The research study objective seeks to improve the efficiency of wind turbines using state-of-the-art techniques in the domain of ML, making wind energy the key player in fashioning a favorable future. Wind Turbine Health Monitoring (WTHM) is typically achieved through either vibration analysis or by using Supervisory Control and Data Acquisition (SCADA) data of wind turbines, wherein conventional fault pattern identification is a time-consuming, guesswork process. This work proposed an intelligent automated approach to early fault detection through the implementation of the HARO (Huber Adam Regression Optimizer) model, which combines Transformer networks with Lasso Regression and the Adam optimizer.
View Article and Find Full Text PDFThe research objective in the context of the study relates to the major concern of corrosion affecting the wind turbines in operation to find materials with high durability in relation to environmental conditions of operation, strength, and cost. A method is an integration of the Analytical Hierarchy Process (AHP) and VIKOR Multi-Criteria Decision Making (MCDM) techniques that will assess seven different material options on sixteen criteria that comprise corrosion resistance, mechanical properties, cost, and a negative environmental impact. From this result, the AHP method calculated the weights for the indicators and chose potential materials, and finally, the VIKOR method used these materials and compared and ranked them to obtain a compromise solution.
View Article and Find Full Text PDFBackground: Trichosanthes lobata (family cucurbitaceae) is used to treat malarial fever and liver disorders. This study aims to investigate possible hepatoprotective activities of ethanolic extract of Trichosanthes lobata against paracetamol-induced hepatotoxicity.
Methods: Hepatotoxicity was induced in Wistar male rats by oral administration, 2 g/kg body weight on 7th day after the administration of ethanolic extract of Trichosanthes lobata and silymarin (100 mg/kg).