A surface acoustic wave(SAW)gyroscope measures the rate of rotational angular velocity by exploiting a phenomenon known as the SAW gyroscope effect.Such a gyroscope is a great candidate for application in harsh enviro...A surface acoustic wave(SAW)gyroscope measures the rate of rotational angular velocity by exploiting a phenomenon known as the SAW gyroscope effect.Such a gyroscope is a great candidate for application in harsh environments because of the simplification of the suspension vibration mechanism necessary for traditional microelectromechanical system(MEMS)gyroscopes.Here,for the first time,we propose a novel toroidal standing-wave-mode SAW gyroscope using focused interdigitated transducers(FIDTs).Unlike traditional SAW gyroscopes that use linear IDTs to generate surface acoustic waves,which cause beam deflection and result in energy dissipation,this study uses FIDTs to concentrate the SAW energy based on structural features,resulting in better focusing performance and increased SAW amplitude.The experimental results reveal that the sensitivity of the structure is 1.51µV/(°/s),and the bias instability is 0.77°/s,which are improved by an order of magnitude compared to those of a traditional SAW gyroscope.Thus,the FIDT component can enhance the performance of the SAW gyroscope,demonstrating its superiority for angular velocity measurements.This work provides new insights into improving the sensitivity and performance of SAW gyroscopes.展开更多
交流电磁场检测(alternating current field measurement, ACFM)技术广泛应用于制造业等工业领域中金属结构物的缺陷检测。针对单传感器在非预知缺陷检测过程中存在的角度偏转及裂纹定位等问题展开了研究,首先通过COMSOL Multiphysics...交流电磁场检测(alternating current field measurement, ACFM)技术广泛应用于制造业等工业领域中金属结构物的缺陷检测。针对单传感器在非预知缺陷检测过程中存在的角度偏转及裂纹定位等问题展开了研究,首先通过COMSOL Multiphysics仿真结果可知:场强的X和Y方向分量在角度偏转的过程中存在信号互补的规律,然后通过建立比例因子进而实现了数据增广型灰色神经网络模型(data augmented grey neural network model, DA-GNNM)的预测,同时模拟预测对比回归预测可知DA-GNNM模型的预测效果较优。此外通过多梯度偏转仿真实现了偏转裂纹的重构,其次通过搭建实验平台以及信号特征提取等工作验证了DA-GNNM预测模型的合理性,平均预测误差2.56%;最后通过预测角度进一步改善了非平行检测过程中裂纹重构图像的偏转问题。展开更多
The utility poles of an electric power distribution system are frequently damaged by wind-related disasters.This study notes that the wooden poles are particularly vulnerable to such disasters and the failures of the ...The utility poles of an electric power distribution system are frequently damaged by wind-related disasters.This study notes that the wooden poles are particularly vulnerable to such disasters and the failures of the poles can cause a network-level failure leading to short-or longterm power outages. To mitigate the problem, this study proposes a framework for measuring the resilience of the wooden utility poles based on the angular deflection of a pole due to the wind force. Given the existing inclination angle of a pole, the angular deflection is measured by finite element analysis using ANSYS~? Workbench^1 to determine the resilience area under various wind speeds. For this, the conditions of load and support for a pole, which are called boundary conditions in ANSYS~?, are generated. The proposed framework also includes an approach to cost–benefit analysis that compares different strategies for corrective action. The results of the case study in which the framework was applied show that the proposed framework can be effectively utilized by electric power distribution companies to increase the resilience of their systems.展开更多
The utility poles of electric power distribution lines are very vulnerable to many natural hazards, while power outages due to pole failures can lead to adverse economic and social consequences. Utility companies,ther...The utility poles of electric power distribution lines are very vulnerable to many natural hazards, while power outages due to pole failures can lead to adverse economic and social consequences. Utility companies,therefore, need to monitor the conditions of poles regularly and predict their future conditions accurately and promptly to operate the distribution system continuously and safely.This article presents a novel pole monitoring method that uses state-of-the-art deep learning and computer vision methods to meet the need. The proposed method automatically captures the current pole inclination angles using an unmanned aerial vehicle. The method calculates the bending moment exerted on the poles due to wind and gravitational forces, as well as cable weight, to compare it with the moment of rupture. The method also includes a machine learning-based model that is built by using a support vector machine to predict the resilience conditions of a pole after a wind event in a faster manner. The three modules of the proposed method are effective tools to classify pole conditions and are expected to enable utility companies to increase the resilience of their systems.展开更多
基金supported by the Natural Science Basic Research Plan in Shaanxi Province of China(Program No.2023JC-XJ-07)the National Key Research and Development Program of China(No.2018YFB2002602)the National Natural Science Foundation of China(No.52375577 and No.52075454).
文摘A surface acoustic wave(SAW)gyroscope measures the rate of rotational angular velocity by exploiting a phenomenon known as the SAW gyroscope effect.Such a gyroscope is a great candidate for application in harsh environments because of the simplification of the suspension vibration mechanism necessary for traditional microelectromechanical system(MEMS)gyroscopes.Here,for the first time,we propose a novel toroidal standing-wave-mode SAW gyroscope using focused interdigitated transducers(FIDTs).Unlike traditional SAW gyroscopes that use linear IDTs to generate surface acoustic waves,which cause beam deflection and result in energy dissipation,this study uses FIDTs to concentrate the SAW energy based on structural features,resulting in better focusing performance and increased SAW amplitude.The experimental results reveal that the sensitivity of the structure is 1.51µV/(°/s),and the bias instability is 0.77°/s,which are improved by an order of magnitude compared to those of a traditional SAW gyroscope.Thus,the FIDT component can enhance the performance of the SAW gyroscope,demonstrating its superiority for angular velocity measurements.This work provides new insights into improving the sensitivity and performance of SAW gyroscopes.
文摘The utility poles of an electric power distribution system are frequently damaged by wind-related disasters.This study notes that the wooden poles are particularly vulnerable to such disasters and the failures of the poles can cause a network-level failure leading to short-or longterm power outages. To mitigate the problem, this study proposes a framework for measuring the resilience of the wooden utility poles based on the angular deflection of a pole due to the wind force. Given the existing inclination angle of a pole, the angular deflection is measured by finite element analysis using ANSYS~? Workbench^1 to determine the resilience area under various wind speeds. For this, the conditions of load and support for a pole, which are called boundary conditions in ANSYS~?, are generated. The proposed framework also includes an approach to cost–benefit analysis that compares different strategies for corrective action. The results of the case study in which the framework was applied show that the proposed framework can be effectively utilized by electric power distribution companies to increase the resilience of their systems.
文摘The utility poles of electric power distribution lines are very vulnerable to many natural hazards, while power outages due to pole failures can lead to adverse economic and social consequences. Utility companies,therefore, need to monitor the conditions of poles regularly and predict their future conditions accurately and promptly to operate the distribution system continuously and safely.This article presents a novel pole monitoring method that uses state-of-the-art deep learning and computer vision methods to meet the need. The proposed method automatically captures the current pole inclination angles using an unmanned aerial vehicle. The method calculates the bending moment exerted on the poles due to wind and gravitational forces, as well as cable weight, to compare it with the moment of rupture. The method also includes a machine learning-based model that is built by using a support vector machine to predict the resilience conditions of a pole after a wind event in a faster manner. The three modules of the proposed method are effective tools to classify pole conditions and are expected to enable utility companies to increase the resilience of their systems.
