Modelling Corona Discharge Characteristic in Electricity Transmission Lines for Fault Detection System

Author(s):  
Vaidotas Marusauskas ◽  
Saulius Gudzius ◽  
Audrius Jonaitis ◽  
Jonas Vaicys ◽  
Tomas Merfeldas ◽  
...  
2020 ◽  
Vol 1486 ◽  
pp. 062024
Author(s):  
Xiaoming Xiao ◽  
Weinan Hu ◽  
Jun Ran ◽  
Zheng Xu ◽  
Guoyu Hei ◽  
...  

2011 ◽  
Vol 105-107 ◽  
pp. 2188-2193
Author(s):  
Xiao Han ◽  
Xi Chen ◽  
Peng Fei Li

Corona discharge is a kind of self maintained discharges that occurs in the extremely uneven electric field which often happens in the industrial and daily living environments. In this paper, we study the characteristics of corona discharge, especially the ones in the time domain and frequency domain of negative corona discharge. Based on the analyzed characteristics mentioned above, we design and optimize a kind of patch antennas, which has the advantages of small volume compared to the traditional one used to receive the signals generated by corona discharge. This new antenna can be used in the field of security inspection on high voltage transmission lines applied in the industrial applications.


2016 ◽  
Vol 12 (02) ◽  
pp. 5
Author(s):  
Fenhua Sheng ◽  
Zujue Chen

The paper mainly aimed at solving the problem of yarn color fault detection. Yarn with different color is hard to detect in yarn production, a special photoelectric sensor is designed in this paper. First, this paper analyzed the requirement of light source and photoelectric receiver in the photoelectric sensor, and designs the light path and driver circuit. Then this paper analyzed the amplifier circuit and noise in the photoelectric sensor, with an amplifier circuit of minimal noise proposed at last. Finally, this paper tested the yarn color fault detection system with virtual instrument, and the test results showed a great application prospect of the photoelectric sensor. Photoelectric yarn clearer was the first type of electronic yarn clearer, but due to the under development of the optical technology and measurement technology, the photoelectric yarn cleaner can't meet the requirements of textile production, gradually replaced by capacitive yarn cleaner. Though photoelectric yarn cleaner had a good visual conformity degree, it’s still a unreplaceable method in colored yarn faults


2013 ◽  
Vol 05 (04) ◽  
pp. 1298-1302 ◽  
Author(s):  
Lan Chen ◽  
Lin Lin ◽  
Mimi Tian ◽  
Xingming Bian ◽  
Liming Wang ◽  
...  

Author(s):  
Nwoke G. O.

Abstract: Transmission line fault detection is an important aspect of monitoring the health of a power plant since it indicates when suspected faults could lead to catastrophic equipment failure. This research looks at how to detect generator and transmission line failures early and investigates fault detection methods using Artificial Neural Network approaches. Monitoring generator voltages and currents, as well as transmission line performance metrics, is a key monitoring criterion in big power systems. Failures result in system downtime, equipment damage, and a high danger to the power system's integrity, as well as a negative impact on the network's operability and dependability. As a result, from a simulation standpoint, this study looks at fault detection on the Trans Amadi Industrial Layout lines. In the proposed approach, one end's three phase currents and voltages are used as inputs. For the examination of each of the three stages involved in the process, a feed forward neural network with a back propagation algorithm has been used for defect detection and classification. To validate the neural network selection, a detailed analysis with varied numbers of hidden layers was carried out. Between transmission lines and power customers, electrical breakdowns have always been a source of contention. This dissertation discusses the use of Artificial Neural Networks to detect defects in transmission lines. The ANN is used to model and anticipate the occurrence of transmission line faults, as well as classify them based on their transient characteristics. The results revealed that, with proper issue setup and training, the ANN can properly discover and classify defects. The method's adaptability is tested by simulating various defects with various parameters. The proposed method can be applied to the power system's transmission and distribution networks. The MATLAB environment is used for numerous simulations and signal analysis. The study's main contribution is the use of artificial neural networks to detect transmission line faults. Keywords: Faults and Revenue Losses


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