{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T02:15:19Z","timestamp":1768011319511,"version":"3.49.0"},"reference-count":32,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Project for Guangdong Administration for Market Regulation (Guangdong Intellectual Property Administration)","award":["2021ZZ02"],"award-info":[{"award-number":["2021ZZ02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Solar power generation has great development potential as an abundant and clean energy source. However, many factors affect the efficiency of the photovoltaic (PV) module; among these factors, outdoor PV modules are inevitably affected by stains, thus reducing the power generation efficiency of the PV panel. This paper proposes a framework for PV module stain detection based on UAV hyperspectral images (HSIs). The framework consists of two stain detection methods: constrained energy minimization (CEM)-based and orthogonal subspace projection (OSP)-based stain detection methods. Firstly, the contaminated PV modules are analyzed and processed to enhance the data\u2019s analytical capability. Secondly, based on the known spectral signature of the PV module, stain detection methods are proposed, including CEM-based stain detection and OSP-based stain detection for PV modules. The experimental results on real data illustrate that, in comparison with contrasting methods, the proposed method achieves stain detection results that closely align with known stain percentages. Additionally, it exhibits a fitting curve similar to the more maturely developed electroluminescence-based methods currently in use.<\/jats:p>","DOI":"10.3390\/rs16010153","type":"journal-article","created":{"date-parts":[[2023,12,31]],"date-time":"2023-12-31T04:51:51Z","timestamp":1703998311000},"page":"153","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Stain Detection Based on Unmanned Aerial Vehicle Hyperspectral Photovoltaic Module"],"prefix":"10.3390","volume":"16","author":[{"given":"Da","family":"Li","sequence":"first","affiliation":[{"name":"China Southern Power Grid Energy Efficiency and Clean Energy Co., Ltd., Guangzhou 510663, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3175-4169","authenticated-orcid":false,"given":"Lan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}]},{"given":"Mingyang","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}]},{"given":"Pengliang","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}]},{"given":"Yintong","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}]},{"given":"Jian","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}]},{"given":"Sui","family":"Dai","sequence":"additional","affiliation":[{"name":"Guangdong Testing Institute of Product Quality Supervision, Guangzhou 510670, China"}]},{"given":"Meiping","family":"Song","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1109\/JPHOTOV.2019.2958149","article-title":"Research on image registration algorithm and its application in photovoltaic images","volume":"10","author":"Zhao","year":"2020","journal-title":"IEEE J. Photovolt."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ravishankar, R., AlMahmoud, E., Habib, A., and de Weck, O.L. (2023). Capacity estimation of solar farms using deep learning on high-resolution satellite imagery. Remote Sens., 15.","DOI":"10.3390\/rs15010210"},{"key":"ref_3","unstructured":"SolarBe, News (2023, August 23). Overview of the Photovoltaic Industry\u2019s Development in the Past Three Years and Future Trends. Available online: https:\/\/news.solarbe.com\/202308\/23\/371119.html."},{"key":"ref_4","first-page":"82","article-title":"High-precision segmentation method for distributed photovoltaic buildings based on improved unet","volume":"44","author":"Xu","year":"2023","journal-title":"J. Sol. Energy"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Qin, W., Wang, L., Yang, C., Su, X., and Wu, J. (2022). Enhancement of photovoltaic power potential in China from 2010 to 2020: The contribution of air pollution control policies. Remote Sens., 15.","DOI":"10.3390\/rs15010228"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Jumaboev, S., Jurakuziev, D., and Lee, M. (2022). Photovoltaics plant fault detection using deep learning techniques. Remote Sens., 14.","DOI":"10.3390\/rs14153728"},{"key":"ref_7","first-page":"5","article-title":"Effect of airborne dust deposition on PV module surface on its power generation performance","volume":"28","author":"Zhang","year":"2012","journal-title":"Power Grid Clean Energy"},{"key":"ref_8","first-page":"7","article-title":"Pollution impact on the leakage current and power degradation of photovoltaic modules","volume":"40","author":"Wang","year":"2019","journal-title":"Acta Energiae Solaris Sin."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4299","DOI":"10.1016\/j.atmosenv.2011.04.084","article-title":"Experimental investigation of the impact of airborne dust deposition on the performance of solar photovoltaic (PV) modules","volume":"45","author":"Jiang","year":"2011","journal-title":"Atmos. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1267","DOI":"10.1016\/j.rser.2016.06.068","article-title":"Dust as an unalterable deteriorative factor affecting PV panel\u2019s efficiency: Why and how","volume":"65","author":"Zaihidee","year":"2016","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2920","DOI":"10.1016\/j.rser.2012.02.012","article-title":"Effect of dust, humidity and air velocity on efficiency of photovoltaic cells","volume":"16","author":"Mekhilef","year":"2012","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5154","DOI":"10.1016\/j.energy.2011.06.018","article-title":"Simulating the dust effect on the energy performance of photovoltaic generators based on experimental measurements","volume":"36","author":"Kaldellis","year":"2011","journal-title":"Energy"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1908","DOI":"10.4028\/www.scientific.net\/AMR.875-877.1908","article-title":"Effect of dust on photovoltaic performance","volume":"875\u2013877","author":"Kazem","year":"2014","journal-title":"Adv. Mater. Res."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Wen, W., Li, S., Zhou, F., Li, M., Xie, Q., and Chen, S. (2021, January 26\u201328). Stain detection method of solar panel based on spot elimination. Proceedings of the Big Data, Artificial Intelligence and Internet of Things Engineering, Nanchang, China.","DOI":"10.1109\/ICBAIE52039.2021.9390021"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Li, T., Yang, D., Chen, C., Zeng, Z., Huang, G., Tao, B., and Li, J. (2022, January 5\u20139). A mobile robot design for efficient and large-scale solar panel cleaning. Proceedings of the IEEE International Conference on Robotics and Biomimetics, Xishuangbanna, China.","DOI":"10.1109\/ROBIO55434.2022.10011850"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/S0960-1481(00)00093-8","article-title":"Effect of dust accumulation on solar transmittance through glass covers of plate-type collectors","volume":"22","author":"Hegazy","year":"2001","journal-title":"Renew. Energy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4862","DOI":"10.1016\/j.energy.2010.09.002","article-title":"Quantifying the decrease of the photovoltaic panels\u2019 energy yield due to phenomena of natural air pollution disposal","volume":"35","author":"Kaldellis","year":"2010","journal-title":"Energy"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3124","DOI":"10.1016\/j.rser.2010.07.065","article-title":"Impact of dust on solar photovoltaic (PV) performance: Research status, challenges and recommendations","volume":"14","author":"Mani","year":"2010","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Nurjanah, S., and Dewi, T. (2021, January 14\u201315). Dusting and Soiling Effect on PV Panel Performance: Case Study Open-pit Mining in South Sumatra. Indonesia. Proceedings of the International Conference on Electrical and Information Technology, Malang, Indonesia.","DOI":"10.1109\/IEIT53149.2021.9587351"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Amr, L., Abdellatif, S.O., Kirah, K., and Ghali, H.A. (2021, January 7\u20139). Investigating the optical impact of an effective time-dependent dust accumulation layer on the optoelectronic performance of monocrystalline solar cell. Proceedings of the International Conference on Green Energy, Computing and Sustainable Technology, Miri, Sarawak, Malaysia.","DOI":"10.1109\/GECOST52368.2021.9538685"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"123927","DOI":"10.1016\/j.energy.2022.123927","article-title":"A novel model to determine the relationship between dust concentration and energy conversion efficiency of photovoltaic (PV) panels","volume":"252","author":"Fan","year":"2022","journal-title":"Energy"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Rekioua, D., and Matagne, E. (2012). Optimization of Photovoltaic Power Systems: Modelization, Simulation and Control, Springer Science & Business Media.","DOI":"10.1007\/978-1-4471-2403-0"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1016\/j.renene.2018.02.046","article-title":"Effectively predict the solar radiation transmittance of dusty photovoltaic panels through Lambert-Beer law","volume":"123","author":"Xingcai","year":"2018","journal-title":"Renew. Energy"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2022.3215576","article-title":"Target Detection in Hyperspectral Imagery Using Atmospheric-Spectral Modeling and Deep Learning","volume":"19","author":"Jha","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1626","DOI":"10.1109\/TGRS.2014.2346479","article-title":"Progressive band processing of constrained energy minimization for subpixel detection","volume":"53","author":"Chang","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1109\/36.298007","article-title":"Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach","volume":"32","author":"Harsanyi","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2403","DOI":"10.1109\/TGRS.2020.3002724","article-title":"Orthogonal subspace projection-based go-decomposition approach to finding low-rank and sparsity matrices for hyperspectral anomaly detection","volume":"59","author":"Chang","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1118","DOI":"10.1109\/JPHOTOV.2021.3084818","article-title":"Photovoltaic image registration based on feature matching via guided spatial consensus","volume":"5","author":"Song","year":"2021","journal-title":"IEEE J. Photovolt."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1109\/36.911111","article-title":"Fully constrained least squares linear mixture analysis for material quantification in hyperspectral imagery","volume":"39","author":"Heinz","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5887","DOI":"10.1109\/JSTARS.2020.3024903","article-title":"Background learning based on target suppression constraint for hyperspectral target detection","volume":"13","author":"Xie","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"112305","DOI":"10.1007\/s11432-020-2915-2","article-title":"Collaborative representation with background purification and saliency weight for hyperspectral anomaly detection","volume":"65","author":"Hou","year":"2022","journal-title":"Sci. China Inf. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1436","DOI":"10.1109\/LGRS.2020.2998809","article-title":"Hyperspectral anomaly detection via integration of feature extraction and background purification","volume":"18","author":"Ma","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/1\/153\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:44:34Z","timestamp":1760132674000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/1\/153"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,29]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["rs16010153"],"URL":"https:\/\/doi.org\/10.3390\/rs16010153","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,29]]}}}