全聚焦算法依靠信号的幅度信息进行延迟叠加(delay and sum,DAS)成像,实际应用中信号并非总能满足相干叠加这一前提,而非相干信号的叠加导致噪声和伪影。文章提出一种循环相干因子(circular coherence factor,CCF)加权的延迟乘和(delay ...全聚焦算法依靠信号的幅度信息进行延迟叠加(delay and sum,DAS)成像,实际应用中信号并非总能满足相干叠加这一前提,而非相干信号的叠加导致噪声和伪影。文章提出一种循环相干因子(circular coherence factor,CCF)加权的延迟乘和(delay multiply and sum,DMAS)CCF-DMAS优化算法,实现薄板中缺陷的兰姆波全聚焦成像。该方法考虑接收阵元间的空间相干性,对接收信号进行相乘耦合,利用数据中的相位信息计算相干因子实现自适应加权,以扩大相干和非相干信号间的差异,从而达到缩窄主瓣,减少旁瓣,提高成像分辨率的效果。建立超声阵列发射、接收实验系统,通过楔块耦合,在含通孔缺陷的锆合金薄板上激发S_(0)模态兰姆波,捕获全矩阵数据;通过CCF-DMAS算法对采集的数据相位加权,生成新的频率分量;利用带通滤波保留二次谐波分量进行全聚焦成像。实验结果表明:与DAS和DMAS全聚焦成像算法相比,CCF-DMAS全聚焦优化算法能够有效抑制噪声和伪影,信噪比提高约39%和22%,阵列性能指数提高约86%和69%,为薄板无损检测的后处理提供了一种有效的改进方案。展开更多
Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional ...Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.展开更多
Graphene-doped CuO(rGO-CuO)nanocomposites with flower shapes were prepared by an improved solvothermal method.The samples were characterized by X-ray diffraction,X-ray photoelectron spectroscopy and UV–visible spectr...Graphene-doped CuO(rGO-CuO)nanocomposites with flower shapes were prepared by an improved solvothermal method.The samples were characterized by X-ray diffraction,X-ray photoelectron spectroscopy and UV–visible spectroscopy.The active species in the degradation reaction of rGO-CuO composites under ultrasonic irradiation were detected by electron paramagnetic resonance.On the basis of comparative experiments,the photodegradation mechanisms of two typical dyes,Rhodamine B(Rh B)and methyl orange(MO),were proposed.The results demonstrated that the doped CuO could improve the degradation efficiency.The catalytic degradation efficiency of rGO-CuO(2:1)to rhodamine B(RhB)and methyl orange(MO)reached 90%and 87%respectively,which were 2.1 times and 4.4 times of the reduced graphene oxide.Through the first-principles and other theories,we give the reasons for the enhanced catalytic performance of rGO-CuO:combined with internal and external factors,rGO-CuO under ultrasound could produce more hole and active sites that could interact with the OH·in pollutant molecules to achieve degradation.The rGO-CuO nanocomposite has a simple preparation process and low price,and has a high efficiency of degrading water pollution products and no secondary pollution products.It has a low-cost and high-efficiency application prospect in water pollution industrial production and life.展开更多
文摘全聚焦算法依靠信号的幅度信息进行延迟叠加(delay and sum,DAS)成像,实际应用中信号并非总能满足相干叠加这一前提,而非相干信号的叠加导致噪声和伪影。文章提出一种循环相干因子(circular coherence factor,CCF)加权的延迟乘和(delay multiply and sum,DMAS)CCF-DMAS优化算法,实现薄板中缺陷的兰姆波全聚焦成像。该方法考虑接收阵元间的空间相干性,对接收信号进行相乘耦合,利用数据中的相位信息计算相干因子实现自适应加权,以扩大相干和非相干信号间的差异,从而达到缩窄主瓣,减少旁瓣,提高成像分辨率的效果。建立超声阵列发射、接收实验系统,通过楔块耦合,在含通孔缺陷的锆合金薄板上激发S_(0)模态兰姆波,捕获全矩阵数据;通过CCF-DMAS算法对采集的数据相位加权,生成新的频率分量;利用带通滤波保留二次谐波分量进行全聚焦成像。实验结果表明:与DAS和DMAS全聚焦成像算法相比,CCF-DMAS全聚焦优化算法能够有效抑制噪声和伪影,信噪比提高约39%和22%,阵列性能指数提高约86%和69%,为薄板无损检测的后处理提供了一种有效的改进方案。
基金supported by the National Natural Science Foundation of China under(Grant No.52175531)in part by the Science and Technology Research Program of Chongqing Municipal Education Commission under Grant(Grant Nos.KJQN202000605 and KJZD-M202000602)。
文摘Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.
基金supported by the National Natural Science Foundation of China (No.11375136)。
文摘Graphene-doped CuO(rGO-CuO)nanocomposites with flower shapes were prepared by an improved solvothermal method.The samples were characterized by X-ray diffraction,X-ray photoelectron spectroscopy and UV–visible spectroscopy.The active species in the degradation reaction of rGO-CuO composites under ultrasonic irradiation were detected by electron paramagnetic resonance.On the basis of comparative experiments,the photodegradation mechanisms of two typical dyes,Rhodamine B(Rh B)and methyl orange(MO),were proposed.The results demonstrated that the doped CuO could improve the degradation efficiency.The catalytic degradation efficiency of rGO-CuO(2:1)to rhodamine B(RhB)and methyl orange(MO)reached 90%and 87%respectively,which were 2.1 times and 4.4 times of the reduced graphene oxide.Through the first-principles and other theories,we give the reasons for the enhanced catalytic performance of rGO-CuO:combined with internal and external factors,rGO-CuO under ultrasound could produce more hole and active sites that could interact with the OH·in pollutant molecules to achieve degradation.The rGO-CuO nanocomposite has a simple preparation process and low price,and has a high efficiency of degrading water pollution products and no secondary pollution products.It has a low-cost and high-efficiency application prospect in water pollution industrial production and life.
