Investigations of Electrical Trees in the Inner Layer of XLPE Cable Insulation Using Computer-aided Image Recording Monitoring

Using a computer-aided image recording monitoring system, extensive measurements have been performed in the inner layer of 66 kV cross-linked polyethylene (XLPE)cables. It has been found that there are three kinds of electrical trees in the samples,the branch-like tree, the bush-like tree and the mixed tree that is a mixture of the above two kinds. When the applied voltage frequency is less than or equal to 250 Hz, only the mixed tree appears in XLPE samples, when the frequency is greater than or equal to 500 Hz, only the dense branch-like tree develops, both of which are attributed to the coexistence of non-uniform crystallization and internal residual stress in semicrystalline XLPE cables during the process of manufacturing. Through the fractal analyses of these electrical trees, it has been found that both the propagation and structure characteristics can be described by fractal dimension directly or indirectly. It is suggested that the propagation and structural characteristics of electrical trees are closely related to the morphology and the residual stress in material at low frequency, i.e., the propagation characteristics of electrical trees depends upon not only the boundaries between big spherulites and amorphous region, but also the impurity, micropore concentration and the relative position of needle electrode tip with respect to spherulites or amorphous region in the low frequency range. However, at high frequency, it has nothing to do with the morphology of material. It is suggested that the injection and extraction process of charge from and to dielectrics via the needle electrode are more intense at high frequency than in low frequency. Thus, it can form relatively uniform dielectric weak region in front of needle electrode, which leads to similar initiation and propagation characteristics of electrical trees at high frequency

The characteristics of electrical trees in the inner and outer layers of different voltage rating XLPE cable insulation

The statistical initiation and propagation characteristics of electrical trees in cross-linked polyethylene (XLPE) cables with different voltage ratings from 66 to 500 kV were investigated under a constant test voltage of 50 Hz/7 kV (the 66 kV rating cable is from UK, the others from China). It was found that the characteristics of electrical trees in the inner region of 66 kV cable insulation differed considerably from those in the outer region under the same test conditions; however, no significant differences appeared in the 110 kV rating cable and above. The initiation time of electrical trees in both the inner and the outer regions of the 66 kV cable is much shorter than that in higher voltage rating cables; in addition the growth rate of electrical trees in the 66 kV cable is much larger than that in the higher voltage rating cables. By using x-ray diffraction, differential scanning calorimetry and thermogravimetry methods, it was revealed that besides the extrusion process, the molecular weight of base polymer material and its distribution are the prime factors deciding the crystallization state. The crystallization state and the impurity content are responsible for the resistance to electrical trees. Furthermore, it was proposed that big spherulites will cooperate with high impurity content in enhancing the initiation and growth processes of electrical trees via the ‘synergetic effect’. Finally, dense and small spherulites, high crystallinity, high purity level of base polymer material and super-clean production processes are desirable for higher voltage rating cables

A Code Reviewer Recommendation Approach Based on Attentive Neighbor Embedding Propagation

Code review as an effective software quality assurance practice has been widely applied in many open-source software communities. However, finding a suitable reviewer for certain codes can be very challenging in open-source communities due to the difficulty of learning the characteristics of reviewers and the code-reviewer interaction sparsity in open-source software communities. To tackle this problem, most previous approaches focus on learning developers’ capabilities and experiences and recommending suitable developers based on their historical interactions. However, such approaches usually suffer from data-sparsity and noise problems, which may reduce the recommendation accuracy. In this paper, we propose an attentive neighbor embedding propagation enhanced code reviewer recommendation framework (termed ANEP). In ANEP, we first construct the reviewer–code interaction graph and learn the semantic representations of the reviewer and code based on the transformer model. Then, we explicitly explore the attentive high-order embedding propagation of reviewers and code and refine the representations along their neighbors. Finally, to evaluate the effectiveness of ANEP, we conduct extensive experiments on four real-world datasets. The experimental results show that ANEP outperforms other state-of-the-art approaches significantly