A new methodology of fault location for predictive maintenance of transmission lines

Silva, Paula Renatha N. da; Negrão, Martin Max L.C.; Vieira, P.; Sanz-Bobi, Miguel Á.

doi:10.1016/j.ijepes.2012.04.057

Cited by 14 publications

(4 citation statements)

References 23 publications

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“…Both ANNs have been widely used, the last years, in the solution of many power system problems presenting very accurate results. MLP and RBF ANNs have been used for the fault location and predictive maintenance of transmission lines [9,10], for the estimation of transmission lines' distance protection [11], for lightning outage calculations and grounding resistance issues [12], for voltage stability monitoring [13], for the estimation of electric fields and the critical flashover voltage along high-voltage insulators [12,14], and for power transformer problems such as insulation aging and fault diagnosis [15,16].…”

Section: Artificial Neural Network' (Anns) Implementationmentioning

confidence: 99%

An artificial neural network software tool for the assessment of the electric field around metal oxide surge arresters

Ekonomou

Mladenov

2015

Neural Comput & Applic

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The paper presents an artificial neural network (ANN) software tool that has been developed in order to assess the electric field around medium-voltage surge arresters. The knowledge of the electric field around gapless metal oxide surge arresters is very useful for diagnostic tests and design procedures. For the training, validating, and testing of the ANNs, real data have been used collected from hundreds of measurements. The developed ANN software can be used by electric utilities in order to diagnose the condition of the surge arresters without stopping their operation and by laboratories and manufacturing/retail companies dealing with medium-voltage surge arresters and either face a lack of suitable measuring equipment or want to compare/verify their own measurements.

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Section: Artificial Neural Network' (Anns) Implementationmentioning

confidence: 99%

An artificial neural network software tool for the assessment of the electric field around metal oxide surge arresters

Ekonomou

Mladenov

2015

Neural Comput & Applic

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“…Today, many countries have to urgently address the issue of the timely detection and elimination of defects in transmission lines [14][15][16][17]. What makes it highly relevant to design appropriate 'preemptive' solutions is their strong economic effect that shows in lower expenditures on the elimination of failures, compensation of power losses and operating costs [13,[17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Asset management in grid companies using integrated diagnostic devices

Gitelman¹,

Kozhevnikov²,

Kaplin³

2019

Int. J. EQ

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The digitization of power grids envisages a transition to new models of fault diagnosis, repair and maintenance of electric power grid equipment. The most promising tools for implementing advanced production asset management strategies are integrated technologies that are based on robotic diagnostic platforms, various hardware-software instruments and smart data analysis systems. The article analyzes other countries' experience of developing robotic methods of fault diagnosis and maintenance of overhead power transmission lines, which present a major challenge in terms of monitoring, failure prediction and localized repairs. The Cablewalker robotic system was used as an example for identifying the advantages of integrated diagnostic hardware systems as opposed to traditional methods of power grid equipment maintenance and overhaul. Recommendations are given for adopting the technology in grid companies. During trials of the technology on a 2.34-km section of a power transmission line 112 defects were detected versus three that were identified by means of 'manual' inspection. A digital twin of the transmission line was created to manage its technical condition with regard to various risks.

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“…Second is preventive maintenance, where maintenance is performed at regular intervals in order to avoid machine breakdowns (Joo & Min, 2013;Moghaddam & Usher, 2011;Yeh, Kao & Chang, 2009;You, Li & Meng, 2011;Zhao, 2003). Third is predictive maintenance, where the health of the system is continuously monitored using sophisticated equipments and maintenance is performed only when required by the state of the system/machine (Chu, Proth & Wolff, 1998;Costa, Carnero & Oliveira, 2012;Dieulle, Berenguer, Grall & Roussignol, 2001;Hsiao, Drury, Wu & Paquet, 2013;Moya, 2004;Neves, Santiago & Maia, 2011;Silva, Negrao, Junior & Bobi, 2012). In corrective maintenance, the machine/machines is in a highly degraded state, prolonging the maintenance time, while preventive maintenance entails a higher frequency of maintenance, resulting in more than required maintenance, thereby increasing machine down time.…”

Section: Introductionmentioning

confidence: 99%

Development of Predictive Maintenance Model for N-Component Repairable System Using NHPP Models and System Availability Concept

Srivastava

2016

Global Business Review

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The technologically intensive nature of the predictive maintenance (PdM) method restricts its use to companies with higher turnover. This research is aimed to propose a PdM model for an N-component repairable system by integrating non-homogeneous Poisson process (NHPP) models and a system availability concept such that the use of technology is minimized, thereby extending its applicability to companies with lower turnover. It is known that manufacturing systems show reliability degradation with repeated overhauls and component replacements. This has the effect that the mean time between failures (MTBF) is non-identically distributed. Hence, the failure pattern of each component is analyzed using NHPP models and the mean system availability is calculated, which is now compared with the threshold system availability deciding the overall maintenance of the system. Further, the developed model is validated on a wheat flour mill.

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A new methodology of fault location for predictive maintenance of transmission lines

Cited by 14 publications

References 23 publications

An artificial neural network software tool for the assessment of the electric field around metal oxide surge arresters

An artificial neural network software tool for the assessment of the electric field around metal oxide surge arresters

Asset management in grid companies using integrated diagnostic devices

Development of Predictive Maintenance Model for N-Component Repairable System Using NHPP Models and System Availability Concept

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