The growing interest around offshore wind power, providing at the same time better wind conditions and fewer visual or environmental impacts, has lead many energy suppliers to consider the installation of offshore wind farms. However, the marine environment makes the installation and maintenance of wind turbines much more complicated, raising the capital and operation costs to an undesirable level and preventing the fast progression of this technology worldwide. Availability of offshore wind turbines varies between 65 and 90% depending on location, whereas onshore turbines range between 95 and 98% in most cases. In 2009, the ETI launched a research project aiming to improve economical efficiency of offshore wind farms by increasing their availability and decreasing their maintenance costs (partly through replacing corrective maintenance by preventive maintenance). This project named “Inflow” involves the development of a condition monitoring system, a system designed to monitor the state of different wind turbine components, and to analyze this data in order to determine the wind turbines overall condition at any given time, as well as its potential system ailments   This paper describes two different approaches to perform the condition monitoring of offshore wind farms, the first one involves thresholds-based analysis, while the other involves pattern recognition.