Research On Vibration Characteristics Of Power Transformer And Monitoring Method Of Winding State

With the continuous improvement of the power grid voltage level and the increasing of transmission capacity,power transformers in actual operation will inevitably be subjected to more different degrees of short-circuit impact,which can easily lead to the loosening of the core lamination,the deformation of winding or the relaxation of pretightening force,and other problems.It will cause the decline of the insulation and mechanical properties of power transformers,and then the power transformer will fault.The on-line vibration analysis method can real-time monitor the running state of the internal components of power transformers,but it lacks the research on the vibration mechanism of the body(core and winding)and the theoretical criterion for reasonable analysis of the data acquisition.The vibration mechanism and the diagnostic criteria are not yet perfect.Therefore,this dissertation make an in-depth study of transformer vibration,vibration energy transfer process and the method of winding state through the theoretical analysis,COMSOL and MATLAB simulation,experimental analysis and other methods,using the SFZ11-1800/220 type and YNd11 connection of transformer winding oil immersed power transformer as the research object.The research work is of great significance for the safe and stable operation of power transformers.This dissertation makes a theoretical analysis and formula derivation of the vibration performance of power transformers,and uses the finite element analysis software COMSOL for the electric-magnetic-solid coupling simulation calculation of the winding vibration with rated current applied under the load test conditions of the 220 kV power transformer.It is showed by the results that the vibration performance of the transformer under load current condition are mainly 100 Hz,no high-frequency component and the simulation signal is highly correlated with the measured signal.It is proved that the accuracy of the multiphysics field winding vibration simulation model.A power transformer vibration information acquisition and test platform was set up.No-load and load tests were carried out for 66 kV and 220 kV power transformers.The no-load and load vibration signals were collected and analyzed.The analysis results showed that: The no-load and load-vibration characteristics of power transformers are basically consistent with the theoretical analysis of iron cores and windings,and the vibration of the core and thewinding is not affected by the power transformer model and voltage level.Based on CEEMD single channel blind source separation(BSS)algorithm is studied.Using this algorithm,the simulation vibration signals are aliasing and separated and the simulation of vibration signal of no-load and load test.The simulation results show that the algorithm is effective and repeatable.At the same time,using this algorithm to successfully separate the winding vibration signal from the online monitoring vibration signal,and uses the neural network self-learning method to perform self-identification of the separated signal,and automatically selects the winding vibration signal from the online vibration signal separation result.The CEEMD energy entropy algorithm is studied and applied to the online monitoring of power transformer winding operation status.The validity of this method is verified by the CEEMD decomposition and energy entropy comparison analysis of the online monitoring test data.The algorithm can directly reflect the difference of the vibration signal on the surface of the tank and effectively quantify the deformation degree of the winding of the power transformer after the short circuit impact and this method is not affected by the size of the load current and has stability.