Study On Capacitive Sensing For Insulation Aging Of Dielectric Materials

Dielectric materials have low electrical conductivity and good dielectric strength properties,are the insulating materials widely used in wires,cables,motors and other electrical equipment.Cable insulation will be prone to aging under the long-term moisture,extreme temperatures,chemical corrosion,and mechanical stress influences.Cable insulation aging may lead to faults like short-circuit and corona discharge,causing great economic losses.Therefore,timely and accurate detections of insulation aging ensure the safe operation of power equipment.In this dissertation,capacitive sensing based on the coplanar capacitive sensor was studied and applied to the insulation aging detections.First of all,finite element model of a flexible coplanar sensor was established based on the Ansys Maxwell software.Modeling,solution setups and post processes were analyzed in detail.Then,influence of the cable center conductor on the electric field distribution and output capacitance composition were studied.Moreover,the structure parameters and the performance indexes of the coplanar capacitive sensor were introduced.Followed by the relationships between the performance indexes and the structure parameters based on the flexible coplanar sensor were studied by simulations,the optimization method of the sensor structure parameters was given and the influences of the sensor substrate and the sensor covering arc-angle were discussed.The simulation experiments of water tree aging of insulation based on the flexible coplanar capacitance sensor was carried out,and the simulation results showed that the flexible coplanar capacitance sensor can detect the different degree of water tree aging of cable insulation effectively.A flexible coplanar capacitive sensor was developed for benchmark experiment.The result showed that the experimental result is in good agreement with the simulation result.Therefore,coplanar capacitive sensor can be used to detect the cable insulation effectively.Finally,the relationship between the relative permittivity and the output capacitance of the multi-layer sample containing conductor was studied.The mathematical model of the parameter estimation algorithm was given.Then,the model was established by using the multiple nonlinear regression algorithm and the GABP network algorithm.The results showed that the GABP network parameter estimation algorithm has better prediction accuracy in solving the inverse problem of the multi-layer sample containing conductor.