Metal particles and dirty contaminants on the spacer surface are mainly considered to be the critical factor in sudden flashovers. Understanding the discharge characteristics as well as the detectability of metal particles in the gas-insulated switchgear (GIS) will be helpful in improving its safety and reliability. In this paper, a high-sensitivity measurement system based on cross-reference pulse current (PC) and ultra-high-frequency (UHF) methods was established. The PC and UHF signals generated by partial discharges (PDs) of metal particles of different lengths (Φ = 0.5 mm, L = 2, 5, 8, and 10 mm) at different positions on a real spacer surface were studied. The PD characteristics and detectability of the metal particles on the spacer surface were obtained while the detection limitation was also discussed. It is found that under PD test condition, the apparent charge of the PDs is less than 1 pC for particles shorter than 5 mm, and the conventional PD detection method have limitations in detecting these short particles on the spacer surface. Under operation condition, only the apparent charge of particles longer than 8 mm can exceed 1 pC, which means it is difficult to detect the particles shorter than 8 mm in field. However, the result indicates that even the 5 mm long particle will be harmful to the GIS. Meanwhile, it is also been found that the detection sensitivity also has a great influence on the judgement of PD severity. This study is of great interest for understanding the PD characteristics, discharge levels, and detectability of short metal particles on spacer surface.

Gas insulated switchgear (GIS) insulation failures occur frequently in field operations, seriously affecting the reliability of power systems. Fault statistics show that nearly half of the insulation flashover faults in field operation are strongly related to the switching operation, and metal particles are considered to be a crucial cause of flashover. The impact vibration generated by the switching operation may activate the metal particles and make them lift and jump in the GIS, reducing the insulation performance. Therefore, in this study, an experimental platform was established to simulate the impact vibration generated by the switching operation. The flashover characteristics induced by metal particles under impact vibration were studied, and the movement behavior of metal particles was also analyzed. The results show that metal particles lying on the enclosure lift under the impact vibration and then keep jumping in the GIS. These particles can jump to cause insulator flashover with high probability after the impact vibration. The longer the metal particles, the higher the probability of insulator flashover, and the shorter the average jump duration of the metal particles before the flashover. Moreover, compared with the flake particles, linear particles are more likely to cause insulator flashover after the impact vibration. This study demonstrates the mechanism of insulator flashover caused by metal particles under impact vibration, which provides a significant support for understanding the insulation failures strongly related to the switching operation in practical applications.

HFCT method is a common detection technology for partial discharge (PD) in transformer. However, it suffers a lot from electromagnetic interference in field applications because conventional detection band of it is relatively low, usually in HF band. In this paper, a HFCT, which frequency response includes the whole of the VHF band and extends up to 500 MHz in the UHF band, is adopted to improve the anti-interference capacity of HFCT method. And we make a full investigation on the detection characteristics of HFCT method in UHF band based on an actual 220 kV transformer with complete internal structures. Four typical defects model is established as PD sources, additionally, conventional methods are also adopted in the experiment to make comparison with HFCT method in UHF band. The experiment results indicate that HFCT method can detect PD effectively in UHF band, and the detection sensitivity of it is no less than that of conventional methods. The results confirm the effectiveness of HFCT method in UHF band, therefore, the problem of low anti-interference capacity of conventional HFCT method that detects PD in HF band can be overcome. It offers a new effective and practical solution for transformer field monitoring of PD, especially for the transformers to which internal antenna UHF method can't be applied due to the lack of dielectric window.

Gas insulated switchgear equipment (GIS) is widely used in power system, and more attention has been paid to discharge defects than mechanical defects. However, since mechanical defects are a major cause of the failure in GIS, it is of great significance to carry out relevant research on mechanical defects. Detection and diagnosis methods of mechanical defects based on vibration signal are studied in this paper. Firstly, vibration mechanisms of GIS are analyzed. Due to structural differences between single phase insulated type GIS and three phase insulated type GIS, there are big differences in vibration mechanisms between the two types of GISs. Secondly, experimental research on mechanical defects is carried out based on a 110 kV GIS equipment and a self-developed vibration detection system; results show that mechanical defects can be diagnosed by analyzing signal amplitude, frequency spectrum and waveform distortion rate, and a large current is more beneficial for diagnosing mechanical defects. Lastly, field application has been carried out on 220 kV GIS equipment, and a poor contact defect is found, demonstrating that abnormal diagnosis can be realized by method proposed in this paper. Experimental research and field application demonstrate the feasibility and effectiveness of detection and diagnosis method for mechanical defects based on vibration signal and provide experience for subsequent engineering application.

The ultra‐high frequency (UHF) method has been widely used in a gas‐insulated system (GIS) for partial‐discharge detection, and many achievements have been realised. In addition, many studies based on artificial defects have been made to confirm its validity. Therefore, the UHF method is generally believed to be sufficiently effective for GIS monitoring. However, in practical application, the authors find that for some micro‐crack discharge in GIS insulator, the UHF method has low sensitivity. To fully study the characteristics of the micro‐crack discharge in the GIS insulator, an experiment is conducted in this study using an actual post insulator with a micro‐crack defect. The current signal based on IEC 60270 standard and the radio‐frequency electromagnetic signal is simultaneously measured for thorough analysis. The results show that some submillimetre crack defects may occur in the GIS insulator. Its discharge is mainly presented as glow discharge, and the discharge signal frequency usually cannot reach the UHF band; thus, it cannot be effectively detected by the UHF method. This study provides complementary information to the applicability of the UHF method and inspires further study of the GIS insulator and its monitoring technology.

The insulation condition is the key to determining whether gas insulated switchgears (GISs) can operate stably and reliably. Partial discharge (PD) detection is an important technique for condition monitoring and evaluation in GIS. Acoustic emission (AE) method is commonly used in on-site PD detection. However, in field applications, there are often problems such as low signal-to-noise ratio (SNR) of measured ultrasonic signals and difficulty in extracting PD pulses. To solve this problem, a denoising method for GIS ultrasonic signals based on the combination of ultrasonic and ultra-high frequency (UHF) signals is proposed in this paper. Based on the difference in correlation between noise and PD signals, the noise in measured signal can be suppressed through accumulating and averaging of multiple ultrasonic signals, and the SNR of PD signal can be significantly improved. An actual 500-kV GIS experiment platform is established, and PD measurements for different types of defects are conducted. Then, a comparative study is conducted on the denoising performance of the proposed method and traditional denoising methods such as wavelet method and singular value decomposition (SVD) method. The results indicate that compared to traditional methods, the method proposed in this paper has a higher reduction in noise level. Especially for extremely low-SNR signals (PD pulses buried in noise), traditional methods have poor performance, while the proposed method can still extract the PD pulse form the noise. Furthermore, based on the denoised ultrasonic signals, the defect localization analysis is conducted to demonstrates the correctness of the denoising results. Finally, the proposed method is applied to on-site PD detection, which further evaluates the effectiveness of the denoising method.