# Environmental Effects on HV Dielectric Materials and Related Sensing Technologies
## 2 Analyses and Discussions
Different radiation patterns within distinct dielectric materials correspond to a different power density. The improvement of PD detection techniques relies on an accurate interpretation of the EM spectra emitted from discharge zones. A study of the coupling between the EM radiation generated by PD and electric or electronic systems is of real interest as novel sensing techniques use the available HV infrastructure to detect electrical faults [88]. The EM radiation emitted from PD can be characterized by its amplitude, frequency band and time of occurrence. These are determined by the rate of the ionization process and the dimensions of the cavities in which a plasma discharge (also called PD) is created [89]. The repetitive breakdown of gas within the dielectric cavities in insulators is the main source of intense EM radiation. The PD signal is characterized by the amplitude and spectral distribution of the EM signal. These characteristics, together with the rate of discharge activity, can assist in identifying the type of PD-related faults in the HV network. It was shown in [90] that the radiation pattern emitted from a PD source from a fault-like cavity in a HV insulator is determined by the intensity of the source and the condition and geometry of the dielectric material. The diffraction pattern depends on the geometry and characteristics of insulating materials. The cross-sectional amplitude in tandem with field investigations showed that the power generated from a PD source depends on the media in which it is located. The results show that a PD fault sensor must discriminate between EM radiation emitted from different insulators to assess their remaining service life. This is required as power densities obtained from insulating materials with different dielectric constants can indicate different levels of aging. Systems and methods for detecting defects on insulators have been proposed [91], and methods for the characterization, monitoring and management of their condition [92; 93; 101; 102; 103; 104; 105; 106; 107; 108; 109; 110; 111] were assessed. To quantify the state of degradation of HV insulators, health indices for asset condition assessment were proposed [112]. Recently, electromagnetic sensors were employed to detect the electromagnetic radiation associated with defective insulators [84; 113]. The electromagnetic sensing technique opened the path to the pre-fault detection of HV insulators using the overhead power line as the sensor [88; 114]. In [115], the authors developed the proposed technology in an Internet of Things (IoT) technology that currently monitors 24/7 power networks for incipient faults that can lead to insulator failure and power network breakdown. The system is mainly intended for the early detection of faults in a low-voltage distribution network in which at least two detectors are each located on one of two power poles at either end of a section of a power distribution line. Each detector includes a GPS unit, an uninterruptable power supply, a means of communication to send data to a base station, antenna sensors with a bandwidth of \(1\) MHz to \(3\) GHz for each wire in the power line, and a processor to receive signals from each sensor and collect data relating to them to build estimation and prediction pertaining to the state of the power network. A maintenance prioritization method, system and computer program product for HV insulators was also recently proposed [116]. The technology includes the collection of data including image data and status data for a plurality of HV components, such as power lines and bushings, building a three-dimensional image of each object, and estimating a risk factor of failure for each object by analyzing the information and the three-dimensional image of the object to compare with known characteristics of the object and a reference object description.