Wind Speed and Direction Measurement Based on Three Mutually Transmitting Ultrasonic Sensors

Shan, Zebiao; Xie, Xiaoran; Liu, Xiaosong

doi:10.1109/lgrs.2023.3236005

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…These restrictions complicate solar energy resources management and integration of solar energy into the grid. Conventional wind sensors, such as cup anemometers or wind vanes, may have limitations in capturing subtle changes in wind speed and direction, particularly in complex wind flow conditions or at high altitudes [45,46]. As a result, inaccurate wind energy predictions lead to suboptimal utilization of wind power resources.…”

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confidence: 99%

Sensors in Civil Engineering: From Existing Gaps to Quantum Opportunities

Kantsepolsky,

Aviv

2024

Smart Cities

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The vital role of civil engineering is to enable the development of modern cities and establish foundations for smart and sustainable urban environments of the future. Advanced sensing technologies are among the instrumental methods used to enhance the performance of civil engineering infrastructures and address the multifaceted challenges of future cities. Through this study, we discussed the shortcomings of traditional sensors in four primary civil engineering domains: construction, energy, water, and transportation. Then, we investigated and summarized the potential of quantum sensors to contribute to and revolutionize the management of civil engineering infrastructures. For the water sector, advancements are expected in monitoring water quality and pressure in water and sewage infrastructures. In the energy sector, quantum sensors may facilitate renewables integration and improve grid stability and buildings’ energy efficiency. The most promising progress in the construction field is the ability to identify subsurface density and underground structures. In transportation, these sensors create many fresh avenues for real-time traffic management and smart mobility solutions. As one of the first-in-the-field studies offering the adoption of quantum sensors across four primary domains of civil engineering, this research establishes the basis for the discourse about the scope and timeline for deploying quantum sensors to real-world applications towards the quantum transformation of civil engineering.

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confidence: 99%

Sensors in Civil Engineering: From Existing Gaps to Quantum Opportunities

Kantsepolsky,

Aviv

2024

Smart Cities

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“…Although ultrasonic anemometers have been extensively studied, certain measurement errors still exist. Not only do these errors come from the structure of the ultrasonic anemometer, but they may also be caused by the external special measurement environment (Ghahramani et al, 2019;Shan et al, 2023). Common error elimination methods include: (1) employing high-50 quality and high-precision sensors and components to improve measurement accuracy (Knöller et al, 2024;White et al, 2020);…”

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A quality control method based on physical constraints and data-driven collaborative for wind observations along high-speed railway lines

Xiong,

Chen,

Zhang

et al. 2024

Preprint

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Abstract. This study proposed a new quality control method via physical constraints and data-driven collaborative artificial intelligence (PD-BX) to reduce wind speed measurement errors caused by the complex environment along high-speed railway lines, achieving enhanced accuracy and reliability. On the one hand, based on the special structure in railway assembly, the physical constraint model of the railway electrical catenary supports and anemometers were experimentally established. The performance of the physical model in the wind field was simulated based on FLUENT software and the environmental change characteristics of the anemometer in the railway area were analyzed. On the other hand, to solve the constrained error mapping expression under different wind conditions, a data-driven model of hyperparameter optimization (BO-XGBoost) is introduced to perform error compensation on physical relationships. Through the PD-BX method, the RMSE of the railway anemometer was reduced by 2.497 from 2.790 to 0.293, achieving quality control of wind observations along the high-speed railway lines and providing reliable results for improving the accuracy of the high-speed railway early warning system.

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