A new nonlinear correction method of current transformer is proposed for the second current signals distortion which caused by the iron core saturation of current transformer (CT). In this method, the saturation interval is determined by the sudden change characteristic of the secondary current saturation waveform, the secondary current value of the saturation transition interval is estimated by the least squares method, and the relationship between the hysteresis current, the secondary current and the magnetic flux under the saturation of the current transformer is used to establish the positive definite linear system of the magnetic flux estimation, the secondary current value after compensation can be obtained by inverse transformation. This paper analyzes the new method of current transformer nonlinear compensation theoretically and experimentally, the experimental results verified the effectiveness of this method, the method can improve the measurement accuracy of the current transformer from the original degree 0.5 to degree 0.1.
This study proposed a remote sensing-based approach to quantify the spatio-temporal patterns of vegetation dynamics and associated impact factors in typical karst regions of Southwest China. Google Earth engine (GEE), the world's most advanced geospatial data cloud computing platform, was employed to construct long time series satellite data set with 30 m resolution, composed of nearly 4,000 Landsat scenes from 1988 to 2016. Image preprocessing was also conducted on the GEE platform. The maximum value composite (MVC) method was used to produce annual maximum normalized difference vegetation index (NDVI) of the study areas. Annual maximum fractional vegetation cover (annFVC) was thus quantitatively estimated based on Dimidiate Pixel Model (DPM). Ordinary least squares (OLS) regression was adopted to identify the spatial patterns of the direction and rate of change in annFVC at a pixel scale. In addition, a terrain niche index (TNI) was used to investigate the influence of topographic factors on vegetation trends. Moreover, the relationships between annFVC and climatic factors were identified using correlation analysis. The results show that annFVC significantly increased at a rate of 0.0032/year in Nandong and 0.0041/year in Xiaojiang watershed for the period 1988-2016. Furthermore, 26.97% and 27.16% of pixels were found to undergo significant increase in terms of annFVC in Nandong and Xiaojiang, respectively. For both Nandong and Xiaojiang, decreasing vegetation trend was curbed with the increase of elevation and slope. Additionally, correlation analysis demonstrated that annFVC was more strongly and positively correlated with temperature than with precipitation in spite of insignificance.
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