Under harmonic wave excitation, the dynamic response of a bilinear SDOF system can be expressed by the Hilbert spectrum. The Hilbert spectrum can be formulated by (1) the inter-wave combination mechanism between the s...Under harmonic wave excitation, the dynamic response of a bilinear SDOF system can be expressed by the Hilbert spectrum. The Hilbert spectrum can be formulated by (1) the inter-wave combination mechanism between the steady response and the transient response when the system behaves linearly, or (2) the intra-wave modulation mechanism embedded in one intrinsic mode function (IMF) component when the system behaves nonlinearly. The temporal variation of the instantaneous frequency of the IMF component is consistent with the system nonlinear behavior of yielding and unloading. As a thorough study of this fundamental structural dynamics problem, this article investigates the influence of the amplitude of the harmonic wave excitation on the Hilbert spectrum and the intrinsic oscillatory mode of the dynamic response of a bilinear SDOF system.展开更多
The tin(Sn)-tungsten(W)polymetallic ore concentrated district in SE Yunnan is distributed at the junction region of the Yangtze Block,the Cathaysian Block and the Indosinian Block,where there are several giant deposit...The tin(Sn)-tungsten(W)polymetallic ore concentrated district in SE Yunnan is distributed at the junction region of the Yangtze Block,the Cathaysian Block and the Indosinian Block,where there are several giant deposits of tin,tungsten,copper,silver,lead,zinc and indium closely associated with a large scale Late Cretaceous magmatism.Bi-dimensional empirical mode decomposition(BEMD)is used to extract aeromagnetic anomalous components at the survey scale of 1:200000 from the original aeromagnetic data of SE Yunnan.Four intrinsic mode functions(IMFs)and a residues component are obtained,which may reflect the geological structures and geological bodies at different spatial scales from high frequency to low frequency.The results are shown as follows:(1)Two different types of Precambrian basement in the study area were recognized:one is the Yangtze Block basement characterized by a strong positive magnetic anomaly,the other is the Cathaysian Block basement with a weak negative magnetic anomaly.The former consists of high grade metamorphic rocks including metamorphosed basic igneous rocks,while the latter consists of low grade metamorphosed sedimentary rocks.(2)The aeromagnetic anomalies associated with Sn-W polymetallic mineralization and related to granites in the study area illustrate a pattern of a skarnized alteration-mineralization zone with a positive ring magnetic anomaly enclosing a granitic intrusion with negative magnetic anomaly;(3)The ring positive magnetic anomaly zones enclosing the negative magnetic anomaly are defined as the SnW polymetallic ore-searching targets in the study area.展开更多
In view of the usefulness of Empirical Mode Decomposition （EMD）, Artificial Neural Networks （ ANN）, and Most Relevant Matching Extension （MRME） methods in dealing with nonlinear signals, we pro- pose a new way o...In view of the usefulness of Empirical Mode Decomposition （EMD）, Artificial Neural Networks （ ANN）, and Most Relevant Matching Extension （MRME） methods in dealing with nonlinear signals, we pro- pose a new way of combining these methods to deal with signal prediction. We found the results of combining EMD with either ANN or MRME to have higher prediction precision for a time series than the result of using EMD alone.展开更多
A new algorithm, named segmented second empirical mode decomposition （EMD） algorithm, is proposed in this paper in order to reduce the computing time of EMD and make EMD algorithm available to online time-frequency ...A new algorithm, named segmented second empirical mode decomposition （EMD） algorithm, is proposed in this paper in order to reduce the computing time of EMD and make EMD algorithm available to online time-frequency analysis. The original data is divided into some segments with the same length. Each segment data is processed based on the principle of the first-level EMD decomposition. The algorithm is compared with the traditional EMD and results show that it is more useful and effective for analyzing nonlinear and non-stationary signals.展开更多
Dynanfic forces are the main factor that influences the axle weight measurement accuracy of moving vehicle. Empirical mode decomposition （EMD） is presented to separate the dynamic forces contained in the axle weight...Dynanfic forces are the main factor that influences the axle weight measurement accuracy of moving vehicle. Empirical mode decomposition （EMD） is presented to separate the dynamic forces contained in the axle weight signal. The concept and algorithm of EMD are introduced. The characteristic of the axle weight signal is analyzed. The method of judging pseudo intrinsic mode function （pseudo-IMF） is presented to improve the weighing accuracy. Numerical simulation and field experiments are conducted to evaluate the performance of EMD. The result shows effectiveness of the proposed method. Maximum weighing errors of the front axle, the rear axle and the gross weight at the speed of 15 km/h or lower are 2.22%, 6.26% and 4.11% respectively.展开更多
基金National Natural Science Foundation of China Under Grant No.50278090
文摘Under harmonic wave excitation, the dynamic response of a bilinear SDOF system can be expressed by the Hilbert spectrum. The Hilbert spectrum can be formulated by (1) the inter-wave combination mechanism between the steady response and the transient response when the system behaves linearly, or (2) the intra-wave modulation mechanism embedded in one intrinsic mode function (IMF) component when the system behaves nonlinearly. The temporal variation of the instantaneous frequency of the IMF component is consistent with the system nonlinear behavior of yielding and unloading. As a thorough study of this fundamental structural dynamics problem, this article investigates the influence of the amplitude of the harmonic wave excitation on the Hilbert spectrum and the intrinsic oscillatory mode of the dynamic response of a bilinear SDOF system.
基金jointly funded by the National Key Research and Development Project of China(No.2016YFC0600509)the National Natural Science Foundation of China(Nos.41972312,41672329,41272365)the China Geological Survey(No.1212011220922)。
文摘The tin(Sn)-tungsten(W)polymetallic ore concentrated district in SE Yunnan is distributed at the junction region of the Yangtze Block,the Cathaysian Block and the Indosinian Block,where there are several giant deposits of tin,tungsten,copper,silver,lead,zinc and indium closely associated with a large scale Late Cretaceous magmatism.Bi-dimensional empirical mode decomposition(BEMD)is used to extract aeromagnetic anomalous components at the survey scale of 1:200000 from the original aeromagnetic data of SE Yunnan.Four intrinsic mode functions(IMFs)and a residues component are obtained,which may reflect the geological structures and geological bodies at different spatial scales from high frequency to low frequency.The results are shown as follows:(1)Two different types of Precambrian basement in the study area were recognized:one is the Yangtze Block basement characterized by a strong positive magnetic anomaly,the other is the Cathaysian Block basement with a weak negative magnetic anomaly.The former consists of high grade metamorphic rocks including metamorphosed basic igneous rocks,while the latter consists of low grade metamorphosed sedimentary rocks.(2)The aeromagnetic anomalies associated with Sn-W polymetallic mineralization and related to granites in the study area illustrate a pattern of a skarnized alteration-mineralization zone with a positive ring magnetic anomaly enclosing a granitic intrusion with negative magnetic anomaly;(3)The ring positive magnetic anomaly zones enclosing the negative magnetic anomaly are defined as the SnW polymetallic ore-searching targets in the study area.
基金supporteal by the Notional Natural Scince Foundation of Hebei Province(D201000921)
文摘In view of the usefulness of Empirical Mode Decomposition （EMD）, Artificial Neural Networks （ ANN）, and Most Relevant Matching Extension （MRME） methods in dealing with nonlinear signals, we pro- pose a new way of combining these methods to deal with signal prediction. We found the results of combining EMD with either ANN or MRME to have higher prediction precision for a time series than the result of using EMD alone.
文摘A new algorithm, named segmented second empirical mode decomposition （EMD） algorithm, is proposed in this paper in order to reduce the computing time of EMD and make EMD algorithm available to online time-frequency analysis. The original data is divided into some segments with the same length. Each segment data is processed based on the principle of the first-level EMD decomposition. The algorithm is compared with the traditional EMD and results show that it is more useful and effective for analyzing nonlinear and non-stationary signals.
基金Project supported by the Science Foundation of Shanghai Municipal Commission of Science and Technology （Grant No.035115003）.Acknowledgment The authors would like to thank Shanghai Yamato Scale Co., Ltd. for providing the experiment site and truck.
文摘Dynanfic forces are the main factor that influences the axle weight measurement accuracy of moving vehicle. Empirical mode decomposition （EMD） is presented to separate the dynamic forces contained in the axle weight signal. The concept and algorithm of EMD are introduced. The characteristic of the axle weight signal is analyzed. The method of judging pseudo intrinsic mode function （pseudo-IMF） is presented to improve the weighing accuracy. Numerical simulation and field experiments are conducted to evaluate the performance of EMD. The result shows effectiveness of the proposed method. Maximum weighing errors of the front axle, the rear axle and the gross weight at the speed of 15 km/h or lower are 2.22%, 6.26% and 4.11% respectively.
