Search

As the mining depth of North China-type coal fields increases year by year, the threat of Ordovician limestone karst water damage to coal seam mining is increasing, and the risk of floor water inrush increases gradually. To ensure safe production in coal mines and avoid casualties and economic losses, it is essential to accurately predict the risk of coal floor water inrush. The traditional approach to determine whether there is risk during the mining process is the water inrush coefficient method, which has certain limitations because it does not fully consider the water yield of the aquifer and the actual hydraulic resistance of the aquitard. Therefore, in this paper, a new method was put forward and applied for predicting the floor water inrush risk attributed to the Ordovician karst fissure confined aquifer from the Permian-age coal deposits in the Xiayukou coal field, Hancheng mining area, Shanxi, China. The influence of floor water inrush is comprehensively considered from the three aspects of the aquifer’s water yield, the hydraulic resistance characteristics of the aquitard and the tectonic development of the study area. Based on the new analytic hierarchy process-linear weighted average (AHP-LWA) method, a water abundance structure index (WASI) was created using the burial depth of the Ordovician aquifer (Dp), water abundance layer (Ly) and morphological features of the aquifer (Mf). Similarly, a hydraulic resistance structure index (HRSI) model was established using aquitard thickness (Tk), number of aquifers and aquitards (Num), sand–mud ratio (SMr) and core recovery rate (CRr); additionally, fractal dimension values were used to characterize the degree of structural development. Finally, a water inrush risk evaluation model was constructed, and a contour map was drawn using the risk index method of floor water inrush (RIWI) values and revealed three water inrush risk zones: normal mining area (0.18–0.32), medium-risk area (0.32–0.38) and high-risk area (0.38–0.52). Model verification was accomplished by the actual exposed water inrush points during the No. 3 coal seam mining work, which are all located in the high-risk area zoned by the RIWI method, and the water sources are all from the third section of the Upper Majiagou strong aquifer. The results show that the new evaluation model has high prediction accuracy, small error and wide applicability, and the model meets the basic requirements of mine production safety, provides favourable technical support for floor water inrush prediction during the Carboniferous–Permian lower coal group mining above the confined aquifer and is of great significance to ensure safe and efficient production of the coal mine.

The aim of this paper is to diagnose the bushing faults by making use of the infrared images. Before diagnosing the bushing faults, the preprocessing and segmentation should be processed. The preprocessing, which includes adaptive median filtering, K-means, opening operation, is applied to filter the noise and remove the background. To segment the bushing from the image, simple linear iterative clustering (SLIC) is applied which allows the bushing segmented according to the shape of it and makes it works better. After analyzing the thermal characteristics of the fault image of bushings from the DL/T-664-2016 Application rules of infrared diagnosis for live electrical equipment, it can be concluded that diagnose the fault area’s relative position can be a great way to diagnose the bushing, so it’s regarded as a principle to classify the faults. In this paper, we selected some typical infrared bushing images with faults. After the processing, the results have been verified that the method is able to segment the bushing and diagnose the fault preliminarily.

Oil-immersed inverted current transformer, as an important electrical equipment in power grid, is mainly used in power plants and substations. Accidents caused by oil-immersed inverted current transformers are generally accompanied by explosions, which not only reduce the amount of electricity delivered, but also damage other nearby equipment in the substation and even cause casualties. Therefore, it is very necessary to detect and evaluate the operation status of oil-immersed inverted current transformer and study the fault prevention technology to reduce the probability of accidents. According to the common faults of oil-immersed inverted current transformer, this paper firstly analyzed the parts and components with high fault rate of current transformer. Combined with the operating condition of current transformer and its internal insulation structure, the internal temperature field simulation model of current transformer and the temperature calculation model of key parts were established. It was found that the temperature near the winding of the oil-immersed inverted current transformer was the highest, while the temperature rise at the lower part far from the heat source was very small. The simulation results were basically consistent with the experimental results, and it was found that the temperature distribution on both sides of the primary conductor in the head region of the current transformer was symmetrical.