Anti-Interference and Location Performance for Turn-to-Turn Short Circuit Detection in Turbo-Generator Rotor Windings

• Published in: Energies (Basel) 2019-04, Vol.12 (7), p.1378
• Main Authors: Wu, Yucai, Ma, Guanhua
• Format: Article
• Language: English
• Subjects: Asymmetry; Circuits; detection coil; dynamic eccentricity; Electric potential; Electric power; Energy; Fault diagnosis; Generators; Harmonics; judge; Load; Magnetic fields; Magnetic permeance; Methods; Nuclear power plants; rotor winding; Sensors; Short circuits; Symmetry; turbo-generator; Turbogenerators; turn-to-turn short circuit; Voltage; Waveforms
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en12071378

Online and location detection of rotor winding inter-turn short circuits are an important direction in the field of fault diagnosis in turbo-generators. This area is facing many difficulties and challenges. This study is based on the principles associated with the U-shaped detection coil method. Compared with dynamic eccentricity faults, the characteristics of the variations in the main magnetic field after a turn-to-turn short circuit in rotor windings were analyzed and the unique characteristics were extracted. We propose that the degree of a turn-to-turn short circuit can be judged by the difference in the induction voltage of the double U-shaped detection coils mounted on the stator core. Here, the faulty slot position was determined by the local convex point formed by the difference in the induced voltage. Numerical simulation was used here to determine the induced voltage characteristics in the double U-shaped coils caused by the turn-to-turn short circuit fault. We analyzed the dynamic eccentricity fault as well as combined the fault of a turn-to-turn short circuit and dynamic eccentricity. Finally, we demonstrate the positive anti-interference performance associated with this fault detection method. This new online detection method is satisfactory in terms of sensitivity, speed, and positioning, and overall performance is superior to the traditional online detection methods.