shake,tilt,or even collapse,so it is increasingly necessary to realize remote condition monitoring of the foundations.At present,the wind turb...A slight uneven settlement of the foundation may cause the wind turbine to shake,tilt,or even collapse,so it is increasingly necessary to realize remote condition monitoring of the foundations.At present,the wind turbine foundation monitoring system is incomplete.The current monitoring research of the tower foundation is mainly of contact measurements,using acceleration sensors and static-level sensors for monitoring multiple reference points.Such monitoring methods will face some disadvantages,such as the complexity of monitoring deployment,the cost of manpower,and the load effect on the tower structure.To solve above issues,this paper aims to investigate wind turbine tower foundation variation dynamic monitoring based on machine vision.Machine vision monitoring is a kind of noncontact measurement,which helps to realize comprehensive diagnosis of early foundation uneven settlement and loose faults.The FEA model is firstly investigated as the theoretical foundation to investigate the dynamics of the tower foundation.Second,the Gaussian-based vibration detection is adopted by tracking the tower edge points.Finally,a tower structure with distributed foundation support is tested.The modal parameters obtained from the visual measurement are compared with those from the accelerometer,proving the vision method can effectively monitor the issues with tower foundation changes.展开更多
As important methods to guide the field soil compaction,the standard and modified Proctor tests for laboratory compaction have remained unchanged for decades,which should be improved to better understand the compactio...As important methods to guide the field soil compaction,the standard and modified Proctor tests for laboratory compaction have remained unchanged for decades,which should be improved to better understand the compaction process and the properties of soils.In this study,an accelerometer was installed on a Marshall impact compactor to capture the dynamic response of three types of soils during compaction.The experimental test results indicated that the acceleration curve for each blow gradually evolved to a stable pattern following the progress of compaction,and the impact and gyratory locking points were linearly related with coefficient of determination R2equal to 0.59.The impact compaction curve could be further constructed by filtering the structural resonance,which can be used to quantify the compactability of soil materials.Although each type of soil had a unique set of compaction curves,the slope and value of compaction curve altered accordingly as the moisture content changed for the same soil.In addition,the average acceleration value at the final compaction stage could serve as the target value of soil stiffness.展开更多
The transient impulse features caused by rolling bearing faults are often present in the resonance frequency band which is closely related to the dynamic characteristics of the machine structure.Informative frequency ...The transient impulse features caused by rolling bearing faults are often present in the resonance frequency band which is closely related to the dynamic characteristics of the machine structure.Informative frequency band identification is a crucial prerequisite for envelope analysis and thereby accurate fault diagnosis of rolling bearings.In this paper,based on the ratio of quasi-arithmetic means and Gini index,improved Gini indices(IGIs)are proposed to quantify the transient impulse features of a signal,and their effectiveness and advantages in sparse quantification are confirmed by simulation analysis and comparisons with traditional sparsity measures.Furthermore,an IGI-based envelope analysis method named IGIgram is developed for fault diagnosis of rolling bearings.In the new method,an IGI-based indicator is constructed to evaluate the impulsiveness and cyclostationarity of the narrow-band filtered signal simultaneously,and then a frequency band with abundant fault information is adaptively determined for extracting bearing fault features.The performance of the IGIgram method is verified on the simulation signal and railway bearing experimental signals and compared with typical sparsity measures-based envelope analysis methods and log-cycligram.The results demonstrate that the proposed IGIs are efficient in quantifying bearing fault-induced transient features and the IGIgram method with appropriate power exponent can effectively achieve the diagnostics of different axle-box bearing faults.展开更多
Intelligent compaction （IC） is a relatively new technology for asphalt paving industry. The present study evaluated the effectiveness and potential issues of the IC technology for flexible pavement resurfacing const...Intelligent compaction （IC） is a relatively new technology for asphalt paving industry. The present study evaluated the effectiveness and potential issues of the IC technology for flexible pavement resurfacing construction using two field projects. In the first project, a geostatistical semivariogram model was established and the parameters derived from it were compared with univariate statistical parameters for the Compaction Meter Value （CMV） data. Further analyses illustrated the effect of temperature on the CMV value and compaction uniformity. In the second project, a multivariate analysis was performed between in situ tests and IC data. The possibility of combining various IC data to predict the asphalt layer density and improve the current quality control and assurance system was discussed.展开更多
文摘In Fused Filament Fabrication(FFF),the state of material flow significantly influences printing outcomes.However,online monitoring of these micro-physical processes within the extruder remains challenging.The flow state is affected by multiple parameters,with temperature and volumetric flow rate(VFR)being the most critical.The study explores the stable extrusion of flow with a highly sensitive acoustic emission(AE)sensor so that AE signals generated by the friction in the annular region can reflect the flow state more effectively.Nevertheless,the large volume and broad frequency range of the data present processing challenges.This study proposes a method that initially selects short impact signals and then uses the Fast Kurtogram(FK)to identify the frequency with the highest kurtosis for signal filtration.The results indicate that this approach significantly enhances processing speed and improves feature extraction capabilities.By correlating AE characteristics under various parameters with the quality of extruded raster beads,AE can monitor the real-time state of material flow.This study offers a concise and efficient method for monitoring the state of raster beads and demonstrates the potential of online monitoring of the flow states.
基金the support of the National Natural Science Foundation of China(NSFC)(62076029)Guangdong provincial base platforms and major scientific research project:Research on Remote Large Facility Condition Monitoring Method Based on Motion Amplification(ZX-2021-040)+1 种基金Major Scientific and Technological Project in the Inner Mongolia Autonomous Region(2023YFSW0003)the Guangdong Basic and Applied Basic Research Fund Offshore Wind Power Scheme-General Project under Grant 2022A1515240042.
文摘A slight uneven settlement of the foundation may cause the wind turbine to shake,tilt,or even collapse,so it is increasingly necessary to realize remote condition monitoring of the foundations.At present,the wind turbine foundation monitoring system is incomplete.The current monitoring research of the tower foundation is mainly of contact measurements,using acceleration sensors and static-level sensors for monitoring multiple reference points.Such monitoring methods will face some disadvantages,such as the complexity of monitoring deployment,the cost of manpower,and the load effect on the tower structure.To solve above issues,this paper aims to investigate wind turbine tower foundation variation dynamic monitoring based on machine vision.Machine vision monitoring is a kind of noncontact measurement,which helps to realize comprehensive diagnosis of early foundation uneven settlement and loose faults.The FEA model is firstly investigated as the theoretical foundation to investigate the dynamics of the tower foundation.Second,the Gaussian-based vibration detection is adopted by tracking the tower edge points.Finally,a tower structure with distributed foundation support is tested.The modal parameters obtained from the visual measurement are compared with those from the accelerometer,proving the vision method can effectively monitor the issues with tower foundation changes.
文摘As important methods to guide the field soil compaction,the standard and modified Proctor tests for laboratory compaction have remained unchanged for decades,which should be improved to better understand the compaction process and the properties of soils.In this study,an accelerometer was installed on a Marshall impact compactor to capture the dynamic response of three types of soils during compaction.The experimental test results indicated that the acceleration curve for each blow gradually evolved to a stable pattern following the progress of compaction,and the impact and gyratory locking points were linearly related with coefficient of determination R2equal to 0.59.The impact compaction curve could be further constructed by filtering the structural resonance,which can be used to quantify the compactability of soil materials.Although each type of soil had a unique set of compaction curves,the slope and value of compaction curve altered accordingly as the moisture content changed for the same soil.In addition,the average acceleration value at the final compaction stage could serve as the target value of soil stiffness.
基金supported by the National Key Research and Development Program of China (Grant No.2019YFB1405401)the National Natural Science Foundation of China (Grant No.P110520G02004)the China Scholarship Council (Grant No.202107000033),which are highly appreciated by the authors。
文摘The transient impulse features caused by rolling bearing faults are often present in the resonance frequency band which is closely related to the dynamic characteristics of the machine structure.Informative frequency band identification is a crucial prerequisite for envelope analysis and thereby accurate fault diagnosis of rolling bearings.In this paper,based on the ratio of quasi-arithmetic means and Gini index,improved Gini indices(IGIs)are proposed to quantify the transient impulse features of a signal,and their effectiveness and advantages in sparse quantification are confirmed by simulation analysis and comparisons with traditional sparsity measures.Furthermore,an IGI-based envelope analysis method named IGIgram is developed for fault diagnosis of rolling bearings.In the new method,an IGI-based indicator is constructed to evaluate the impulsiveness and cyclostationarity of the narrow-band filtered signal simultaneously,and then a frequency band with abundant fault information is adaptively determined for extracting bearing fault features.The performance of the IGIgram method is verified on the simulation signal and railway bearing experimental signals and compared with typical sparsity measures-based envelope analysis methods and log-cycligram.The results demonstrate that the proposed IGIs are efficient in quantifying bearing fault-induced transient features and the IGIgram method with appropriate power exponent can effectively achieve the diagnostics of different axle-box bearing faults.
文摘Intelligent compaction （IC） is a relatively new technology for asphalt paving industry. The present study evaluated the effectiveness and potential issues of the IC technology for flexible pavement resurfacing construction using two field projects. In the first project, a geostatistical semivariogram model was established and the parameters derived from it were compared with univariate statistical parameters for the Compaction Meter Value （CMV） data. Further analyses illustrated the effect of temperature on the CMV value and compaction uniformity. In the second project, a multivariate analysis was performed between in situ tests and IC data. The possibility of combining various IC data to predict the asphalt layer density and improve the current quality control and assurance system was discussed.
