This paper focuses on the fast rate fault detection filter (FDF) problem for a class of multirate sampled-data (MSD) systems. A lifting technique is used to convert such an MSD system into a linear time-invariant disc...This paper focuses on the fast rate fault detection filter (FDF) problem for a class of multirate sampled-data (MSD) systems. A lifting technique is used to convert such an MSD system into a linear time-invariant discrete-time one and an unknown input observer (UIO) is considered as FDF to generate residual. The design of FDF is formulated as an H∞ optimization problem and a solvable condition as well as an optimal solution are derived. The causality of the residual generator can be guaranteed so that the fast rate residual can be implemented via inverse lifting. A numerical example is included to demonstrate the feasibility of the obtained results.展开更多
A seismometer data acquisition unit has been used in the Changping seismic station to record the output of a strainmeter. The output of a strainmeter was sampled at a rate of l00/sec by seismometer acquisition from th...A seismometer data acquisition unit has been used in the Changping seismic station to record the output of a strainmeter. The output of a strainmeter was sampled at a rate of l00/sec by seismometer acquisition from the original rate of 1 per minute. Plenty of high frequency sampled data was recorded. The minute value curve calculated from the seismometer acquisition are consistent with that of the original data sampled by the strain acquisition system. More complete waveforms were recorded with a higher sampling rate, and seismic phase parameters calculated by using higher sampling rate strain seismic waves are also in consistency with the results of its predecessors. Spectra of the strain seismic waves are compared with that of seismic waves recorded by a seismometer in the Shisanling seismic station, and their trends are almost the same. Besides, some lower frequency components still exist in strain seismic waves.展开更多
The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by...The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.展开更多
Purpose–Individuals’driving behavior data are becoming available widely through Global Positioning System devices and on-board diagnostic systems.The incoming data can be sampled at rates ranging from one Hertz(or e...Purpose–Individuals’driving behavior data are becoming available widely through Global Positioning System devices and on-board diagnostic systems.The incoming data can be sampled at rates ranging from one Hertz(or even lower)to hundreds of Hertz.Failing to capture substantial changes in vehicle movements over time by“undersampling”can cause loss of information and misinterpretations of the data,but“oversampling”can waste storage and processing resources.The purpose of this study is to empirically explore how micro-driving decisions to maintain speed,accelerate or decelerate,can be best captured,without substantial loss of information.Design/methodology/approach–This study creates a set of indicators to quantify the magnitude of information loss(MIL).Each indicator is calculated as a percentage to index the extent of information loss(EIL)in different situations.An overall information loss index named EIL is created to combine the MIL indicators.Data from a driving simulator study collected at 20 Hertz are analyzed(N=718,481 data points from 35,924 s of driving tests).The study quantifies the relationship between information loss indicators and sampling rates.Findings–The results show that marginally more information is lost as data are sampled down from 20 to 0.5 Hz,but the relationship is not linear.With four indicators of MILs,the overall EIL is 3.85 per cent for 1-Hz sampling rate driving behavior data.If sampling rates are higher than 2 Hz,all MILs are under 5 per cent for importation loss.Originality/value–This study contributes by developing a framework for quantifying the relationship between sampling rates,and information loss and depending on the objective of their study,researchers can choose the appropriate sampling rate necessary to get the right amount of accuracy.展开更多
基金Supported by National Natural Science Foundation of P. R. China (60374021)the Natural Science Foundation of Shandong Province (Y2002G05)the Youth Scientists Foundation of Shandong Province (03BS091, 05BS01007) and Education Ministry Foundation of P. R. China (20050422036)
文摘This paper focuses on the fast rate fault detection filter (FDF) problem for a class of multirate sampled-data (MSD) systems. A lifting technique is used to convert such an MSD system into a linear time-invariant discrete-time one and an unknown input observer (UIO) is considered as FDF to generate residual. The design of FDF is formulated as an H∞ optimization problem and a solvable condition as well as an optimal solution are derived. The causality of the residual generator can be guaranteed so that the fast rate residual can be implemented via inverse lifting. A numerical example is included to demonstrate the feasibility of the obtained results.
基金sponsored by Central Public-interest Scientific Institution Basic Research Fund of Institute of Crustal Dynamics,CEA(ZDJ2008-40,ZDJ2010-15)
文摘A seismometer data acquisition unit has been used in the Changping seismic station to record the output of a strainmeter. The output of a strainmeter was sampled at a rate of l00/sec by seismometer acquisition from the original rate of 1 per minute. Plenty of high frequency sampled data was recorded. The minute value curve calculated from the seismometer acquisition are consistent with that of the original data sampled by the strain acquisition system. More complete waveforms were recorded with a higher sampling rate, and seismic phase parameters calculated by using higher sampling rate strain seismic waves are also in consistency with the results of its predecessors. Spectra of the strain seismic waves are compared with that of seismic waves recorded by a seismometer in the Shisanling seismic station, and their trends are almost the same. Besides, some lower frequency components still exist in strain seismic waves.
基金supported by the National Natural Science Foundation of China(61863034)
文摘The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.
文摘Purpose–Individuals’driving behavior data are becoming available widely through Global Positioning System devices and on-board diagnostic systems.The incoming data can be sampled at rates ranging from one Hertz(or even lower)to hundreds of Hertz.Failing to capture substantial changes in vehicle movements over time by“undersampling”can cause loss of information and misinterpretations of the data,but“oversampling”can waste storage and processing resources.The purpose of this study is to empirically explore how micro-driving decisions to maintain speed,accelerate or decelerate,can be best captured,without substantial loss of information.Design/methodology/approach–This study creates a set of indicators to quantify the magnitude of information loss(MIL).Each indicator is calculated as a percentage to index the extent of information loss(EIL)in different situations.An overall information loss index named EIL is created to combine the MIL indicators.Data from a driving simulator study collected at 20 Hertz are analyzed(N=718,481 data points from 35,924 s of driving tests).The study quantifies the relationship between information loss indicators and sampling rates.Findings–The results show that marginally more information is lost as data are sampled down from 20 to 0.5 Hz,but the relationship is not linear.With four indicators of MILs,the overall EIL is 3.85 per cent for 1-Hz sampling rate driving behavior data.If sampling rates are higher than 2 Hz,all MILs are under 5 per cent for importation loss.Originality/value–This study contributes by developing a framework for quantifying the relationship between sampling rates,and information loss and depending on the objective of their study,researchers can choose the appropriate sampling rate necessary to get the right amount of accuracy.
