A system for turbogenerator predictive maintenance based on Electrical Signature Analysis

This paper proposes a prototype to detect incipient faults in non-salient pole synchronous generators based on the Electrical Signature Analysis (ESA) technique. The methodology consists in taking measurements of the machine stator voltages and currents and processing the acquired signals. By analyzing the voltages and currents spectra, it is possible to distinguish a faulty condition from a healthy one and to infer the failure type of the generator. This is summarized in a set of ESA failure patterns, which were proved through tests conducted in a custom made scale model laboratory. The custom laboratory setup consists of a small fault injection capable two-pole synchronous generator driven by an inverter-fed induction motor. The proposed prototype is operating in four turbogenerators of a Brazilian power plant. The main advantages of the presented system are the low intrusiveness, the ease of installation and it is economically viable. Moreover, the ESA failure patterns are based on defined frequencies and the structural features of the machine.