Partial Discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. The measurement of PDs is useful in the diagnosis of electrical equipment because PDs activity is related to different ageing mechanisms. Classical Phase-Resolved Partial Discharge (PRPD) patterns are able to identify PD sources when they are related to a clear degradation process and when the noise level is low compared to the amplitudes of the PDs. However, real insulation systems usually exhibit several PD sources and the noise level is high, especially if measurements are performed on-line. High-frequency (HF) sensors and advanced signal processing techniques have been successfully applied to identify these phenomena in real insulation systems. In this paper, spectral power analyses of PD pulses and the spectral power ratios at different frequencies were calculated to classify PD sources and noise by means of a graphical representation in a plane. This technique is a flexible tool for noise identification and will be useful for pulse characterization.

In this paper, the applications of thermoplastic, thermoset polymers, and a brief description of the functions of each subsystem are reviewed. The synthetic route and characteristics of polymeric materials are presented. The mechanical properties of polymers such as impact behavior, tensile test, bending test, and thermal properties like mold stress-relief distortion, generic thermal indices, relative thermal capability, and relative thermal index are mentioned. Furthermore, this paper covers the electrical behavior of polymers, mainly their dielectric strength. Different techniques for evaluating polymers’ suitability applied for electrical insulation are covered, such as partial discharge and high current arc resistance to ignition. The polymeric materials and processes used for manufacturing cables at different voltage ranges are described, and their applications to high voltage DC systems (HVDC) are discussed. The evolution and limitations of polymeric materials for electrical application and their advantages and future trends are mentioned. However, to reduce the high cost of filler networks and improve their technical properties, new techniques need to be developed. To overcome limitations associated with the accuracy of the techniques used for quantifying residual stresses in polymers, new techniques such as indentation are used with higher force at the stressed location.

In order to investigate how artificial neural networks (ANNs) have been applied for partial discharge (PD) pattern recognition, this paper reviews recent progress made on ANN development for PD classification by a literature survey. Contributions from several authors have been presented and discussed. High recognition rate has been recorded for several PD faults, but there are still many factors that hinder correct recognition of PD by the ANN, such as high-amplitude noise or wide spectral content typical from industrial environments, trial and error approaches in determining an optimum ANN, multiple PD sources acting simultaneously, lack of comprehensive and up to date databank of PD faults, and the appropriate selection of the characteristics that allow a correct recognition of the type of source which are currently being addressed by researchers. Several suggestions for improvement are proposed by the authors include: (1) determining the optimum weights in training the ANN; (2) using PD data captured over long stressing period in training the ANN; (3) ANN recognizing different PD degradation levels; (4) using the same resolution sizes of the PD patterns when training and testing the ANN with different PD dataset; (5) understanding the characteristics of multiple concurrent PD faults and effectively recognizing them; and (6) developing techniques in order to shorten the training time for the ANN as applied for PD recognition Finally, this paper critically assesses the suitability of ANNs for both online and offline PD detections outlining the advantages to the practitioners in the field. It is possible for the ANNs to determine the stage of degradation of the PD, thereby giving an indication of the seriousness of the fault.

Emerging tropical cities are experiencing rapid population growth and development, which can greatly affect the thermal environments. The effects of roadside trees and road orientation on the outdoor thermal environment were investigated on four different roads in Kuala Lumpur, Malaysia. Field measurements were conducted to assess outdoor thermal environments, where the selection of sites was based on different roadside tree morphological features and road orientations. Outdoor air temperature (T_a), relative humidity (RH), globe temperature (T_g), wind speed (WS), and wind direction (WD) were measured. Absolute humidity (AH) was estimated based on relative humidity and air temperature. Planting dense canopy trees with an average sky view factor (SVF) of 0.07 reduced the mean radiant temperature (T_mrt) by 35% and the physiological equivalent temperature (PET) by 25%. East–West (E–W) and Northwest–Southeast (NW–SE) oriented roads had high PET values of 41 °C and 43 °C, respectively. North–South (N–S) and Northeast–Southwest (NE–SW) orientated roads had lower PET values (37 °C), providing improved outdoor microclimate. Roadside trees provided greater cooling potential in E–W and NW–SE oriented roads. The findings are useful for urban road design in tropical cities in order to improve the outdoor thermal environment and pedestrian comfort.