VISION INSPECTION AND MONITORING OF WIND TURBINE FARMS IN EMERGING SMART GRIDS
Abstract
Todays, Smart Grids as the goal of next generation power grid system span wide and new aspects of power generation from distributed and bulk power generators to the end-user utilities. There are many advantages to develop these complex and multilayer system of systems such as increasing agility, reliability, efficiency, privacy, security for both Energy and ICT sections in smart grid architecture. In emerging smart grids, the communication infrastructures play main role in grid development and as a result multimedia applications are more practical for the future power systems. In this work, we introduce our method for monitoring and inspection of Wind Turbine (WT) farms in smart grids. In our proposed system, a thermal vision camera is embedded on a wireless sensor node for each WT to capture appropriate images and send video streams to the coordinator. It gets video frames to perform machine Vision Inspection (VI) and monitoring purposes. In our constructed model, turbine blade velocity estimation is targeted by detecting two important landmarks in the image that are named hub and blade. By tracking the blade in the consecutive frames and based on proposed scoring function, we can estimate the velocity of the turbine blade. Obtained results clearly indicate that accurate hub and blade positions extraction lead to error free estimation of turbine blade velocity.
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M. E. El-Hawary, "The smart grid—state-of-the-art and future trends," Electric Power Components and Systems, vol. 42, pp. 239-250, 2014.
V. C. Gungor, D. Sahin, T. Kocak, S. Ergut, C. Buccella, C. Cecati, et al., "A survey on smart grid potential applications and communication requirements," IEEE Transactions on Industrial Informatics, vol. 9, pp. 28-42, 2013.
N. IqtiyaniIlham, M. Hasanuzzaman, and M. Hosenuzzaman, "European smart grid prospects, policies, and challenges," Renewable and Sustainable Energy Reviews, vol. 67, pp. 776-790, 2017.
S. G. C. CEN-CENELEC-ETSI, "Group," in Smart grid reference architecture, ed, 2012.
N. Framework, "Roadmap for smart grid interoperability standards," National Institute of Standards and Technology, 2010.
M. Kuzlu, M. Pipattanasomporn, and S. Rahman, "Communication network requirements for major smart grid applications in HAN, NAN and WAN," Computer Networks, vol. 67, pp. 74-88, 2014.
A. Usman and S. H. Shami, "Evolution of communication technologies for smart grid applications," Renewable and Sustainable Energy Reviews, vol. 19, pp. 191-199, 2013.
H. Li, L. Lai, and W. Zhang, "Communication requirement for reliable and secure state estimation and control in smart grid," IEEE Transactions on Smart Grid, vol. 2, pp. 476-486, 2011.
P. Tchakoua, R. Wamkeue, M. Ouhrouche, F. Slaoui-Hasnaoui, T. A. Tameghe, and G. Ekemb, "Wind turbine condition monitoring: State-of-the-art review, new trends, and future challenges," Energies, vol. 7, pp. 2595-2630, 2014.
C.-S. Tsai, C.-T. Hsieh, and S.-J. Huang, "Enhancement of damage-detection of wind turbine blades via CWT-based approaches," IEEE Transactions on energy conversion, vol. 21, pp. 776-781, 2006.
R. Gade and T. B. Moeslund, "Thermal cameras and applications: a survey," Machine vision and applications, vol. 25, pp. 245-262, 2014.
A. B. Nikolic, N. Neskovic, R. Antic, and A. Anastasijevic, "Industrial wireless sensor networks as a tool for remote on-line management of power transformers'heating and cooling process," Facta Universitatis, Series: Electronics and Energetics, vol. 30, pp. 107-119, 2016.
M. Milutinov, N. Đurić, N. Pekarić-Nađ, D. Mišković, and D. Knežević, "Multiband sensors for wireless electromagnetic field monitoring system-SEMONT," Facta Universitatis, Series: Electronics and Energetics, vol. 25, pp. 137-150, 2012.
M. R. Kosanović and M. K. Stojčev, "RPLL-Rendezvous protocol for long-living sensor node," Facta Universitatis, Series: Electronics and Energetics, vol. 28, pp. 85-102, 2015.
E. Cuevas, V. Osuna, and D. Oliva, "Template Matching," presented at the Evolutionary Computation Techniques: A Comparative Perspective, 2017.
G. Jasvilis, C. Weise, and B. Zenger-Landolt, "Finding complex patterns using template matching," 2016.
A. Mahmood, A. Mian, and R. Owens, "On Optimizing Auto-correlation for Fast Template Matching Through Transitive Elimination," arXiv preprint arXiv:1407.3535, 2014.
F. Zhong, S. He, and B. Li, "Blob analyzation-based template matching algorithm for LED chip localization," The International Journal of Advanced Manufacturing Technology, pp. 1-9, 2015.
Y. Zhang, S. Wang, P. Sun, and P. Phillips, "Pathological brain detection based on wavelet entropy and Hu moment invariants," Bio-medical materials and engineering, vol. 26, pp. S1283-S1290, 2015.
J. Flusser and T. Suk, "Rotation moment invariants for recognition of symmetric objects," IEEE Transactions on Image Processing, vol. 15, pp. 3784-3790, 2006.
M. K. Bahaghighat and J. Mohammadi, "Novel approach for baseline detection and Text line segmentation," International Journal of Computer Applications, vol. 51, 2012.
M. K. Bahaghighat and R. Akbari, "Fingerprint image enhancement using GWT and DMF," in Proce. of the 2nd International Conference on Signal Processing Systems (ICSPS), 2010, pp. V1-253-V1-257.
S. Tang, "Face recognition method based on gabor wavelet and memetic ecological algorithm," Biomedical Research, pp. 1-1, 2017.
T. S. Lee, "Image representation using 2D Gabor wavelets," IEEE Transactions on pattern analysis and machine intelligence, vol. 18, pp. 959-971, 1996.
N. Karimimehr and A. A. B. Shirazi, "Fingerprint image enhancement using gabor wavelet transform," in Proceedings of the 18th Iranian Conference on Electrical Engineering (ICEE), 2010, pp. 316-320.
S. Li, D. C. Wunsch, E. A. O'Hair, and M. G. Giesselmann, "Using neural networks to estimate wind turbine power generation," IEEE Transactions on energy conversion, vol. 16, pp. 276-282, 2001.
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ISSN: 0353-3670 (Print)
ISSN: 2217-5997 (Online)
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