Aerial image analysis based on improved adaptive clustering for photovoltaic module inspection

Exploitation and using of clean and renewable energy to improve the domestic energy structure is important for building smart city. Photovoltaic (PV) power generation is a good choose, and modules inspection is an important direction of PV power generation. The manual inspection is a common way but is not feasible for large-scale PV systems in practice due to low efficiency, high error rate and long assessment time. Currently inspection system based on Unmanned Aerial Vehicles (UAVs) has been proved to be a better solution in PV inspection. How to locate PV arrays in aerial image captured by UAV is one of the technical changes exist in UAV-based PV inspection. This paper proposed an improved adaptive clustering method based on k- means algorithm to orientate and acquire single PV array's edge, lots of monitoring data indicate this algorithm has a high accuracy and make the loss rate lower than 5%.

[1]  Claudia Buerhop,et al.  Faults and infrared thermographic diagnosis in operating c-Si photovoltaic modules: A review of research and future challenges , 2016 .

[2]  Pascual Campoy Cervera,et al.  COLIBRI: A vision-Guided UAV for Surveillance and Visual Inspection , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[3]  Jonathan Leloux,et al.  Advanced PV modules inspection using multirotor UAV , 2015 .

[4]  Markus Metz,et al.  GRASS GIS: A multi-purpose open source GIS , 2012, Environ. Model. Softw..

[5]  Xiaoou Tang,et al.  Single Image Haze Removal Using Dark Channel Prior , 2011 .

[6]  Alison S. Tomlin,et al.  Modelling of roof geometries from low-resolution LiDAR data for city-scale solar energy applications using a neighbouring buildings method , 2015 .

[7]  Fu Feng,et al.  A survey on threshold methods of image segmentation. , 2003 .

[8]  Hong Peng,et al.  A novel image thresholding method based on membrane computing and fuzzy entropy , 2013, J. Intell. Fuzzy Syst..

[9]  Mohammadreza Aghaei,et al.  Planning for PV plant performance monitoring by means of unmanned aerial systems (UAS) , 2015 .

[10]  H. Beyer,et al.  Solar energy assessment using remote sensing technologies , 2003 .

[11]  Naser El-Sheimy,et al.  Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition , 2016, Remote. Sens..

[12]  J. Hofierka,et al.  The solar radiation model for Open source GIS: implementation and applications , 2002 .

[13]  Dan Keun Sung,et al.  Solar Power Prediction Based on Satellite Images and Support Vector Machine , 2016, IEEE Transactions on Sustainable Energy.

[14]  Xiao Hua.  A Survey on Threshold Methods of Image Segmentation , 2006 .

[15]  Karl Pearson,et al.  II. Mathematical contributions to the theory of evolution. II. Skew variation in homogeneous material , 1985, Proceedings of the Royal Society of London.

[16]  Geoffrey E. Hinton,et al.  Learning to Detect Roads in High-Resolution Aerial Images , 2010, ECCV.

[17]  G. Štumberger,et al.  Rating of roofs’ surfaces regarding their solar potential and suitability for PV systems, based on LiDAR data , 2013 .

[18]  Mehdi Mokhtarzade,et al.  Road detection from high-resolution satellite images using artificial neural networks , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[19]  Nor Ashidi Mat Isa,et al.  Color image segmentation using histogram thresholding - Fuzzy C-means hybrid approach , 2011, Pattern Recognit..

[20]  Du-Ming Tsai,et al.  An improved anisotropic diffusion model for detail- and edge-preserving smoothing , 2010, Pattern Recognit. Lett..

[21]  J. Daugman.  Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[22]  Xuelong Li,et al.  General Tensor Discriminant Analysis and Gabor Features for Gait Recognition , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Jordan M. Malof,et al.  Automatic Detection of Solar Photovoltaic Arrays in High Resolution Aerial Imagery , 2016, ArXiv.

[24]  Shiming Xiang,et al.  Vehicle Detection in Satellite Images by Parallel Deep Convolutional Neural Networks , 2013, 2013 2nd IAPR Asian Conference on Pattern Recognition.

[25]  FUZZY C-MEANS ALGORITHM FOR SEGMENTATION OF AERIAL PHOTOGRAPHY DATA OBTAINED USING UNMANNED AERIAL VEHICLE , 2015 .

[26]  Jian Sun,et al.  Single image haze removal using dark channel prior , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[27]  Nicolai Petkov,et al.  Nonlinear operator for oriented texture , 1999, IEEE Trans. Image Process..

[28]  Daniel Cremers,et al.  Car detection by fusion of HOG and causal MRF , 2015, IEEE Transactions on Aerospace and Electronic Systems.

[29]  Abdul Nishar,et al.  Thermal infrared imaging of geothermal environments and by an unmanned aerial vehicle (UAV): A case study of the Wairakei – Tauhara geothermal field, Taupo, New Zealand , 2016 .

[30]  M. Pal,et al.  Random forests for land cover classification , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[31]  Shiming Xiang,et al.  Vehicle Detection in Satellite Images by Hybrid Deep Convolutional Neural Networks , 2014, IEEE Geoscience and Remote Sensing Letters.

[32]  Jaroslav Hofierka,et al.  A New GIS‐based Solar Radiation Model and Its Application to Photovoltaic Assessments , 2004, Trans. GIS.

[33]  Mohammadreza Aghaei,et al.  Innovative Automated Control System for PV Fields Inspection and Remote Control , 2015, IEEE Transactions on Industrial Electronics.