{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T20:10:09Z","timestamp":1778530209783,"version":"3.51.4"},"reference-count":60,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T00:00:00Z","timestamp":1778198400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"State Grid Corporation of China Science and Technology Project","award":["J2025059"],"award-info":[{"award-number":["J2025059"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Foreign object detection during unmanned aerial vehicle (UAV) grid inspection suffers from severe visual degradation under adverse weather conditions, such as haze and heavy rain. Existing approaches often struggle to distinguish target textures from weather-induced noise, leading to critical performance drops. We propose the Physics-Prior Complex Wavelet Unrolling Decoupling Module (PCW-UDM) to enable highly robust detection in complex environments. By leveraging the 2D dual-tree complex wavelet transform (2D-DTCWT), our method decouples degraded features into low-frequency and multi-directional high-frequency sub-bands. To tackle haze, we design a Physics-Guided Low-Frequency Dehazing (PGLD) branch that physically inverses the atmospheric scattering process. To combat rain, we introduce the LISTA-Unrolled High-Frequency Deraining (LUHD) branch, which innovatively applies deep unrolled sparse optimisation to remove directional rain streaks without distorting the structural phase. A novel spatio-temporal cross-domain consistency loss further guarantees weather-invariant feature alignment. Extensive evaluations on synthesised adverse datasets and the real-world RTTS dataset prove that our PCW-UDM-equipped network fundamentally overcomes the semantic conflicts of traditional cascaded restoration\u2013detection paradigms, achieving state-of-the-art detection precision and robustness against extreme weather conditions.<\/jats:p>","DOI":"10.3390\/s26102942","type":"journal-article","created":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T19:35:43Z","timestamp":1778528143000},"page":"2942","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Weather-Robust Foreign Object Detection on Transmission Lines via Physics-Driven Complex Wavelet Unrolling"],"prefix":"10.3390","volume":"26","author":[{"given":"Xiaoxiong","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junchi","family":"He","sequence":"additional","affiliation":[{"name":"Distribution Network Operation and Maintenance Center, Guanyun County Electric Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Lianyungang 222207, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Cheng","sequence":"additional","affiliation":[{"name":"Distribution Network Operation and Maintenance Center, Guanyun County Electric Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Lianyungang 222207, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9566-7865","authenticated-orcid":false,"given":"Guangming","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1007\/s10462-022-10189-2","article-title":"A survey of intelligent transmission line inspection based on unmanned aerial vehicle","volume":"56","author":"Luo","year":"2023","journal-title":"Artif. 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