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Abstract The trip mechanism is a weakness in circuit breakers. Traditional fault identification based on the coil current is difficult to report early mechanical defects such as coil‐plunger jam. Here, the vibration signal during the trip process was extracted. Based on the coil current signal and vibration signal, the characteristics of the trip mechanism are analyzed. The phase space reconstruction (PSR) method is used to extract features from the vibration signal. Combined with the features from the coil current waveform, the feature set representing the health condition of the trip mechanism is proposed. The fault simulation tests are carried out and the variation of current vibration characteristics under fault conditions is studied. The fault identification model based on a support vector machine (SVM) is proposed and compared with the identification results when features are extracted from a single signal. When the power supply voltage is dispersed, the prediction accuracy of fault identification is 83.3% considering only the features of the current waveform or vibration signal. And the identification accuracy rises to 96.7% while using the feature set of current and vibration signals. On basis of the current signal, the method further combines the vibration signal so that the robustness of defect identification improves.

Background: Our aim was to determine the potential pharmacological mechanisms of the Guizhi decoction (GZD) in the treatment of osteoarthritis (OA) through an integrated approach of network pharmacological analyses, RNA sequencing (RNA-seq), and experimental validation.Methods: The quality control and identification of bioactive compounds of the GZD were carried out by using ultra-performance liquid chromatography (UPLC), and their OA-related genes were identified through overlapping traditional Chinese medicine systems pharmacology database (TCMSP), DrugBank and SEA Search Server databases, and GeneCards. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were implemented after constructing the component–target network. RNA-seq was used to screen differentially expressed genes (DEGs) under intervention conditions with and without the GZD in vitro. The crossover signaling pathways between RNA-seq and network pharmacology were then analyzed. Accordingly, protein–protein interaction (PPI) networks, GO, and KEGG analysis were performed using the Cytoscape, STRING, or DAVID database. The OA rat model was established to further verify the pharmacological effects in vivo. Hematoxylin–eosin (H&E) and safranin O/fast green (S-O) staining were used to grade the histopathological features of the cartilage. We verified the mRNA and protein expressions of the key targets related to the TNF signaling pathways in vivo and in vitro by qPCR, Western blotting (WB), and immunofluorescence assay. In addition, we also detected inflammatory cytokines in the rat serum by Luminex liquid suspension chip, which included tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β).Results: Eighteen compounds and 373 targets of the GZD were identified. A total of 2,356 OA-related genes were obtained from the GeneCards database. A total of three hub active ingredients of quercetin, kaempferol, and beta-sitosterol were determined, while 166 target genes associated with OA were finally overlapped. The RNA-seq analysis revealed 1,426 DEGs. In the KEGG intersection between network pharmacology and RNA-seq analysis, the closest screening relevant to GZD treatment was the TNF signaling pathway, of which TNF, IL-6, and IL-1β were classified as hub genes. In consistent, H&E and S-O staining of the rat model showed that GZD could attenuate cartilage degradation. When compared with the OA group in vivo and in vitro, the mRNA levels of TNF-α, IL-1β, IL-6, matrix metalloproteinase 3 (MMP3), and matrix metalloproteinase 9 (MMP9) were all downregulated in the GZD group (all p < 0.05). The expression levels of anabolic proteins (Col2α1 and SOX9) were all higher in the GZD group than in the OA group (p < 0.05), while the expression levels of the catabolic proteins (MMP9 and COX-2) and TNF-α in the GZD group were significantly lower than those in the OA group (p < 0.05). In addition, the expression levels of TNF, IL-6, and IL-1β were upregulated in the OA group, while the GZD group prevented such aberrations (p < 0.01).Conclusion: The present study reveals that the mechanism of the GZD against OA may be related to the regulation of the TNF signaling pathway and inhibition of inflammatory response.

Air insulation strength relates closely to the electrostatic field distribution of the gap configuration. To achieve insulation prediction on the basis of electric field (EF) simulations, the spatial structure is characterized by a feature set including 38 parameters defined on a straight line between sphere electrodes. A support vector classifier (SVC) with particle swarm optimization (PSO) is used to establish a prediction model, whose input variables are those features. The EF nonuniform coefficient f of each sample gap is calculated and used for training sample selection according to the ranges off values. Trained by only 11-sample data, the PSO-optimized SVC model is employed to predict the power frequency breakdown voltages of 260-sphere gaps with a wide range of structure sizes. The predicted values coincide with the standard data given in IEC 60052 very well, with the same trend and minor relative errors. The MAPEs of the five predictions with different training sets are within 2.0%. The model is also effective to predict the breakdown voltages of Φ9.75-cm sphere-Φ6.5-cm sphere gaps, whose MAPEs are within 2.6%. The results demonstrate the effectiveness of the EF feature set and the generalization ability of the SVC model under the case of limited samples. This paper lays the foundation for estimating the dielectric strength of other air gaps with similar structures.

The hybrid high-voltage direct current (HVDC) breaker combines mechanical and power electronics switching that enables it to interrupt power flows within a few milliseconds. Mechanical switch is a key component of hybrid HVDC breaker and has a number of serially connected interrupter units which ideally would divide the voltage equally. The static voltage distribution characteristics and voltage sharing design of a multi-break mechanical switch were discussed in this study. A finite-element model was developed to study the static voltage distribution characteristics and capacitance parameters of multi-break mechanical switch (which actually consists of resistance and capacitance parameters under direct current) as a preliminary study. Comparisons were made under the simulation of vertical and U-shaped arrangement forms. The results indicate that the static voltage distribution of the high-voltage terminal is at least more than 65%, whereas the severe non-uniform voltage distribution can be well improved by means of the method proposed in this study.

The transmission corridors can be effectively saved using 750 kV four-circuit transmission line on the same tower. In order to reduce the corona level, structure optimisation of fittings plays an important role in the transmission line design. In this study, the electric field distribution of 750 kV transmission line on six cross-arms tower was calculated based on finite element method, and the influences of pipe diameter, ring diameter and installation position of the grading ring were analysed. The results show that the increase of pipe diameter can reduce the electric field strength of grading ring while the increase of installation position and decrease of ring diameter are important to protect the end fitting of composite insulator. When using grading ring with the pipe diameter of 100 mm, the ring diameter of 700–900 mm and the installation position of 150–250 mm, the electric field strength can be controlled in a reasonable range. These results can provide references for the grading ring design of 750 kV four-circuit transmission line on the same tower.

Full-scale discharge tests of transmission line–tower air gaps are costly and time-consuming, and they cannot exhaustively simulate all the gap configurations in practical engineering. In this paper, a machine learning model established by support vector machine is introduced to predict the switching impulse discharge voltages of the ultra-high-voltage (UHV) AC transmission line–tower air gaps. The three-dimensional finite element models of a UHV cup-type tower and a UHV compact transmission line were established for electric field calculation, and some features were extracted from the hypothetic discharge channel and the shortest path between the bundled conductor and the tower. These features under a given voltage were normalised and input to the SVM model, while the output is two binary values, respectively, representing gap withstanding or breakdown. Trained by experimental data of one type of the UHV transmission line–tower gaps, the SVM model is able to predict the discharge voltages of another gap type. The mean absolute percentage errors of the two engineering gap types, under different gap distances, are 8.31 and 4.86%, respectively, which are acceptable for engineering applications. The results provide a possible way to obtain the discharge voltages of complicated engineering gaps by mathematical calculations.

Background/Aims: Bone marrow-derived mesenchymal stem cells (MSCs) are responsible for new bone formation during adulthood. Accumulating evidences showed that Osthole promotes the osteogenic differentiation in primary osteoblasts. The aim of this study was to investigate whether Osthole exhibits a potential to stimulate the osteogenic differentiation of MSCs and the underlying mechanism. Methods: MSCs were treated with a gradient concentration of Osthole (6.25 µM, 12.5 µM, and 25 µM). Cell proliferation was assessed by western blotting with the proliferating cell nuclear antigen (PCNA) and Cyclin D1 antibodies, fluorescence activated cell sorting (FACS), and cell counting kit 8 (CCK8). MSCs were cultured in osteogenesis-induced medium for one or two weeks. The osteogenic differentiation of MSCs was estimated by Alkaline Phosphatase (ALP) staining, Alizarin red staining, Calcium influx, and quantitative PCR (qPCR). The underlying mechanism of Osthole-induced osteogenesis was further evaluated by western blotting with antibodies in Wnt/β-catenin, PI3K/Akt, BMPs/smad1/5/8, and MAPK signaling pathways. Results: Osthole inhibited proliferation of rat MSCs in a dose-dependent manner. Osthole suppressed osteogenic differentiation of rat MSCs by down-regulating the activities of Wnt/β-catenin and Erk1/2-MAPK signaling. Conclusions: Osthole inhibits the proliferation and osteogenic differentiation of rat MSCs, which might be mediated through blocking the Wnt/β-catenin and Erk1/2-MAPK signaling pathways.

Background/Aims: Cartilage destruction is thought to be the major mediator of osteoarthritis. Recent studies suggest that inhibition of subchrondral bone loss by anti-osteoporosis (OP) drug can protect cartilige erosion. Osthole, as a promising agent for treating osteoporosis, may show potential in treating osteoarthritis. The purpose of this study was to investigate whether Osthole affects the proliferation and catabolism of rat chondrocytes, and the degeneration of cartilage explants. Methods: Rat chondrocytes were treated with Osthole (0 μM, 6.25 μM, 12.5 μM, and 25 μM) with or without IL1-β (10ng/ml) for 24 hours. The expression levels of type II collagen and MMP13 were detected by western Blot. Marker genes for chondrocytes (A-can and Sox9), matrix metalloproteinases (MMPs), aggrecanases (ADAMTS5) and genes implicated in extracellular matrix catabolism were evaluated by qPCR. Cell proliferation was assessed by measuring proliferating cell nuclear antigen (PCNA) expression and fluorescence activated cell sorter. Wnt7b/β-catenin signaling was also investigated. Cartilage explants from two-week old SD rats were cultured with IL-1β, Osthole and Osthole plus IL-1β for four days and glycosaminoglycan (GAG) synthesis was assessed with toluidine blue staining and Safranine O/Fast Green FCF staining, collagen type II expression was detected by immunofuorescence. Results: Osthole reduced expression of chondrocyte markers and increased expression of MMP13, ADAMTS5 and MMP9 in a dose-dependent manner. Catabolic gene expression levels were further improved by Osthole plus IL-1β. Osthole inhibited chondrocyte proliferation. GAG synthesis and type II collagen were decreased in both the IL-1β groups and the Osthole groups, and significantly reduced by Osthole plus IL-1β. Conclusions: Our data suggested that Osthole increases the catabolism of rat chondrocytes and cartilage explants, this effect might be mediated through inhibiting Wnt7b/β-catenin pathway.