Wind Turbine Fault Forensic Analysis of SCADA Data Using Machine Learning Techniques

摘要

Methodologies and tools that can support the task of finding out the possible causes of a fault manifested by a specific alarm or a set of alarms can benefit wind farm owners to increase availability and production and reduce costs. On the other hand, data availability from SCADA of the wind park has a great potential of information that can support this specific task, more when it is already available and using this data for fault diagnosis does not require any type of extra implementation or hardware installation in the wind turbine. However, due to the high number of available variables and data, analysing them can be a high time consuming task and when just well-known related variables are analysed hidden causes or not common causes cannot be or are hard to be found. For all these reasons, in this work, we present a methodology and tool, part of Smartive platform, that been fed by all available SCADA data and other source of information, can support fault forensic analysis in order to find the main causes of faults.