Spatial and Temporal Characteristics of Insulator Contaminations Revealed by Daily Observations of Equivalent Salt Deposit Density
1
State Grid Key Laboratory of High-Voltage Field-Test Technique, Electric Power Research Institute of Hubei Power Grid Corporation, Wuhan 430077, China
2
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road 129, Wuhan 430079, China
3
College of Information Science and Engineering, Huazhong University of Science and Technology Wuchang Branch, Wuhan 430064, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Sensors 2015, 15(2), 3023-3040; https://doi.org/10.3390/s150203023
Received: 28 November 2014 / Revised: 5 January 2015 / Accepted: 23 January 2015 / Published: 29 January 2015
(This article belongs to the Special Issue Optical Sensors for Chemical, Biological and Industrial Applications)
Abstract
The accurate estimation of deposits adhering on insulators is of great significance to prevent pollution flashovers which cause huge costs worldwide. Researchers have developed sensors using different technologies to monitor insulator contamination on a fine time scale. However, there is lack of analysis of these data to reveal spatial and temporal characteristics of insulator contamination, and as a result the scheduling of periodical maintenance of power facilities is highly dependent on personal experience. Owing to the deployment of novel sensors, daily Equivalent Salt Deposit Density (ESDD) observations of over two years were collected and analyzed for the first time. Results from 16 sites distributed in four regions of Hubei demonstrated that spatial heterogeneity can be seen at both the fine and coarse geographical scales, suggesting that current polluted area maps are necessary but are not sufficient conditions to guide the maintenance of power facilities. Both the local emission and the regional air pollution condition exert evident influences on deposit accumulation. A relationship between ESDD and PM10 was revealed by using regression analysis, proving that air pollution exerts influence on pollution accumulations on insulators. Moreover, the seasonality of ESDD was discovered for the first time by means of time series analysis, which could help engineers select appropriate times to clean the contamination. Besides, the trend component shows that the ESDD increases in a negative exponential fashion with the accumulation date (ESDD = a − b × exp(−time)) at a long time scale in real environments. View Full-Text
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Ruan, L.; Han, G.; Zhu, Z.; Zhang, M.; Gong, W. Spatial and Temporal Characteristics of Insulator Contaminations Revealed by Daily Observations of Equivalent Salt Deposit Density. Sensors 2015, 15, 3023-3040.