Research on Classification Algorithm Optimization of Transformer Vibration Eigenvalues
In the field of fault detection of power transformer based on the vibration signal eigenvalues,such diagnos-tic indexes as fundamental frequency ratio and total harmonics distortion are widely used at present.However,in case of normal operation of transformer,the multi-frequency signals such as 200 Hz or 300 Hz will be generated due to nonlinear effect of vibration source and resonance of mechanical parts,which reduces the classification of eigenval-ues to the normal and faulty conditions.For solving above problem,56 sets of vibration data of transformers at differ-ent voltage levels and at normal and fault conditions are collected,and the classification effect of traditional eigenval-ues is tested.Moreover,the finite element simulation model of three-phase power transformers with three voltage lev-els is set up,the vibration distribution characteristics on the oil tank surface and the causes of multi-frequency com-ponents are analyzed.The calculation formula of the fundamental frequency ratio and total harmonics distortion is op-timized,the classification effect of the two eigenvalues is improved.The Test results show that the classification effect of the two eigenvalues after optimization is improved by 47%and 28%,respectively.
万方数据
维普
