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Sensors for Structural Health Monitoring of Agricultural Structures

机译:农业结构结构健康监测传感器

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摘要

The health diagnosis of agricultural structures is critical to detecting damages such as cracks in concrete, corrosion, spalling, and delamination. Agricultural structures are susceptible to environmental degradation due to frequent exposure to water, organic effluent, farm chemicals, structural loading, and unloading. Various sensors have been employed for accurate and real-time monitoring of agricultural building structures, including electrochemical, ultrasonic, fiber-optic, piezoelectric, wireless, fiber Bragg grating sensors, and self-sensing concrete. The cost–benefits of each type of sensor and utility in a farm environment are explored in the review. Current literature suggests that the functionality of sensors has improved with progress in technology. Notable improvements made with the progress in technology include better accuracy of the measurements, reduction of signal-to-noise ratio, and transmission speed, and the deployment of machine learning, deep learning, and artificial intelligence in smart IoT-based agriculture. Key challenges include inconsistent installation of sensors in farm structures, technical constraints, and lack of support infrastructure, awareness, and preference for traditional inspection methods.
机译:农业结构的健康诊断对于检测混凝土,腐蚀,剥落和分层等裂缝等损坏至关重要。由于频繁暴露于水,有机污水,农场化学品,结构载荷和卸载,农业结构易受环境降解的影响。各种传感器已经采用了用于农业建筑结构的准确和实时监测,包括电化学,超声波,光纤,压电,无线,光纤布拉格光栅传感器和自感应混凝土。在审查中探讨了各种类型的传感器和公用事业的成本优势。目前的文献表明传感器的功能在技术进展方面得到了改进。技术进步的显着改进包括测量的更好准确性,降低信噪比和传输速度,以及机器学习,深度学习和基于智能物联网农业的人工智能的部署。关键挑战包括农场结构,技术限制以及缺乏支持基础设施,意识和传统检验方法的缺乏的传感器的不一致。

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