Advanced Fault Detection of Synchronous Generators Using Stray Magnetic Field

Many methods used for precise fault detection in salient pole synchronous generators (SPSGs) often require
a priori
knowledge of the healthy case, but this requirement impedes application of the methods since an accurate analysis of different machine quantity waveforms is not usually carried out during commissioning. The inspection and maintenance processes in SPSGs are also costly and time consuming; therefore, reliable methods that can detect and discriminate between different faults without comparison with the healthy condition are highly desirable. This article proposes a precise method for detection and discrimination between different fault types in the SPSG. The method does not require healthy machine data and is applied to diagnose both interturn short circuits (ITSCs) in the field winding and dynamic eccentricities (DEs). The proposed nonintrusive detection algorithm is based on advanced signal analysis of stray magnetic field data and can be applied during SPSG operation. The method is highly precise for monitoring the condition of the rotor field winding and yields a unique pattern for diagnosing possible ITSC faults. Moreover, a distinctive pattern for the DE fault enables the discrimination between both considered failures, even if they are present at the same time. The proposed method is validated through finite-element modeling and experimentally on 100-kVA and 22-MVA SPSGs to demonstrate its applicability in real power plants.