Partial discharge (PD) is an important phenomenon that reflects the insulation condition of electrical equipment. In order to protect the safety of power grids, it is of significance to diagnose the type of insulation defects inside the equipment accurately and early through PD pattern recognition. In this article, phase resolved pulse sequence (PRPS) graphs in 3D were constructed by the PD pulse data of the gas-insulated switchgear (GIS) acquired, then the histogram of oriented gradient (HOG) features were extracted directly from the 3D PRPS graphs, and finally the attribute selective Naïve Bayes classifier was used to recognize the discharge pattern. In addition, this method was compared with two traditional methods, i.e., the statistical method and the grayscale gradient co-occurrence matrix method, from three aspects. The result shows that 3D PRPS graphs have different morphology characteristics in vision under different defects, and the similarity among different voltages applied is higher than among different defects, so it is reasonable to use them as the basis for PD pattern recognition. The contrast indicates that the HOG method not only has the highest accuracy with the least requirement for pretreatment and training, but it also has robustness when the voltage applied changes. Consequently, this method has the universality for PD pattern recognition that is based on 3D PRPS graphs.

Partial discharge (PD) leads to the generation of electrical, acoustic, optical, and thermal signals. The propagation characteristics of optical signals in gas insulated metal-enclosed transmission lines (GIL) are the basis of optical detection research. This paper simulates the propagation of PD optical signals in GIL through modeling GIL with different structures and specification parameters. By analyzing the optical parameters on the probe surface and the detection points when the PD source position is different, the influence of the difference in specifications caused by the voltage level on the propagation of the GIL PD optical signal is studied. The results show that the GIL cavity structure will affect the faculae distribution and the relative irradiance (RI) of the detection surface; the PD source position has a huge impact on the faculae distribution on the detection surface, but has little influence on the RI; as the voltage rises, the faculae distribution on the detection surface becomes more obvious, and the mean of RI decreases. The above results have the reference value for the manufacture of GIL equipment and the research of PD optical detection. When the specular reflection coefficient of surface material is smaller and the diffuse reflection coefficient is larger, the outline of the light spot is clearer, the proportion of brighter parts is larger, and the maximum value of the RI is larger.

For 110 kV and above tunnel-installed high-voltage (HV) cross-linked poly-ethylene (XLPE) cable systems, it is a normal procedure to adopt a cross-bonding scheme. The high-frequency current method is frequently used in the cross-bonded cable systems for on-site or online partial discharge (PD) detection by monitoring the signals on the cross-bonding wires. To further study the amplitude distribution characteristics of the PD signals, a parametric characteristic admittance model of a three-phase cable system in a tunnel is established based on Tylavsky’s formulas. The model is used to calculate the amplitude distribution formula of the PD pulse current on the cross-bonding wires. In addition, the influence of cable laying and tunnel environment on the amplitude distribution is also studied. Finally, the correctness of the model and the conclusion are verified by simulation experiments and on-site tests. The results show that the signal amplitude distribution is determined by the ratio of the characteristic admittances. As the distance between the cables and the distance from the inner wall of the tunnel increase, the amplitude difference gradually decreases.

During the field test, if the input and output lines and intervals of the withstand voltage test after the GIS equipment are segmented, and a non-self-recovery discharge or breakdown occurs during the test, only the hearing of the human ear will determine the exact location of the failure. It is more difficult, and it is easy for misjudgement to waste manpower, material resources and cause unnecessary damage to equipment. Therefore, in the field AC withstand voltage test of GIS equipment, finding the location of discharge breakdown is a key technical problem that needs to be urgently solved on the site. This paper studies the propagation characteristics and detection principles of electromagnetic wave signals and vibration signals that cause breakdown faults in 1000kV GIS, and develops a positioning system based on combined acoustic-electrical detection technology for AC withstand voltage of UHV GIS in the field. In the test, it was verified through actual test cases that the method can quickly and accurately locate the location of the breakdown discharge, and provided a set of convenient and effective technical means to ensure the smooth on-site withstand voltage test of GIS equipment.