Dataset on Guided Waves from Long-Term Structural Health Monitoring under Uncontrolled and Dynamic Conditions 机器收录·待核验

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Few studies address guided wave structural health monitoring under controlled and dynamic environments, largely due to the lack of a public benchmark dataset. To address this gap, this paper presents a public dataset from a long-term outdoor structural monitoring experiment conducted at the University of Utah, Salt Lake City. The monitoring, spanning over 4.5 years, collected approximately 6.4 million guided waves under both regular environmental variations (e.g., daily temperature changes ranging from −12.2◦C to 52.5◦C) and irregular variations (e.g., rain and snow). The measured guided waves in the public dataset are also affected by sensor drift and installation shifts consistently over time. Additionally, thirteen types of damage were introduced to the monitored structure to support damage detection and severity evaluation under these conditions. The dataset includes measurement times, temperature, humidity, air pressure, brightness, and weather information to aid in damage detection. The provided public dataset aims to assist researchers in developing more practical methods for structural health monitoring in uncontrolled and dynamic environments.

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落地页

https://springernature.figshare.com/articles/dataset/Dataset_on_Guided_Waves_from_Long-Term_Structural_Health_Monitoring_under_Uncontrolled_and_Dynamic_Conditions/28112504

许可证

CC-BY-4.0 (置信:verified_official)

发布年份

2025

发布方

figshare

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