Advanced wireless system for predictive monitoring of structural wind turbine co...
Advanced wireless system for predictive monitoring of structural wind turbine components
Wind energy plants are increasingly becoming critical parts of electrical infrastructure around the world. Despite major technological advancements over the past decade, an estimated 5.500 wind turbine blades fail each year, resul...
ver más
¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
Wind energy plants are increasingly becoming critical parts of electrical infrastructure around the world. Despite major technological advancements over the past decade, an estimated 5.500 wind turbine blades fail each year, resulting in long periods of unexpected downtime and repair costs.
At eologix sensor technologies gmbh, we are developing an advanced system called eolACC that uses wireless accelerometers to detect damage to blades before they fail. The patented sensor technology is thin and flexible, allowing it to be easily applied to virtually any location, even on aerodynamic surfaces of blades. Together with a base station and our software, diagnostics will alert operators of poor blade conditions and thus enhance their ability to plan critical maintenance activities. Additionally, the insight from blade sensors will help operators manage assets more effectively, and make objective decisions about useful lifetimes and operating ranges.
eolACC builds off of an ice detection system previously made by eologix by utilizing the same sensor profile, wireless data transmission, and ambient light power system. Initially eolACC will be sold to owners and operators of wind plants, and in the future we will pursue collaboration with large wind turbine manufacturers.
The eolACC system will ultimately help wind power plants to operate more efficiently by reducing unexpected downtime. Owners and operators will be able to more effectively plan budgets and maximize the lifetime of their assets.