Detecting Failures at an Earlier Stage

Replacing components in a wind turbine is a costly procedure, especially if required urgently; however, it can be avoided or planned for by on-going monitoring of temperatures

Canadian optimization software company, Clir Renewables, has released its latest AI feature. The Clir AI platform has evolved to learn how to identify anomalies in component temperatures to detect failure at an earlier stage. Maintenance budgets for wind farms account for the majority of associated OPEX. These planned budgets can be shattered if unexpected repair is required due to a component failure. Increased expenditure is not the only cost involved with unexpected failures. When a failure occurs, the turbine can be out of operation anywhere from a few days to a few weeks, dependent on... ... More: Official Press Release Clir Renewables

Keywords:

Clir Renewables, turbine, wind turbine, AI, platform, anomaly, component, temperature, failure, detection, replacing