A review on fault classification methodologies in power transmission systems: Part-II

Prasad, Avagaddi; Edward, J. Belwin; Ravi, K.

doi:10.1016/j.jesit.2016.10.003

Cited by 47 publications

(21 citation statements)

References 5 publications

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“…Markovič et al [41] used data classification algorithm to mine energy consumption model from user load profiles. Prasad et al [42] reviewed fault classification methodologies in power transmission systems by using data classification methods.…”

Section: Related Workmentioning

confidence: 99%

“…Existing data classification approaches mainly solves the imbalance [33, 34] and efficiency problems [36, 38, 39] in the data classification process, and also applies the data classification to specific application scenarios, such as solving privacy protection [37] and fault detection for power transmission line [42]. However, the existing literatures do not identify data content based on data classification algorithms to achieve data protection.…”

Section: Related Workmentioning

confidence: 99%

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Data filter function incremental mining based on feature selection in an active distribution network

Deng

Cai

Zhang

et al. 2020

IET cyber-phys. syst.

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Compared with traditional distributed networks, the complex access environment, flexible access mode, massive access terminal, and data in an active distribution network will bring great security challenges to data transmission. The existing data security methods, such as access control and encryption, address the security of massive, high dimensional, and non-text data in the active distribution network. Therefore, feature selection algorithm based on rough set is first given to reduce the complexity of massive and high dimensional data. And then, based on feature selection, the authors propose a data filtering function model mining algorithm by using gene expression programming (DFFM-FSGEP). Finally, to solve the data filter function model mining of the incremental dataset, they also present an incremental mining algorithm of the filtering function model based on functional fitting (IMFFM-FF). Experimental results show that the proposed algorithm in this study can greatly reduce the complexity of experimental datasets to be processed, and compared with the other algorithms, DFFM-FSGEP has higher classification accuracy and sensitivity, and IMFFM-FF has higher classification speed and classification accuracy for incremental datasets.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Data filter function incremental mining based on feature selection in an active distribution network

Deng

Cai

Zhang

et al. 2020

IET cyber-phys. syst.

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“…On the one hand, there are different reviews about DM applications, e.g., diagnosis in health [9][10][11], marketing [12], industrial [13,14], climatological [15], and financial [16] issues, among others. On the other hand, there are also reviews related to diagnosis methods for specific machines such as transformers [17][18][19], estimation strategies in electric vehicles [20], mathematical models used to study induction motors in defective conditions [21], or, in a more general sense, methodologies of fault classification in transmission systems [22,23] and distribution of energy [24]. There is also the work of Hare et al [25], where they present a study of modern diagnosis methods in smart micro grids.…”

Section: Introductionmentioning

confidence: 99%

Predictive Data Mining Techniques for Fault Diagnosis of Electric Equipment: A Review

et al. 2020

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Data mining is a technological and scientific field that, over the years, has been gaining more importance in many areas, attracting scientists, developers, and researchers around the world. The reason for this enthusiasm derives from the remarkable benefits of its usefulness, such as the exploitation of large databases and the use of the information extracted from them in an intelligent way through the analysis and discovery of knowledge. This document provides a review of the predictive data mining techniques used for the diagnosis and detection of faults in electric equipment, which constitutes the pillar of any industrialized country. Starting from the year 2000 to the present, a revision of the methods used in the tasks of classification and regression for the diagnosis of electric equipment is carried out. Current research on data mining techniques is also listed and discussed according to the results obtained by different authors.

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“…The most regularly happening shortcoming in transmission lines is short out deficiency. Once more, Short circuit flaws are characterized into two kinds they are symmetrical and unsymmetrical deficiencies [2]. The most much of the time happening flaw in transmission system is line to ground issue.…”

Section: Introductionmentioning

confidence: 99%

Fault Classification in Transmission Systems using Wavelet Transform

Prasad¹,

2019

Gazi University Journal of Science

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A review on fault classification methodologies in power transmission systems: Part-II

Cited by 47 publications

References 5 publications

Data filter function incremental mining based on feature selection in an active distribution network

Data filter function incremental mining based on feature selection in an active distribution network

Predictive Data Mining Techniques for Fault Diagnosis of Electric Equipment: A Review

Fault Classification in Transmission Systems using Wavelet Transform

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