Transmission line corridor (i.e., Right-of-Ways (ROW)) clearance management plays a critically important role in power line risk management and is an important task of the routine power line inspection of the grid company. The clearance anomaly detection measures the distance between the power lines and the surrounding non-power-facility objects in the corridor such as trees, and buildings, to judge whether the clearance is within the safe range. To find the clearance hazards efficiently and flexibly, this study thus proposed an automatic clearance anomaly detection method utilizing LiDAR point clouds collected by unmanned aerial vehicle (UAV). Firstly, the terrain points were filtered out using two-step adaptive terrain filter and the pylons were detected in the non-terrain points following a feature map method. After dividing the ROW point clouds into spans based on the pylon detection results, the power line point clouds were extracted according to their geometric distribution in local span point clouds slices, and were further segmented into clusters by applying conditional Euclidean clustering with linear feature constraints. Secondly, the power line point clouds segments were iteratively fitted with 3D catenary curve model that is represented by a horizontal line and a vertical catenary curve defined by a hyperbolic cosine function, resulting in a continuous mathematical model of the discretely sampled points of the power line. Finally, a piecewise clearance calculation method which converts the point-to-catenary curve distance measurements to minimal distance calculation based on differential geometry was used to calculate the distance between the power line and the non-power-facility objects in the ROW. The clearance measurements were compared with the standard safe threshold to find the clearance anomalies in the ROWs. Multiple LiDAR point clouds datasets collected by a large-scale UAV power line inspection system were used to validate the effectiveness and accuracy of the proposed method. The detected results were validated through qualitatively visual inspection, quantitatively manual measurements in raw point clouds and on-site field survey. The experiments show that the automatic clearance anomaly detection method proposed in this paper effectively detects the clearance hazards such as tree encroachment, and the clearance measurement accuracy is decimeter level for the LiDAR point clouds collected by our UAV inspection system.

In this paper, gas chromatography–mass spectrometry (GC–MS) and positron annihilation lifetime spectroscopy (PALS) were used to probe the changes of oligomers and the polydimethylsiloxane (PDMS) network in silicone rubber, after different durations of UVA/UVB irradiation. At the early stage (300 h) of UVB irradiation, D${}_4$ was generated and the lifetime of ${\tau }_3$ also increased, indicating the rupture of the Si-O bond in the PDMS network. These two aging processes were termed the post curing process and the chain session process. The new finding was that UVA could only induce the post curing process; UVB causes the rupture of the chemical bond in silicone rubber. Photons of UVB could break the C-H bond, and then trigger the backbiting decomposition of PDMS, breaking the Si-O bond, while the photons of UVA cannot. The fact that D${}_4$ was generated after UVB irradiation can be used to evaluate the UVB stability of silicone rubber in the future.

Purpose: An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection robot cross obstacle automatically. This paper aims to propose an improved approach which is called adaptive homomorphic filter and supervised learning (AHSL) for overhead ground wire detection. Design/methodology/approach: First, to decrease the influence of the varying illumination caused by the open work environment of the inspection robot, the adaptive homomorphic filter is introduced to compensation the changing illumination. Second, to represent ground wire more effectively and to extract more powerful and discriminative information for building a binary classifier, the global and local features fusion method followed by supervised learning method support vector machine is proposed. Findings: Experiment results on two self-built testing data sets A and B which contain relative older ground wires and relative newer ground wire and on the field ground wires show that the use of the adaptive homomorphic filter and global and local feature fusion method can improve the detection accuracy of the ground wire effectively. The result of the proposed method lays a solid foundation for inspection robot grasping the ground wire by visual servo. Originality/value: This method AHSL has achieved 80.8 per cent detection accuracy on data set A which contains relative older ground wires and 85.3 per cent detection accuracy on data set B which contains relative newer ground wires, and the field experiment shows that the robot can detect the ground wire accurately. The performance achieved by proposed method is the state of the art under open environment with varying illumination.

Silicone rubber is widely used as an insulating material. In this article, silicone rubber samples were prepared by varying the content of crosslinker (2,5-bis(tert-butyl-peroxy)-2,5-dimethylhexane, DBPMH), and the free volume holes in the samples were investigated by means of positron annihilation lifetime spectroscopy (PALS) measurement. The surface chemical structure, surface micromorphology and water diffusion of the samples after corona discharge treatment were studied by FTIR, SEM and EIS measurements, respectively. As the crosslinker weight ratio increased from 0.2 wt.% to 1.5 wt.%, the mean free volume hole size first decreased and then remained unchanged. However, the concentration of free volume holes did not vary as the crosslinker weight ratio increased. SEM morphologies show that surface cracks were produced on samples having high crosslinking levels after corona treatment. The water diffusion coefficient of samples after corona treatment increased from 3.13 × 10⁻¹⁰ cm² s⁻¹ to 17.68 × 10⁻¹⁰ cm² s⁻¹ in the initial immersion period, as the crosslinker weight ratio increased from 0.2 wt.% to 3.0 wt.%. The results indicated that deterioration of samples with high crosslinking levels were more serious and water repellency more easily lost. The corona resistance ability of low crosslinking level silicone rubber stems from internal low molecular weight molecules.

In this study, silicone rubber (SiR) with 0, 90, and 180 parts of aluminum hydroxide (Al(OH)₃, ATH) contents prepared in the laboratory was treated in a certain concentration of NO₂ for 0, 12, 24, and 36 h. Fourier transform-infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and thermogravimetry (TG) were used to study the changes in the surface structure and thermal stability of SiR, as well as the influence of Al(OH)₃ on the properties of SiR. According to AFM, the root-mean-square roughness of ATH-90 SiR was 192 nm, which was 2.7 times of ATH-0 SiR. With the incorporation of ATH, the surface of SiR became more susceptible to corrosion by NO₂. According to FT-IR and XPS, with the increase in aging time, the side chain Si-CH₃ of polydimethylsiloxane (PDMS) was oxidized gradually and a few of nitroso -NO₂ groups were formed. According to TG, the incorporation of ATH caused the maximum decomposition rate temperature of PDMS to advance from 458.65 °C to 449.37 and 449.26 °C, which shows that the thermal stability of SiR degraded by adding ATH. After NO₂ aging, a new decomposition stage appeared between 75 and 220 °C (stage Ⅰ), and this decomposition trend was similar to aluminum nitrate, which was proven to reduce the thermal stability of PDMS. The effects of NO₂ on the surface structure and thermal stability of different ATH contents of silicone rubber were preliminarily clarified by a variety of characterization methods, which provided ideas for the development of silicone rubber resistant to NO₂ aging.