Fiber Bragg grating sensor-based temperature monitoring of solar photovoltaic panels using machine learning algorithms

Arora, 2018, High-resolution slow-light fiber Bragg grating temperature sensor with phase-sensitive detection, Opt. Lett., 43, 3337, 10.1364/OL.43.003337 Díaz, 2017, Liquid level measurement based on FBG-embedded diaphragms with temperature compensation, IEEE Sens. J., 18, 193, 10.1109/JSEN.2017.2768510 You, 2019, A novel fiber Bragg grating (FBG) soil strain sensor, Measurement, 139, 85, 10.1016/j.measurement.2019.03.007 Li, 2018, Sensitivity enhancement of FBG-based strain sensor, Sensors, 18, 1607, 10.3390/s18051607 Samiappan, 2020, Enhancing Sensitivity of Fiber Bragg Grating-Based Temperature Sensors through Teflon Coating, Wirel. Pers. Commun., 110, 593, 10.1007/s11277-019-06744-w Ghosh, 2018, Augmentation of sensitivity of FBG strain sensor for biomedical operation, Appl. Opt., 57, 6906, 10.1364/AO.57.006906 Li, 2017, A hybrid FBG displacement and force sensor with a suspended and bent optical fiber configuration, Sens. Actuators A Phys., 268, 117, 10.1016/j.sna.2017.11.032 Li, 2020, Experimental investigation and error analysis of high precision FBG displacement sensor for structural health monitoring, Int. J. Struct. Stab. Dyn., 20, 2040011, 10.1142/S0219455420400118 Mieloszyk, 2017, An application of Structural Health Monitoring system based on FBG sensors to offshore wind turbine support structure model, Mar. Struct., 51, 65, 10.1016/j.marstruc.2016.10.006 Tseng, 2014, 483 Kaur, 2020, An efficient R-peak detection using Riesz fractional-order digital differentiator, Circuits, Syst. Signal Process., 39, 1965, 10.1007/s00034-019-01238-3 Kaur, 2019, Riesz fractional order derivative in Fractional Fourier Transform domain: An insight, Digit, Signal Process., 93, 58 Hill, 1997, Fiber Bragg grating technology fundamentals and overview, J. Light. Technol., 15, 1263, 10.1109/50.618320 Morey, 1990, Fiber optic Bragg grating sensors, in Fiber Optic and Laser Sensors VII, vol. 1169, 98, 10.1117/12.963022 Chen, 2017, EMD self-adaptive selecting relevant modes algorithm for FBG spectrum signal, Opt. Fiber Technol., 36, 63, 10.1016/j.yofte.2017.02.008 Y. Chen, K. Yang, H.L., Self-adaptive multipeak detection algorithm for FBG sensing signal, IEEE Sens. J. 16(8) (2016) 2658-2665. Zhang, 2019, The analysis of FBG central wavelength variation with crack propagation based on a self-adaptive multipeak detection algorithm, Sensors, 19, 1056, 10.3390/s19051056 Biswal, 2020, n-GaAs based extrinsic Dodecanacci photonic quasicrystal, Phys. B: Condens. Matter, 595, 10.1016/j.physb.2020.412340 Liu, 2018, Multipeak detection algorithm based on the Hilbert transform for optical FBG sensing, Opt. Fiber Technol., 45, 47, 10.1016/j.yofte.2018.06.003 Wilamowski, 2009, Neural network architectures and learning algorithms, IEEE Ind. Electron. Mag., 3, 56, 10.1109/MIE.2009.934790 Lauria, 2014, On Hilbert transform methods for low frequency oscillations detection, IET Gener. Transm. Distrib., 8, 1061, 10.1049/iet-gtd.2013.0545 Kabir, 2018, Solar energy: Potential and future prospects, Renew. Sust. Energ. Rev., 82, 894, 10.1016/j.rser.2017.09.094 Vengadesan, 2020, A Review on Recent Developments in Thermal Performance Enhancement Methods of Flat Plate Solar Air Collector, Renew. Sust. Energ. Rev., 134, 10.1016/j.rser.2020.110315 Yoo, 2021, Efficient perovskite solar cells via improved carrier management, Nature, 590, 587, 10.1038/s41586-021-03285-w Kumari, 2019, Development of a highly accurate and fast responsive salinity sensor based on Nuttall apodized Fiber Bragg Grating coated with hygroscopic polymer for ocean observation, Opt. Fiber Technol., 53 Kaur, 2017, Strategic review of interface carrier recombination in earth abundant Cu–Zn–Sn–S–Se solar cells: current challenges and future prospects, J. Mater. Chem. A, 5, 3069, 10.1039/C6TA10543B Lamberti, 2014, Influence of fiber bragg grating spectrum degradation on the performance of sensor interrogation algorithms, Sensors, 14, 24258, 10.3390/s141224258 Negri, 2011, Benchmark for peak detection algorithms in fiber bragg grating interrogation and a new neural network for its performance improvement, Sensors, 11, 3466, 10.3390/s110403466 Tosi, 2017, Review and analysis of peak tracking techniques for fiber bragg grating sensors, Sensors, 17, 2368, 10.3390/s17102368 Huang, 2007, Demodulation of fiber Bragg grating sensor using cross-correlation algorithm, IEEE Photonics Technol. Lett., 19, 707, 10.1109/LPT.2007.895422 Chen, 2013, Research on fbg sensor signal wavelength demodulation based on improved wavelet transform, Optik, 124, 4802, 10.1016/j.ijleo.2013.01.079 An, 2018, Fiber bragg grating temperature calibration based on bp neural network, Optik, 172, 753, 10.1016/j.ijleo.2018.07.064 Breiman, 2001, Random Forests, Machine Learning, 45, 5, 10.1023/A:1010933404324 Geurts, 2006, Extremely randomized trees, Machine Learning, 63, 3, 10.1007/s10994-006-6226-1 Breiman, 1984 Chen, 2011, Digital fractional order Savitzky-Golay differentiator, IEEE Trans, Circuits Syst. II: Express Br., 58, 758, 10.1109/TCSII.2011.2168022 Lamberti, 2014, A novel fast phase correlation algorithm for peak wavelength detection of fiber Bragg grating sensors, Opt. Express, 22, 7099, 10.1364/OE.22.007099 Liu, 2011, A fiber Bragg grating sensor network using an improved differential evolution algorithm, IEEE Photonics Technol. Lett., 23, 1385, 10.1109/LPT.2011.2160992 Mohan, 2019, Effective Heart Disease Prediction using Hybrid Machine Learning Techniques, IEEE Access, 7, 81542, 10.1109/ACCESS.2019.2923707 Bhargava, 2020, Review of Health Prognostics and Condition Monitoring of Electronic Components, IEEE Access, 8, 75163, 10.1109/ACCESS.2020.2989410 Mohan, 2021, An approach to forecast impact of Covid-19 using supervised machine learning model, Software Pract Exper. Shapiro, 1965, An analysis of variance test for normality (complete samples), Biometrika, 52, 591, 10.1093/biomet/52.3-4.591 I.M. Chakravarti, R.G. Laha, and J. Roy, Handbook of Methods of Applied Statistics. Volume I: Techniques of Computation Descriptive Methods, and Statistical Inference. Volume II: Planning of Surveys and Experiments, New York, John Wiley (1967). Lilliefors, 1967, On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown, J. Am. Stat. Assoc., 62, 399, 10.1080/01621459.1967.10482916 Anderson, 1952, Asymptotic theory of certain “goodness-of-fit” criteria based on stochastic processes, Ann. Math. Stat., 23, 193, 10.1214/aoms/1177729437 Chen, 1995, An alernative test for normality based on normalized spacings, J. Statist. Comput. Simulation, 53, 269, 10.1080/00949659508811711 Gao, 2009, Multilevel thresholding for image segmentation through an improved quantum-behaved particle swarm algorithm, IEEE Trans. Instrum. Meas., 59, 93 Maitra, 2008, A hybrid cooperative–comprehensive learning based PSO algorithm for image segmentation using multilevel thresholding, Expert Syst. Appl., 34, 1341, 10.1016/j.eswa.2007.01.002 Rather, 2020, A Hybrid Constriction Coefficient-Based Particle Swarm Optimization and Gravitational Search Algorithm for Training Multi-Layer Perceptron, Int. J. Intell. Comput. Cybern., 13, 129, 10.1108/IJICC-09-2019-0105 Rather, 2021, Application of Constriction Coefficient-Based Particle Swarm Optimisation and Gravitational Search Algorithm for Solving Practical Engineering Design Problems, Int. J. Bio-Inspir. Com., 17, 246, 10.1504/IJBIC.2021.116617 Rather, 2021, Constriction Coefficient Based Particle Swarm Optimization and Gravitational Search Algorithm for Multilevel Image Thresholding, Expert Systems, 38, 10.1111/exsy.12717 Mirjalili, 2014, Grey Wolf Optimizer, Adv. Eng. Softw., 69, 46, 10.1016/j.advengsoft.2013.12.007 Rather, 2020, Swarm-Based Chaotic Gravitational Search Algorithm for Solving Mechanical Engineering Design Problems, World J. Eng., 19, 97, 10.1108/WJE-09-2019-0254 Sivakumar, 2021, Experimental study on the electrical performance of a solar photovoltaic panel by water immersion, Environ. Sci. Pollut. Res., 28, 42981, 10.1007/s11356-021-15228-z S. Navakrishnan, S., et al., An experimental study on simultaneous electricity and heat production from solar PV with thermal energy storage, Energy Convers. Manag. 245 (2021) 114614. Senthil, 2021, A holistic review on the integration of heat pipes in solar thermal and photovoltaic systems, Sol. Energy, 227, 577, 10.1016/j.solener.2021.09.036 Sreejith, 2016, Security constraint unit commitment on combined solar thermal generating units using ABC algorithm, Int. J. Renew. Energy Res., 6, 1361 Anand, 2021, Thermal regulation of photovoltaic system for enhanced power production: A review, J. Energy Storage, 35, 10.1016/j.est.2021.102236 Al-Amri, 2022, Innovative technique for achieving uniform temperatures across solar panels using heat pipes and liquid immersion cooling in the harsh climate in the kingdom of Saudi Arabia, Alex. Eng. J., 61, 1413, 10.1016/j.aej.2021.06.046