A wind turbine system equipped with a tuned liquid column damper （TLCD） is comprehensively studied via shaking table tests using a 1/13-scaled model. The effects of wind and wave actions are considered by inputting ...A wind turbine system equipped with a tuned liquid column damper （TLCD） is comprehensively studied via shaking table tests using a 1/13-scaled model. The effects of wind and wave actions are considered by inputting response- equivalent accelerations on the shaking table. The test results show that the control effect of the TLCD system is significant in reducing the responses under both wind-wave equivalent loads and ground motions, but obviously varies for different inputs, Further, a blade-hub-tower integrated numerical model for the wind turbine system is established. The model is capable of considering the rotational effect of blades by combining Kane＇s equation with the finite element method. The responses of the wind tower equipped with TLCD devices are numerically obtained and compared to the test results, showing that under both controlled and uncontrolled conditions with and without blades＇ rotation, the corresponding responses exhibit good agreement. This demonstrates that the proposed numerical model performs well in capturing the wind-wave coupled response of the offshore wind turbine systems under control. Both numerical and experimental results show that the TLCD system can significantly reduce the structural response and thus improve the safety and serviceability of the offshore wind turbine tower systems. Additional issues that require further study are discussed.展开更多
针对远距离复杂场景下红外弱小目标信噪比低导致目标检测虚警率高的问题,提出了一种时域与空域滤波相融合的红外弱小目标检测方法。采用相对局部对比度算法(Relative Local Contrast Measure,RLCM)增强目标信噪比,抑制高亮度背景;利用...针对远距离复杂场景下红外弱小目标信噪比低导致目标检测虚警率高的问题,提出了一种时域与空域滤波相融合的红外弱小目标检测方法。采用相对局部对比度算法(Relative Local Contrast Measure,RLCM)增强目标信噪比,抑制高亮度背景;利用目标的时空相关性,运用时域局部差分算法(Temporal Local Difference Algorithm,TLCD)增强目标,消除固定噪点。融合空域和时域的检测结果获得时空相对局部对比度图(Spatial-Temporal Relative Local Contrast Map,STRLCM),通过自适应阈值分割提取待检测的真实目标。实验结果表明,与现有算法相比,所提算法可以极大地降低虚警率同时保持较高的检测效果。展开更多
基金National Natural Science Foundation of China Under Grant No.11172210National Hi-Tech Development Plan(863 Plan)Under Grant No.2008AA05Z413+2 种基金the Fundamental Fund for Central Universitiesthe Shuguang Program of Shanghai Citythe State Key Laboratory of Disaster Reduction in Civil Engineering Under Grant Nos.SLDRCE14-A-06 and SLDRCE14-B-17
文摘A wind turbine system equipped with a tuned liquid column damper （TLCD） is comprehensively studied via shaking table tests using a 1/13-scaled model. The effects of wind and wave actions are considered by inputting response- equivalent accelerations on the shaking table. The test results show that the control effect of the TLCD system is significant in reducing the responses under both wind-wave equivalent loads and ground motions, but obviously varies for different inputs, Further, a blade-hub-tower integrated numerical model for the wind turbine system is established. The model is capable of considering the rotational effect of blades by combining Kane＇s equation with the finite element method. The responses of the wind tower equipped with TLCD devices are numerically obtained and compared to the test results, showing that under both controlled and uncontrolled conditions with and without blades＇ rotation, the corresponding responses exhibit good agreement. This demonstrates that the proposed numerical model performs well in capturing the wind-wave coupled response of the offshore wind turbine systems under control. Both numerical and experimental results show that the TLCD system can significantly reduce the structural response and thus improve the safety and serviceability of the offshore wind turbine tower systems. Additional issues that require further study are discussed.
文摘针对远距离复杂场景下红外弱小目标信噪比低导致目标检测虚警率高的问题,提出了一种时域与空域滤波相融合的红外弱小目标检测方法。采用相对局部对比度算法(Relative Local Contrast Measure,RLCM)增强目标信噪比,抑制高亮度背景;利用目标的时空相关性,运用时域局部差分算法(Temporal Local Difference Algorithm,TLCD)增强目标,消除固定噪点。融合空域和时域的检测结果获得时空相对局部对比度图(Spatial-Temporal Relative Local Contrast Map,STRLCM),通过自适应阈值分割提取待检测的真实目标。实验结果表明,与现有算法相比,所提算法可以极大地降低虚警率同时保持较高的检测效果。
