Installing the splitter plates is a passive aerodynamic solution for eliminating vortex-induced vibration (VIV). However, the influences of splitter plates on the VIV and aerostatic performances are more complicated d...Installing the splitter plates is a passive aerodynamic solution for eliminating vortex-induced vibration (VIV). However, the influences of splitter plates on the VIV and aerostatic performances are more complicated due to aerodynamic interference between highway and railway decks. To study the effects of splitter plates, wind tunnel experiments for measuring VIV and aerostatic forces of twin decks under two opposite flow directions were conducted, while the surrounding flow and wind pressure of static twin decks with and without splitter plates are numerically simulated. The results showed that the incoming flow direction affects the VIV response and aerostatic coefficients. The highway deck has poor vertical and torsional VIV, and the VIV region and amplitude are different under different directions. While the railway deck only has vertical VIV when located upstream. The splitter plates can impede the process of vortex generation, shedding and impinging at the gap between twin deck, and significantly reducing the surface fluctuating pressure coefficient, thus effectively suppressing the VIV of twin decks. While, the splitter plates hurt the upstream deck regarding static wind stability and have little effect on the downstream deck. The splitter plates of appropriate width are recommended to improve VIV performances in twin parallel bridges.展开更多
[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been propo...[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been proposed for monitoring cow ruminant behavior,including video surveillance,sound recognition,and sensor monitoring methods.How‐ever,the application of edge device gives rise to the issue of inadequate real-time performance.To reduce the volume of data transmission and cloud computing workload while achieving real-time monitoring of dairy cow rumination behavior,a real-time monitoring method was proposed for cow ruminant behavior based on edge computing.[Methods]Autono‐mously designed edge devices were utilized to collect and process six-axis acceleration signals from cows in real-time.Based on these six-axis data,two distinct strategies,federated edge intelligence and split edge intelligence,were investigat‐ed for the real-time recognition of cow ruminant behavior.Focused on the real-time recognition method for cow ruminant behavior leveraging federated edge intelligence,the CA-MobileNet v3 network was proposed by enhancing the MobileNet v3 network with a collaborative attention mechanism.Additionally,a federated edge intelligence model was designed uti‐lizing the CA-MobileNet v3 network and the FedAvg federated aggregation algorithm.In the study on split edge intelli‐gence,a split edge intelligence model named MobileNet-LSTM was designed by integrating the MobileNet v3 network with a fusion collaborative attention mechanism and the Bi-LSTM network.[Results and Discussions]Through compara‐tive experiments with MobileNet v3 and MobileNet-LSTM,the federated edge intelligence model based on CA-Mo‐bileNet v3 achieved an average Precision rate,Recall rate,F1-Score,Specificity,and Accuracy of 97.1%,97.9%,97.5%,98.3%,and 98.2%,respectively,yielding the best recognition performance.[Conclusions]It is provided a real-time and effective method for monitoring cow ruminant behavior,and the proposed federated edge intelligence model can be ap‐plied in practical settings.展开更多
基金Projects(51925808,52078504,51822803) supported by the National Natural Science Foundation of ChinaProject(2022JJ10082) supported by the Natural Science Foundation of Hunan Province,China+1 种基金Project(N2022Z004) supported by the Research on Technology Development Trend and Key Common Problems in Railway,ChinaProject(Xplorer Prize 2021) supported by the Tencent Foundation,China。
文摘Installing the splitter plates is a passive aerodynamic solution for eliminating vortex-induced vibration (VIV). However, the influences of splitter plates on the VIV and aerostatic performances are more complicated due to aerodynamic interference between highway and railway decks. To study the effects of splitter plates, wind tunnel experiments for measuring VIV and aerostatic forces of twin decks under two opposite flow directions were conducted, while the surrounding flow and wind pressure of static twin decks with and without splitter plates are numerically simulated. The results showed that the incoming flow direction affects the VIV response and aerostatic coefficients. The highway deck has poor vertical and torsional VIV, and the VIV region and amplitude are different under different directions. While the railway deck only has vertical VIV when located upstream. The splitter plates can impede the process of vortex generation, shedding and impinging at the gap between twin deck, and significantly reducing the surface fluctuating pressure coefficient, thus effectively suppressing the VIV of twin decks. While, the splitter plates hurt the upstream deck regarding static wind stability and have little effect on the downstream deck. The splitter plates of appropriate width are recommended to improve VIV performances in twin parallel bridges.
文摘[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been proposed for monitoring cow ruminant behavior,including video surveillance,sound recognition,and sensor monitoring methods.How‐ever,the application of edge device gives rise to the issue of inadequate real-time performance.To reduce the volume of data transmission and cloud computing workload while achieving real-time monitoring of dairy cow rumination behavior,a real-time monitoring method was proposed for cow ruminant behavior based on edge computing.[Methods]Autono‐mously designed edge devices were utilized to collect and process six-axis acceleration signals from cows in real-time.Based on these six-axis data,two distinct strategies,federated edge intelligence and split edge intelligence,were investigat‐ed for the real-time recognition of cow ruminant behavior.Focused on the real-time recognition method for cow ruminant behavior leveraging federated edge intelligence,the CA-MobileNet v3 network was proposed by enhancing the MobileNet v3 network with a collaborative attention mechanism.Additionally,a federated edge intelligence model was designed uti‐lizing the CA-MobileNet v3 network and the FedAvg federated aggregation algorithm.In the study on split edge intelli‐gence,a split edge intelligence model named MobileNet-LSTM was designed by integrating the MobileNet v3 network with a fusion collaborative attention mechanism and the Bi-LSTM network.[Results and Discussions]Through compara‐tive experiments with MobileNet v3 and MobileNet-LSTM,the federated edge intelligence model based on CA-Mo‐bileNet v3 achieved an average Precision rate,Recall rate,F1-Score,Specificity,and Accuracy of 97.1%,97.9%,97.5%,98.3%,and 98.2%,respectively,yielding the best recognition performance.[Conclusions]It is provided a real-time and effective method for monitoring cow ruminant behavior,and the proposed federated edge intelligence model can be ap‐plied in practical settings.
