Insulators play a crucial role in electric power systems by isolating high-voltage currents and supporting conductors. However, insulators exposed to outdoor conditions for extended periods are susceptible to faults caused by contamination, aging, and damage, leading to flashovers that may result in grid outages and economic losses. Accurate assessment of insulator condition is paramount for the safe operation of power systems. Non-contact monitoring methods, which do not interfere with the normal operation of the power system, have become mainstream in insulator condition monitoring, contrasting with traditional contact-based detection. Among these methods, optical imaging technology has garnered significant attention due to its non-contact, non-destructive, high sensitivity, and intuitive characteristics. Optical imaging technology captures reflections, transmissions, and absorptions in different spectral bands to gather information about the surface and interior of insulators, thereby determining the type of faults they may exhibit. This article reviews optical imaging detection methods applied in the field of insulator condition assessment, including infrared thermography, ultraviolet imaging, visible light imaging, and some promising optical monitoring technologies. Additionally, the advantages and limitations of these methods under various insulator fault conditions are analyzed, and challenges in industrial applications are discussed. The purpose of this review is to provide a comprehensive and systematic reference for the application of optical imaging technology in insulator condition assessment, aiming to enhance the efficiency and safety of power system operation and maintenance.

When a high-speed train approaches an insulated split-phase section embedded between neighbouring power supply arms carrying powers with different phases, the vehicle-mounted vacuum circuit breaker (VCB) needs to be switched off to avoid short-circuit fault during the phase-changing procedure. At the moment of switching the VCB contacts, the arc is triggered easily, accompanying with overvoltage impulse. As the core of the whole system, the traction transformer frequently suffers the invasion of the overvoltage impulse, which possibly causes partial discharge or breakdown accidents. To evaluate the impact of overvoltage on the transformer, it is essential to observe the overvoltage distribution at different positions in the transformer. As an equivalent circuit model of the traction transformer involving the spatially distributed capacitance is built based on the improved capacitor network methodology (ICNM), the partial discharge risk in the transformer has been assessed. Ultimately, the multi-physics coupling models based on the finite element method have been launched for observe the specific distribution of the multiphysics field for verifying the validity of equivalent circuit model based on ICNM. These works lay the theoretical foundation for guiding the design of insulation and the thermal dissipation settings of the traction transformer, considering the threat brought from impulse.

So far, silicone rubber (SiR) insulators have been widely used in the power industry all over the world, due to their outstanding insulation properties with high reliability. In practice, some of the insulators are applied in the remote places with harsh environmental conditions such as high altitude, high temperature and high humidity etc. Herein, the currently-existing aging mechanisms have been investigated, as some novel insights into these testing and evaluation methods have been proposed. Via the investigation, it can be found that thermal oxygen aging tends to occur, when insulators are exposed to an environment surrounded by hot air. To analyse the different aging mechanisms of SiR insulator sheds, four types of aging testing and evaluation methods have been systematically summarized, based on the surface structural, chemical, optical, and electrical properties. The conclusion is that non-destructive and non-contact methods, such as HSI, along with the multi - source information fusion methods, are becoming increasingly popular in the assessment of silicone rubber insulator sheds aging. These research efforts provide assurance for reducing the incidence of pollution flashover accidents in power transmission lines and ensuring the safe and stable operation of power transmission and transformation equipment.

The dynamic response characteristics, including maximum jump height and unbalanced tension, of isolated‐span transmission lines after ice‐shedding are investigated by means of experiments. A reduced‐scale modelling method for ice‐shedding from conductor lines is presented and verified with numerical simulations and full‐scale test results in the literature. A parameter study on dynamic responses of isolated‐span conductors under three ice‐shedding scenarios, including whole span ice‐shedding, partial ice‐shedding and unzipping ice‐shedding, is carried out by means of reduced‐scale modelling tests. The effects of these parameters on the maximum jump height at typical positions and unbalanced tension in the tension tower are obtained. It is observed that the partial ice‐shedding scenario may be the worst situation for electrical insulation clearance rather than the whole span ice‐shedding scenario. Moreover, the position of maximum jump height along the span of isolated‐span transmission lines after ice‐shedding could be at around 2/5 of span length, which is different from the conventional opinion that the position is at the midpoint. The results may provide a foundation for the defining of the insulation clearance for an isolated‐span transmission line and the structure design of tension tower arms in an iced zone.

Insulator pollution degree detection is of great significance for preventing a flashover. Equivalent salt deposit density, leakage current, and surface pollution layer conductivity are commonly used to describe insulator pollution degree; however, all these parameters have limitations in field application and real‐time monitoring. Non‐contact detection methods, such as infrared thermal imaging and ultraviolet imaging, only image insulators in a specific band, which makes the extracted features limited. Hyperspectral technology is the new comprehensive image data technology based on imaging spectroscopy that has the advantages of multiband high resolution. Therefore, a method based on hyperspectral image and spectral characteristics is proposed to fully characterize natural pollution information and accurately detect the pollution degree of insulators. The hyperspectral spectral line characteristics, image texture, and colour characteristic data of insulators were extracted and fused and then used to establish the pollution degree detection model on the basis of integrated learning classification algorithms. The results show that the model based on fusion data has an accuracy rate of 95.0%, which is more accurate than the model based on spectral line features only. Consequently, hyperspectral technology can realize the non‐contact detection of pollution degree and provide some guidance for cleaning the contamination of external insulation.