Evaluation of texture feature based on basic local binary pattern for wood defect classification

Wood defects detection has been studied a lot recently to detect the defects on the wood surface and assist the manufacturers in having a clear wood to be used to produce a high-quality product. Therefore, the defects on the wood affect and reduce the quality of wood. This research proposes an effective feature extraction technique called the local binary pattern (LBP) with a common classifier called Support Vector Machine (SVM). Our goal is to classify the natural defects on the wood surface. First, preprocessing was applied to convert the RGB images into grayscale images. Then, the research applied the LBP feature extraction technique with eight neighbors (P=8) and several radius (R) values. After that, we apply the SVM classifier for the classification and measure the proposed technique's performance. The experimental result shows that the average accuracy achieved is 65% on the balanced dataset with P=8 and R=1. It indicates that the proposed technique works moderately well to classify wood defects. This study will consequently contribute to the overall wood defect detection framework, which generally benefits the automated inspection of the wood defects

Power management and control strategies for off-grid hybrid power systems with renewable energies and storage

This document is the Accepted Manuscript of the following article: Belkacem Belabbas, Tayeb Allaoui, Mohamed Tadjine, and Mouloud Denai, 'Power management and control strategies for off-grid hybrid power systems with renewable energies and storage', Energy Systems, September 2017. Under embargo. Embargo end date: 19 September 2018. The final publication is available at Springer via https://doi.org/10.1007/s12667-017-0251-y.This paper presents a simulation study of standalone hybrid Distributed Generation Systems (DGS) with Battery Energy Storage System (BESS). The DGS consists of Photovoltaic (PV) panels as Renewable Power Source (RPS), a Diesel Generator (DG) for power buck-up and a BESS to accommodate the surplus of energy, which may be employed in times of poor PV generation. While off-grid DGS represent an efficient and cost-effective energy supply solution particularly to rural and remote areas, fluctuations in voltage and frequency due to load variations, weather conditions (temperature, irradiation) and transmission line short-circuits are major challenges. The paper suggests a hierarchical Power Management (PM) and controller structure to improve the reliability and efficiency of the hybrid DGS. The first layer of the overall control scheme includes a Fuzzy Logic Controller (FLC) to adjust the voltage and frequency at the Point of Common Coupling (PCC) and a Clamping Bridge Circuit (CBC) which regulates the DC bus voltage. A maximum power point tracking (MPPT) controller based on FLC is designed to extract the optimum power from the PV. The second control layer coordinates among PV, DG and BESS to ensure reliable and efficient power supply to the load. MATLAB Simulink is used to implement the overall model of the off-grid DGS and to test the performance of the proposed control scheme which is evaluated in a series of simulations scenarios. The results demonstrated the good performance of the proposed control scheme and effective coordination between the DGS for all the simulation scenarios considered.Peer reviewedFinal Accepted Versio

Experimental Performance Investigation of Photovoltaic/Thermal (PV–T) System

Photovoltaic solar cells convert light energy from the sun into electricity. Photovoltaic cells are produced by semi-conducting materials to convert the energy into electricity and during this process heat is absorbed by the solar radiation. This heat causes a loss of electricity generation efficiencies.In this study, an experimental setup was designed and established to test two separate photovoltaic panel systems with alone PV and with water cooling system PV/T to examine the heat effect on PV systems. The absorbed heat energy behind the photovoltaic cell's surface in insulated ambient was removed by means of a water cooling system and the tests for both systems were simultaneously performed along the July 2011. It is found that without active water cooling, the temperature of the PV module was higher during day time and solar cells could only achieve around 8% conversion efficiency. On the other hand, when the PV module was operated with active water cooling condition, the temperature dropped significantly, leading to an increase in the efficiency of solarcells as much as 13.6%. Gained from absorbed solar heat and maximum thermal conversion efficiencies of the system are determined as 49% and 51% for two different mass flow rates. It is observed that water flow rate is effective on the increasing the conversion efficiency as well as absorption and transitionrates of cover glass in PV/T (PV–Thermal) collector, the insulation material and cell efficiency. As a conclusion, the conversion efficiency of the PV system with water cooling might be improved on average about 10%. Therefore, it is recommended that PV system should be designed with most efficient type cooling system to enhance the efficiency and to decrease the payback period