Abstract – Traditionally power stations have performed maintenance on their critical machines on a time-based schedule, but this often resulted in activities occurring before they were necessary. Over the past 20 years, there has been a shift in the industry towards condition-based maintenance. This strategy requires the collection of a variety of data to detect most ageing related mechanisms that can be used to better schedule and plan maintenance. Initially, data was collected manually and infrequently, but once the benefits of condition monitoring started to be realized this has more recently shifted to continuous real time monitoring. Today, there is another shift away from application specific software to accessing a variety of data on a common platform and allowing for a more comprehensive analysis.
The most critical machines in a power plant are obviously the turbine generator sets. The generator rotor and stator windings are generally very reliable but they do age over time, thus reducing their electrical and mechanical strengths. This paper will focus on detecting turbine generator rotor and stator winding problems prior to failure using an integrated approach, and a case example including detection of partial discharge, rotor flux, and stator endwinding vibration will be discussed.
