It is difficult to determine the discharge stages in a fixed time of repetitive discharge underwater due to the arc formation process being susceptible to external environmental influences. This paper proposes a novel...It is difficult to determine the discharge stages in a fixed time of repetitive discharge underwater due to the arc formation process being susceptible to external environmental influences. This paper proposes a novel underwater discharge stage identification method based on the Strong Tracking Filter(STF) and impedance change characteristics. The time-varying equivalent circuit model of the discharge underwater is established based on the plasma theory analysis of the impedance change characteristics and mechanism of the discharge process. The STF is used to reduce the randomness of the impedance of repeated discharges underwater, and then the universal identification resistance data is obtained. Based on the resistance variation characteristics of the discriminating resistance of the pre-breakdown, main, and oscillatory discharge stages, the threshold values for determining the discharge stage are obtained. These include the threshold values for the resistance variation rate(K) and the moment(t).Experimental and error analysis results demonstrate the efficacy of this innovative method in discharge stage determination, with a maximum mean square deviation of Scrless than 1.761.展开更多
The electrification of vehicles puts forward higher requirements for the power management efficiency of integrated battery management systems as the primary or sole energy supply.In this paper,an efficient adaptive mu...The electrification of vehicles puts forward higher requirements for the power management efficiency of integrated battery management systems as the primary or sole energy supply.In this paper,an efficient adaptive multi-time scale identification strategy is proposed to achieve high-fidelity modeling of complex kinetic processes inside the battery.More specifically,a second-order equivalent circuit model network considering variable characteristic frequency is constructed based on the high-frequency,medium-high-frequency,and low-frequency characteristics of the key kinetic processes.Then,two coupled sub-filters are developed based on forgetting factor recursive least squares and extended Kalman filtering methods and decoupled by the corresponding time-scale information.The coupled iterative calculation of the two sub-filter modules at different time scales is realized by the voltage response of the kinetic diffusion process.In addition,the driver of the low-frequency subalgorithm with the state of charge variation amount as the kernel is designed to realize the adaptive identification of the kinetic diffusion process parameters.Finally,the concept of dynamical parameter entropy is introduced and advocated to verify the physical meaning of the kinetic parameters.The experimental results under three operating conditions show that the mean absolute error and root-mean-square error metrics of the proposed strategy for voltage tracking can be limited to 13 and 16 mV,respectively.Additionally,from the entropy calculation results,the proposed method can reduce the dispersion of parameter identification results by a maximum of 40.72%and 70.05%,respectively,compared with the traditional fixed characteristic frequency algorithms.The proposed method paves the way for the subsequent development of adaptive state estimators and efficient embedded applications.展开更多
Internet traffic classification plays an important role in network management. Many approaches have been proposed to clas-sify different categories of Internet traffic. However, these approaches have specific us-age c...Internet traffic classification plays an important role in network management. Many approaches have been proposed to clas-sify different categories of Internet traffic. However, these approaches have specific us-age contexts that restrict their ability when they are applied in the current network envi-ronment. For example, the port based ap-proach cannot identify network applications with dynamic ports; the deep packet inspec-tion approach is invalid for encrypted network applications; and the statistical based approach is time-onsuming. In this paper, a novel tech-nique is proposed to classify different catego-ries of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multi-stage classifier. The experimental results demonstrate that this approach has high rec-ognition rate which is up to 98% and good performance of real-time for traffic identifica-tion.展开更多
Based on GC-qqqMS/MS,a qualitative and quantitative analysis method for identifying characteristic markers in gasoline samples was established.According to the established method,different grades(#92,#95,#98)of gasoli...Based on GC-qqqMS/MS,a qualitative and quantitative analysis method for identifying characteristic markers in gasoline samples was established.According to the established method,different grades(#92,#95,#98)of gasoline samples collected from different regions(southern,central,northeastern,and northwestern China)were studied and analyzed.The results show that the gasolines can be classified by the relative contents of aromatics,naphthalene series,indene and other characteristic substances.On the basis of the high sensitivity and selectivity of GC-qqqMS/MS,the experiment has identified the characteristic substances,and used the characteristic-ratios methods as well as stoichiometric tools to study the grades and regional differences of gasoline products.It is conducive to the identification and classification of ILR in public security in fire cases,and can also meet the actual handling demand.展开更多
Experimental modeling of a middle-rise office building via ambient modal identification is presented. A 200-DOF (Dimension of freedom) test model is designed to correlate with finite element mode. A newly developed fr...Experimental modeling of a middle-rise office building via ambient modal identification is presented. A 200-DOF (Dimension of freedom) test model is designed to correlate with finite element mode. A newly developed frequency-spatial domain decomposition ( FSDD ) technique is used to identify modal characteristics of the full-size building by using ambient response measurements. In the interested frequency ranges of 0～4.5 Hz and 0～ 6.5 Hz altogether 9 bending and torsion modes are identified. As one of the major focuses of the project, the accurate damping estimation is conducted based on FSDD. The identified modal frequencies and mode shapes are utilized for finite element model tuning. Excellent agreement has been achieved with respect to the final tuned finite element (FE) model up to 9 modes.展开更多
In this paper, the vibration characteristics of the structure in the finite fluid domain are analyzed using a coupled finite element method. The added mass matrix is calculated with finite element method （FEM） by 8-...In this paper, the vibration characteristics of the structure in the finite fluid domain are analyzed using a coupled finite element method. The added mass matrix is calculated with finite element method （FEM） by 8-node acoustic fluid elements. The vibration characteristics of the structure in the finite fluid domain are calculated combining structure FEM mass matrix. By writing relevant programs, the numerical analysis on vibration characteristics of a submerged cantilever rectangular plate in finite fluid domain and loaded ship model is performed. A modal identification experiment for the loaded ship model in air and in water is conducted and the experiment results verify the reliability of the numerical analysis. The numerical method can be used for further research on vibration characteristics and acoustic radiation problems of the structure in the finite fluid domain.展开更多
荞麦是一种常见的食物过敏原,能够引发呼吸系统、消化系统、循环系统等方面的疾病,严重时可导致过敏性休克甚至死亡。明确荞麦中的主要过敏蛋白,确定其中的过敏原表位,对荞麦致敏机理解析及预防治疗相关的过敏疾病具有重要意义。本文综...荞麦是一种常见的食物过敏原,能够引发呼吸系统、消化系统、循环系统等方面的疾病,严重时可导致过敏性休克甚至死亡。明确荞麦中的主要过敏蛋白,确定其中的过敏原表位,对荞麦致敏机理解析及预防治疗相关的过敏疾病具有重要意义。本文综述了荞麦中的主要过敏原(Fag e 1、Fag e 2、Fag e 3、Fag e 4、Fag e 5、Fag t 2、Fag t 3、Fag t 6)结构特征及其表位的研究进展,旨在为荞麦过敏深入研究与防治提供一定参考。展开更多
基金provided by the shale gas resource evaluation methods and exploration technology research project of the National Science and Technology Major Project of China(No.2016ZX05034)Graduate Innovative Engineering Funding Project of China University of Petroleum(East China)(No.YCX2021109)。
文摘It is difficult to determine the discharge stages in a fixed time of repetitive discharge underwater due to the arc formation process being susceptible to external environmental influences. This paper proposes a novel underwater discharge stage identification method based on the Strong Tracking Filter(STF) and impedance change characteristics. The time-varying equivalent circuit model of the discharge underwater is established based on the plasma theory analysis of the impedance change characteristics and mechanism of the discharge process. The STF is used to reduce the randomness of the impedance of repeated discharges underwater, and then the universal identification resistance data is obtained. Based on the resistance variation characteristics of the discriminating resistance of the pre-breakdown, main, and oscillatory discharge stages, the threshold values for determining the discharge stage are obtained. These include the threshold values for the resistance variation rate(K) and the moment(t).Experimental and error analysis results demonstrate the efficacy of this innovative method in discharge stage determination, with a maximum mean square deviation of Scrless than 1.761.
基金supported by the National Natural Science Foundation of China,China(Grant Nos.62173281,51975319,61801407)the State Key Laboratory of Tribology and Institute of Manufacturing Engineering at Tsinghua University。
文摘The electrification of vehicles puts forward higher requirements for the power management efficiency of integrated battery management systems as the primary or sole energy supply.In this paper,an efficient adaptive multi-time scale identification strategy is proposed to achieve high-fidelity modeling of complex kinetic processes inside the battery.More specifically,a second-order equivalent circuit model network considering variable characteristic frequency is constructed based on the high-frequency,medium-high-frequency,and low-frequency characteristics of the key kinetic processes.Then,two coupled sub-filters are developed based on forgetting factor recursive least squares and extended Kalman filtering methods and decoupled by the corresponding time-scale information.The coupled iterative calculation of the two sub-filter modules at different time scales is realized by the voltage response of the kinetic diffusion process.In addition,the driver of the low-frequency subalgorithm with the state of charge variation amount as the kernel is designed to realize the adaptive identification of the kinetic diffusion process parameters.Finally,the concept of dynamical parameter entropy is introduced and advocated to verify the physical meaning of the kinetic parameters.The experimental results under three operating conditions show that the mean absolute error and root-mean-square error metrics of the proposed strategy for voltage tracking can be limited to 13 and 16 mV,respectively.Additionally,from the entropy calculation results,the proposed method can reduce the dispersion of parameter identification results by a maximum of 40.72%and 70.05%,respectively,compared with the traditional fixed characteristic frequency algorithms.The proposed method paves the way for the subsequent development of adaptive state estimators and efficient embedded applications.
基金supported by the National Key Technology R&D Program under Grant No. 2012BAH18B05
文摘Internet traffic classification plays an important role in network management. Many approaches have been proposed to clas-sify different categories of Internet traffic. However, these approaches have specific us-age contexts that restrict their ability when they are applied in the current network envi-ronment. For example, the port based ap-proach cannot identify network applications with dynamic ports; the deep packet inspec-tion approach is invalid for encrypted network applications; and the statistical based approach is time-onsuming. In this paper, a novel tech-nique is proposed to classify different catego-ries of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multi-stage classifier. The experimental results demonstrate that this approach has high rec-ognition rate which is up to 98% and good performance of real-time for traffic identifica-tion.
基金financially supported by the Technical Research Program of Ministry of Public Security of the People’s Republic of China (2016jsyjb09)the 13th Five-Year National Key Research and Development Project (2017yfc080804)the Central-Level Basic Scientific Research Business Expenses Project (2021jb010)
文摘Based on GC-qqqMS/MS,a qualitative and quantitative analysis method for identifying characteristic markers in gasoline samples was established.According to the established method,different grades(#92,#95,#98)of gasoline samples collected from different regions(southern,central,northeastern,and northwestern China)were studied and analyzed.The results show that the gasolines can be classified by the relative contents of aromatics,naphthalene series,indene and other characteristic substances.On the basis of the high sensitivity and selectivity of GC-qqqMS/MS,the experiment has identified the characteristic substances,and used the characteristic-ratios methods as well as stoichiometric tools to study the grades and regional differences of gasoline products.It is conducive to the identification and classification of ILR in public security in fire cases,and can also meet the actual handling demand.
文摘Experimental modeling of a middle-rise office building via ambient modal identification is presented. A 200-DOF (Dimension of freedom) test model is designed to correlate with finite element mode. A newly developed frequency-spatial domain decomposition ( FSDD ) technique is used to identify modal characteristics of the full-size building by using ambient response measurements. In the interested frequency ranges of 0～4.5 Hz and 0～ 6.5 Hz altogether 9 bending and torsion modes are identified. As one of the major focuses of the project, the accurate damping estimation is conducted based on FSDD. The identified modal frequencies and mode shapes are utilized for finite element model tuning. Excellent agreement has been achieved with respect to the final tuned finite element (FE) model up to 9 modes.
基金Supported by the National Natural Science Foundation of China （No. 51079027）.
文摘In this paper, the vibration characteristics of the structure in the finite fluid domain are analyzed using a coupled finite element method. The added mass matrix is calculated with finite element method （FEM） by 8-node acoustic fluid elements. The vibration characteristics of the structure in the finite fluid domain are calculated combining structure FEM mass matrix. By writing relevant programs, the numerical analysis on vibration characteristics of a submerged cantilever rectangular plate in finite fluid domain and loaded ship model is performed. A modal identification experiment for the loaded ship model in air and in water is conducted and the experiment results verify the reliability of the numerical analysis. The numerical method can be used for further research on vibration characteristics and acoustic radiation problems of the structure in the finite fluid domain.
文摘荞麦是一种常见的食物过敏原,能够引发呼吸系统、消化系统、循环系统等方面的疾病,严重时可导致过敏性休克甚至死亡。明确荞麦中的主要过敏蛋白,确定其中的过敏原表位,对荞麦致敏机理解析及预防治疗相关的过敏疾病具有重要意义。本文综述了荞麦中的主要过敏原(Fag e 1、Fag e 2、Fag e 3、Fag e 4、Fag e 5、Fag t 2、Fag t 3、Fag t 6)结构特征及其表位的研究进展,旨在为荞麦过敏深入研究与防治提供一定参考。
