The effectiveness of deep-bed filtration with respect to suspension formed during the preceding processes is evaluated by the test of filterability. The properties and concentration of the suspension being filtered ar...The effectiveness of deep-bed filtration with respect to suspension formed during the preceding processes is evaluated by the test of filterability. The properties and concentration of the suspension being filtered are affected by the efficiency of the preceding aggregation and separation processes. The basic principles of the test of filterability are based on the mechanistic model of filtration. The equations in the mathematical model of the mechanistic conception of filtration are derived from the theory of filtration. The arrangement of the pilot filtration plant for the determination of filterability of flocculent suspension is presented in this paper. The test of filterability is carried out with a thin-layer filter element. The design of a filter element arrangement and its installation are also disclosed in this paper. The inter-dependence of the coefficient of filtration efficiency on the specific volume of intercepted suspensions, filter media grain sizes and different filtration velocities are graphically presented. In addition, the effect of the filter bed clogging resulting from the properties of different suspensions on the head loss generated, the length of filtration cycle and quality of filtrate produced are also shown in this paper.展开更多
为了更好地应对多目标跟踪联合检测算法面对的场景遮挡问题,通过结合注意力机制,提出基于Transformer的运动预测和数据关联(Transformer-based motion prediction and data association,TrMPDA)联合检测跟踪方法。首先,考虑到置信度检...为了更好地应对多目标跟踪联合检测算法面对的场景遮挡问题,通过结合注意力机制,提出基于Transformer的运动预测和数据关联(Transformer-based motion prediction and data association,TrMPDA)联合检测跟踪方法。首先,考虑到置信度检测框的质量以及深度特征的视觉表示能力对遮挡场景下跟踪效果的影响,重新设计TrMPDA骨干网络中的ResNet卷积模块,利用相邻像素和长距离像素间丰富的上下文关系指导动态注意矩阵的学习,增强深度特征的视觉表示能力,并通过边界框的宽和高估计边界框位置,提高置信度检测框的质量。其次,在本文方法中保留所有的检测框,根据阈值大小划分高置信度检测框和低置信度检测框,分别执行数据关联匹配,以此来平衡由于遮挡导致的检测框低置信度。实验结果表明本文提出的TrMPDA方法与典型的Sort、JDE、Fairmot等多目标跟踪算法相比具有更好的跟踪效果,能够应对多目标跟踪中目标遮挡的问题。展开更多
Harmonic wavelets not only possess the traditional advantages of a wavelet function,they also have other merits such as clear expressions,more flexible time-frequency divisions,a simple transformation algorithm,a fine...Harmonic wavelets not only possess the traditional advantages of a wavelet function,they also have other merits such as clear expressions,more flexible time-frequency divisions,a simple transformation algorithm,a finer box-like frequency spectrum and others.Given the frequency distribution characteristics of the nondestructive testing signals from a rockbolt support system and based on the discrete harmonic wavelet transformation theory,we have effectively abstracted signals from frequency ranges concerned by removing useless high and low frequency signals from the testing signals of the rockbolt support system and obtained filtered signals with a reconstruction algorithm of harmonic wavelets.Finally,we applied the harmonic wavelet transformation in filtering analog signals and measured response signals of rockbolts.The results indicate that harmonic wavelets also have excellent filtering characteristics.展开更多
文摘The effectiveness of deep-bed filtration with respect to suspension formed during the preceding processes is evaluated by the test of filterability. The properties and concentration of the suspension being filtered are affected by the efficiency of the preceding aggregation and separation processes. The basic principles of the test of filterability are based on the mechanistic model of filtration. The equations in the mathematical model of the mechanistic conception of filtration are derived from the theory of filtration. The arrangement of the pilot filtration plant for the determination of filterability of flocculent suspension is presented in this paper. The test of filterability is carried out with a thin-layer filter element. The design of a filter element arrangement and its installation are also disclosed in this paper. The inter-dependence of the coefficient of filtration efficiency on the specific volume of intercepted suspensions, filter media grain sizes and different filtration velocities are graphically presented. In addition, the effect of the filter bed clogging resulting from the properties of different suspensions on the head loss generated, the length of filtration cycle and quality of filtrate produced are also shown in this paper.
文摘为了更好地应对多目标跟踪联合检测算法面对的场景遮挡问题,通过结合注意力机制,提出基于Transformer的运动预测和数据关联(Transformer-based motion prediction and data association,TrMPDA)联合检测跟踪方法。首先,考虑到置信度检测框的质量以及深度特征的视觉表示能力对遮挡场景下跟踪效果的影响,重新设计TrMPDA骨干网络中的ResNet卷积模块,利用相邻像素和长距离像素间丰富的上下文关系指导动态注意矩阵的学习,增强深度特征的视觉表示能力,并通过边界框的宽和高估计边界框位置,提高置信度检测框的质量。其次,在本文方法中保留所有的检测框,根据阈值大小划分高置信度检测框和低置信度检测框,分别执行数据关联匹配,以此来平衡由于遮挡导致的检测框低置信度。实验结果表明本文提出的TrMPDA方法与典型的Sort、JDE、Fairmot等多目标跟踪算法相比具有更好的跟踪效果,能够应对多目标跟踪中目标遮挡的问题。
基金Financial support for this work provided by the National Basic Research Program of China (No.2007CB209400)the 111 Project of China (No.B07028)+2 种基金the Key Program of National Natural Science Foundation of China(No.50834004)the National Natural Science Foundation of China (No.50874104)the Natural Science Foundation of Jiangsu Province(No.BK2006040)
文摘Harmonic wavelets not only possess the traditional advantages of a wavelet function,they also have other merits such as clear expressions,more flexible time-frequency divisions,a simple transformation algorithm,a finer box-like frequency spectrum and others.Given the frequency distribution characteristics of the nondestructive testing signals from a rockbolt support system and based on the discrete harmonic wavelet transformation theory,we have effectively abstracted signals from frequency ranges concerned by removing useless high and low frequency signals from the testing signals of the rockbolt support system and obtained filtered signals with a reconstruction algorithm of harmonic wavelets.Finally,we applied the harmonic wavelet transformation in filtering analog signals and measured response signals of rockbolts.The results indicate that harmonic wavelets also have excellent filtering characteristics.
