The State Monitoring Method of Electronic Voltage Transformer Based on L-M Algorithm

Author(s):  
Han Lian ◽  

In the traditional method of monitoring the state of electronic voltage transformer, there are problems of large monitoring error and weak robustness. Therefore, a new state monitoring method of electronic voltage transformer based on L-M algorithm is proposed. The relationship between input voltage and output voltage of capacitor voltage divider in electronic voltage transformer is obtained by using Laplasse transform. The transfer function model of electronic voltage transformer is constructed based on the relationship result and L-M algorithm. The transfer function model is used to analyze the frequency characteristics of the electronic voltage transformer and the range of normal measurement frequency, and then the partial pressure ratio of the electronic voltage transformer under the high frequency condition is derived. On this basis, by calculating the over voltage amplitude on the two sides of acquisition card in the electronic voltage transformer, the capacitance value between the two adjacent coaxial cylindrical cylinders of the capacitance divider in the electronic voltage transformer is obtained, thus the monitoring of the state of the electronic voltage transformer is completed. The experimental results show that the proposed method has low detection error and strong robustness, and can effectively improve the reliability of electronic voltage transformer.

2021 ◽  
Vol 35 (4) ◽  
pp. 91-96
Author(s):  
Inseon Park ◽  
Muheon Jeong

The market size of the firefighting supplies industry is can be considered a derivative demand of the construction industry, and its patterns differ seasonally. In this study, the seasonal ARIMA model and the transfer function model were established, and their predictive performances were verified. It was statistically confirmed that the firefighting supplies market has a lagging character in the construction industry. Although the seasonal ARIMA model, a representative time-series model, is a suitable predictive model, the transfer function model linked to the construction market is more useful in the short-term forecast period. This study is the first statistical prediction study of the firefighting supplies market in Korea. Based on the structural characteristics of the firefighting supplies industry, the relationship between the building permit and firefighting supplies production should be established using the transfer function model, the transfer function model is more useful in the decision-making process of firefighting supplies policies and the manufacturer’s marketing.


2019 ◽  
Vol 7 (3) ◽  
Author(s):  
Nur Laela Fitriani ◽  
Pika Silvianti ◽  
Rahma Anisa

Transfer function model with multiple input is a multivariate time series forecasting model that combines several characteristics of ARIMA models by utilizing some regression analysis properties. This model is used to determine the effect of output series towards input series so that the model can be used to analyze the factors that affect the Jakarta Islamic Index (JII). The USD exchange rate against rupiah and Dow Jones Index (DJI) were used as input series. The transfer function model was constructed through several stages: model identification stage, estimation of transfer function model, and model diagnostic test. Based on the transfer function model, the JII was influenced by JII at the period of one and two days before. JII was also affected by the USD exchange rate against rupiah at the same period and at one and two days before. In addition, the JII was influenced by DJI at the same period and also at period of one until five days ago. The Mean Absolute Prencentage Error (MAPE) value of forecasting result was 0.70% and the correlation between actual and forecast data was 0.77. This shows that the model was well performed for forecasting JII.


Economies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 21
Author(s):  
Jazmín González Aguirre ◽  
Alberto Del Villar

This paper seeks to assess the effectiveness of customs policies in increasing the resources devoted to controlling and inspection. Specifically, it seeks to analyze whether an increase in the administrative cost of collecting taxes on foreign trade in Ecuador contributes to reducing customs fraud. To this end, we identify and estimate a transfer function model (ARIMAX), considering information on foreign trade such as official international trade statistics report and tariff rates, as well as the execution of budgetary expenditure and Ecuador’s gross domestic product (GDP). The period under study includes quarterly series from 2006 to 2018. The results obtained by the model indicate that allocating greater material and budgetary resources to combat customs fraud does not always achieve the objective of reducing customs evasion.


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