Study On Location Of Transformer Partial Discharge Source Based On Ultrasonic Time Difference Of Arrival

The construction and development of UHV transmission in China has laid a solid foundation for long-distance power transmission,and is an important link to achieve the goal of intelligent,safe and strong power grid.Transformer occupies an important position in the process of power transmission,so the safe and stable operation of transformer is related to the safety of the whole power grid.Insulation is the first line of defense to ensure the safe and stable operation of high-voltage electrical equipment,and the key factor of insulation deterioration caused by partial discharge.Therefore,it is of theoretical and engineering practical significance to carry out the detection and location of transformer partial discharge.The main contents of this paper are as follows:(1)The basic theory of partial discharge is explained,the mechanism of partial discharge generating ultrasound is analyzed,and the principle of using ultrasound to locate the partial discharge source is introduced..(2)Aiming at different noise environments,the time difference estimation algorithm under Gaussian noise and impulse noise is studied separately,the correlation waveform comparison method of CEEMDAN threshold noise reduction optimization is proposed for Gaussian noise conditions,and the covariant correlation method of nonlinear transformation is proposed for impulse noise.Environment and simulation verify that the proposed algorithms are better than traditional time difference estimation algorithms in terms of estimation accuracy.(3)The commonly used algorithms for solving positioning equations are explored: least squares method,genetic algorithm,particle swarm algorithm,and through simulation and comparison,it is concluded that particle swarm algorithm is relatively superior in positioning accuracy and convergence speed.(4)The effectiveness of the method proposed in this paper is verified by field examples.The TDOA estimation algorithm proposed in this paper is used to estimate the TDOA,and the estimated TDOA is brought into the positioning equation,which is solved by particle swarm optimization.The results meet the engineering requirements.