To study the energy storage and dissipation characteristics of deep rock under two-dimensional compression with constant confining pressure,the single cyclic loading-unloading two-dimensional compression tests were pe...To study the energy storage and dissipation characteristics of deep rock under two-dimensional compression with constant confining pressure,the single cyclic loading-unloading two-dimensional compression tests were performed on granite specimens with two height-to-width(H/W)ratios under five confining pressures.Three energy density parameters(input energy density,elastic energy density and dissipated energy density)in the axial and lateral directions of granite specimens under different confining pressures were calculated using the area integral method.The experimental results show that,for the specimens with a specific H/W ratio,these three energy density parameters in the axial and lateral directions increase nonlinearly with the confining pressure as quadratic polynomial functions.Under constant confining pressure compression,the linear energy storage law of granite specimens in the axial and lateral directions was founded.Using the linear energy storage law in different directions,the elastic energy density in various directions(axial elastic energy density,lateral elastic energy density and total elastic energy density)of granite under any specific confining pressures can be calculated.When the H/W ratio varies from 1:1 to 2:1,the lateral compression energy storage coefficient increases and the corresponding axial compression energy storage coefficient decreases,while the total compression energy storage coefficient is almost independent of the H/W ratio.展开更多
In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is propose...In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is proposed in this paper.The animal sound is turned into spectrogram to show the energy,time and frequency characteristics.The sub-band frequency division and sub-band energy division are carried out on the spectrogram for extracting the statistical characteristic of energy and frequency,so as to achieve sub-band power distribution(SPD)and sub-band division.Radon transform(RT)and discrete wavelet transform(DWT)are employed to obtain the important projection coefficients,and the energy values of sub-band frequencies are calculated to extract the sub-band frequency feature.The E-F feature is formed by combining the SPD feature and sub-band energy value feature.The classification is achieved by support vector machine(SVM)classifier.The experimental results show that the method can achieve better recognition effect even when the SNR is below10 dB.展开更多
随着向新型能源体系的转型加速,亟待开展对多元负荷用户的复杂用能特性分析的深入研究。提出了一种综合考量电、冷、热多元负荷耦合特性的用户用能特性标签库构建技术及用户画像方法。首先运用快速相关性滤波算法剔除高冗余低相关特征,...随着向新型能源体系的转型加速,亟待开展对多元负荷用户的复杂用能特性分析的深入研究。提出了一种综合考量电、冷、热多元负荷耦合特性的用户用能特性标签库构建技术及用户画像方法。首先运用快速相关性滤波算法剔除高冗余低相关特征,并通过随机森林和递归式特征消除算法精选出具有强区分能力的用能特征。在聚类阶段,改进的自适应三支密度峰值聚类算法(three-way adaptive density peak clustering,3W-ADPC)通过结合自适应近邻搜索和三支聚类算法提升负荷聚类效果。实证结果表明,所提方法具备在计算效率和聚类精度上的双重优势,能够精准揭示多元负荷用户综合用能特性和深层次信息,证实所提方法在多元负荷用户行为研究中的实用价值。展开更多
基金Projects(41877272,51974359)supported by the National Natural Science Foundation of China。
文摘To study the energy storage and dissipation characteristics of deep rock under two-dimensional compression with constant confining pressure,the single cyclic loading-unloading two-dimensional compression tests were performed on granite specimens with two height-to-width(H/W)ratios under five confining pressures.Three energy density parameters(input energy density,elastic energy density and dissipated energy density)in the axial and lateral directions of granite specimens under different confining pressures were calculated using the area integral method.The experimental results show that,for the specimens with a specific H/W ratio,these three energy density parameters in the axial and lateral directions increase nonlinearly with the confining pressure as quadratic polynomial functions.Under constant confining pressure compression,the linear energy storage law of granite specimens in the axial and lateral directions was founded.Using the linear energy storage law in different directions,the elastic energy density in various directions(axial elastic energy density,lateral elastic energy density and total elastic energy density)of granite under any specific confining pressures can be calculated.When the H/W ratio varies from 1:1 to 2:1,the lateral compression energy storage coefficient increases and the corresponding axial compression energy storage coefficient decreases,while the total compression energy storage coefficient is almost independent of the H/W ratio.
基金Supported by the National Natural Science Foundation of China(No.61075022)
文摘In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is proposed in this paper.The animal sound is turned into spectrogram to show the energy,time and frequency characteristics.The sub-band frequency division and sub-band energy division are carried out on the spectrogram for extracting the statistical characteristic of energy and frequency,so as to achieve sub-band power distribution(SPD)and sub-band division.Radon transform(RT)and discrete wavelet transform(DWT)are employed to obtain the important projection coefficients,and the energy values of sub-band frequencies are calculated to extract the sub-band frequency feature.The E-F feature is formed by combining the SPD feature and sub-band energy value feature.The classification is achieved by support vector machine(SVM)classifier.The experimental results show that the method can achieve better recognition effect even when the SNR is below10 dB.
文摘随着向新型能源体系的转型加速,亟待开展对多元负荷用户的复杂用能特性分析的深入研究。提出了一种综合考量电、冷、热多元负荷耦合特性的用户用能特性标签库构建技术及用户画像方法。首先运用快速相关性滤波算法剔除高冗余低相关特征,并通过随机森林和递归式特征消除算法精选出具有强区分能力的用能特征。在聚类阶段,改进的自适应三支密度峰值聚类算法(three-way adaptive density peak clustering,3W-ADPC)通过结合自适应近邻搜索和三支聚类算法提升负荷聚类效果。实证结果表明,所提方法具备在计算效率和聚类精度上的双重优势,能够精准揭示多元负荷用户综合用能特性和深层次信息,证实所提方法在多元负荷用户行为研究中的实用价值。
