Title :
Local degradation diagnosis for cable insulation based on broadband impedance spectroscopy
Author :
Zhiqiang Zhou ; Dandan Zhang ; Junjia He ; Menghu Li
Author_Institution :
State Key Lab. of Adv. Electromagn. Eng. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
The diagnosis of portions in a cable that are severely degraded before breakdown occurs is of prime importance. This paper presents a novel method based on the broadband impedance spectroscopy (BIS) to precisely locate local degradations in a cable and determine their insulation conditions. Firstly, an integral transform (IT) algorithm is developed to transform the frequency-dependent BIS to a spatial domain function, which characterizes the changes of propagation constant along the cable and then degradations can be located. Next, a procedure based on the particle swarm optimization (PSO) is worked out to minimize the error between the measured impedance of the cable and that calculated by a model, and then the complex dielectric permittivity for each of the degradations is figured out to assess the insulation condition. Simulation results show that portions with loss tangent (tan δ) higher than the adjacent regions can be clearly located with a spatial resolution as short as 0.01 m even if the cable length is 500 m. After the PSO procedure, tan δ of the degraded portions can be obtained to indicate the severity of the degradation. The validity of the method is also verified by experiments performed on a 50 m long cable.
Keywords :
cable insulation; particle swarm optimisation; transforms; BIS; broadband impedance spectroscopy; cable insulation; dielectric permittivity; integral transform algorithm; local degradation diagnosis; particle swarm optimization; size 0.01 m; size 50 m; size 500 m; spatial domain function; Degradation; Impedance; Impedance measurement; Mathematical model; Power cable insulation; Power cables; Cable insulation; broadband impedance spectroscopy (BIS); integral transform (IT); local degradation diagnosis; particle swarm optimization (PSO);
Journal_Title :
Dielectrics and Electrical Insulation, IEEE Transactions on
DOI :
10.1109/TDEI.2015.004799