G. Sudharsan, J. Vishnupriyan, K. Anand, K. Chidambarathanu
{"title":"Smart Monitoring System for Small-scale Wind Turbine Model","authors":"G. Sudharsan, J. Vishnupriyan, K. Anand, K. Chidambarathanu","doi":"10.1109/icdcece53908.2022.9793080","DOIUrl":null,"url":null,"abstract":"The most pressing challenges in the development of fossil fuel energy resources are their high value and scarcity. Therefore, renewable energy achieved through the mismanagement of natural resources is one of the most important aspects defining the energy crisis. Solar, wind, geothermal and recurring event energy are examples of assets. The cost of wind turbines is much higher compared to diesel generators. Moreover, regular maintenance costs often account for up to one-twentieth of the total cost of a rotary engine. However, accidental failure of certain elements such as blades, gearboxes, supports, brake systems can lead to high costs. Identifying parts of a system with human resources or intelligent systems helps to stop and reduce serious failures. Therefore, a completely different condition monitoring system has been applied to wind turbines, providing a great opportunity to develop a large space for analysis in the fields of structural turbine condition monitoring and field condition monitoring systems. Assessing the health of critical system components can help you become more aware of failed components and reduce maintenance time and costs. By using a completely different kind of sensor for the rotary engine components and using the right control and data acquisition systems, a complex condition monitoring system is provided.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icdcece53908.2022.9793080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The most pressing challenges in the development of fossil fuel energy resources are their high value and scarcity. Therefore, renewable energy achieved through the mismanagement of natural resources is one of the most important aspects defining the energy crisis. Solar, wind, geothermal and recurring event energy are examples of assets. The cost of wind turbines is much higher compared to diesel generators. Moreover, regular maintenance costs often account for up to one-twentieth of the total cost of a rotary engine. However, accidental failure of certain elements such as blades, gearboxes, supports, brake systems can lead to high costs. Identifying parts of a system with human resources or intelligent systems helps to stop and reduce serious failures. Therefore, a completely different condition monitoring system has been applied to wind turbines, providing a great opportunity to develop a large space for analysis in the fields of structural turbine condition monitoring and field condition monitoring systems. Assessing the health of critical system components can help you become more aware of failed components and reduce maintenance time and costs. By using a completely different kind of sensor for the rotary engine components and using the right control and data acquisition systems, a complex condition monitoring system is provided.