scholarly journals Fault Detection of Actuator with Digital Positioner Based on Trend Analysis Method

10.5772/9084 ◽  
2010 ◽  
Author(s):  
Xiaobin Huang ◽  
Jizhen Liu ◽  
Yuguang Niu
Keyword(s):  
Fault Detection ◽  
Trend Analysis ◽  
Analysis Method

scholarly journals Trend Analysis of Parent Education in Korea - Using Network Analysis Method -

2017 ◽  
Vol 23 (3) ◽  
pp. 75-94 ◽  
Author(s):  
YoungHwan Kim ◽  
Kang, Doobong ◽  
이승민
Keyword(s):  
Network Analysis ◽  
Trend Analysis ◽  
Parent Education ◽  
Analysis Method

scholarly journals A spatial and temporal analysis on NDVI in Urad grassland during 2010-2019 over remote sensing

2021 ◽  
Vol 336 ◽  
pp. 06029
Author(s):  
Yueying Zhang ◽  
Tiantian Liu ◽  
Yuxi Wang ◽  
Ming Zhang ◽  
Yu Zheng
Keyword(s):  
Remote Sensing ◽  
Trend Analysis ◽  
Temporal Analysis ◽  
Vegetation Coverage ◽  
Analysis Method ◽  
Modis Ndvi ◽  
The Past ◽  
Spatial And Temporal Analysis ◽  
Change Trend ◽  
Temporal And Spatial

The temporal-spatial dynamic variation of vegetation coverage from 2010 to 2019 in Urad Grassland, Inner Mongolia has been investigated by analysing on MODIS NDVI remote sensing products. This paper applies pixel dichotomy approach and linear regression trend analysis method to analyze the temporal and spatial evolution trend of vegetation coverage over the past 10 years. The average annual vegetation coverage showed a downward trend in general from 2010 to 2019. The vegetation distribution and change trend analysis provide a thorough and scientific reference for policymaking in environmental protection.

scholarly journals Long-Term Trends and Seasonality Detection of the Observed Flow in Yangtze River Using Mann-Kendall and Sen’s Innovative Trend Method

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1855 ◽  
Author(s):  
Ali ◽  
Kuriqi ◽  
Abubaker ◽  
Kisi
Keyword(s):  
Trend Analysis ◽  
Yangtze River ◽  
Winter Season ◽  
Trend Test ◽  
Analysis Method ◽  
Adaptation Measures ◽  
Minimum Flow ◽  
Mk Test ◽  
Innovative Trend Analysis ◽  
Increasing Trend

Trend analysis of streamflow provides practical information for better management of water resources on the eve of climate change. Thus, the objective of this study is to evaluate the presence of possible trends in the annual, seasonal, maximum, and minimum flow of Yangtze River at Cuntan and Zhutuo stations in China for the period 1980 to 2015. The assessment was carried out using the Mann–Kendall trend test, and the innovative trend analysis, while Sen’s slope is used to estimate the magnitude of the changes. The results of the study revealed that there were increasing and decreasing trends at Cuntan and Zhutuo stations in different months. The mean annual flow was found to decrease at a rate of −26.76 m3/s and −17.37 m3/s at both stations. The minimum flow was found to significantly increase at a rate of 30.57 m3/s and 16.37 m3/s, at a 95% level of confidence. Maximum annual flows showed an increasing trend in both regions of the Yangtze River. On the seasonal scale, the results showed that stations are more sensitive to seasonal flow variability suggesting a probable flooding aggravation. The winter season showed an increasing flow trend, while summer showed a decreasing trend. The spring flow was found to have an increasing trend by the Mann–Kendall test at both stations, but in the Zhutuo Station, a decreasing trend was found by way of the innovative trend analysis method. However, the autumn flow indicated a decreasing trend over the region by the Mann–Kendall (MK) test at both stations while it had an increasing trend in Cuntan by the innovative trend analysis method. The result showed nonstationary increasing and decreasing flow trends over the region. Innovative trend analysis method has the advantage of detecting the sub-trends in the flow time series because of its ability to present the results in graphical format. The results of the study indicate that decreasing trends may create water scarcity if proper adaptation measures are not taken.

The Application of Improved HHT to Harmonic Analysis and Fault Detection of Power System

2011 ◽  
Vol 354-355 ◽  
pp. 1406-1411
Author(s):  
Wen Hua Han ◽  
Hai Xia Ren ◽  
Xu Chen ◽  
Xiao Juan Tao
Keyword(s):  
Fault Detection ◽  
Power System ◽  
Harmonic Analysis ◽  
Harmonic Signal ◽  
Ensemble Empirical Mode Decomposition ◽  
Frequency Domain Analysis ◽  
Analysis Method ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Mode Decomposition

Hilbert-Huang transform (HHT) is a new time-frequency-domain analysis method, which is suitable for non-stationary and nonlinear signals. In this paper, endpoint continuation and ensemble empirical mode decomposition (EEMD) decomposition method are introduced to improve the HHT, which solve the endpoint winger and modal aliasing problem. The improved HHT (IHHT) is used for analyzing the harmonic signal and detecting the fault signal of power system. Simulation results show that IHHT is feasible and effective for harmonic analysis and fault detection.

Sign in / Sign up

Export Citation Format

Share Document