140
views
1
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Fault detection, classification and location for transmission lines and distribution systems: a review on the methods

      review-article

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          A comprehensive review on the methods used for fault detection, classification and location in transmission lines and distribution systems is presented in this study. Though the three topics are highly correlated, the authors try to discuss them separately, so that one may have a more logical and comprehensive understanding of the concepts without getting confused. Great significance is also attached to the feature extraction process, without which the majority of the methods may not be implemented properly. Fault detection techniques are discussed on the basis of feature extraction. After the overall concepts and general ideas are presented, representative works as well as new progress in the techniques are covered and discussed in detail. One may find the content of this study helpful as a detailed literature review or a practical technical guidance.

          Most cited references116

          • Record: found
          • Abstract: found
          • Article: not found

          Deep learning.

          Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            ANFIS: adaptive-network-based fuzzy inference system

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              A tutorial on support vector regression

                Bookmark

                Author and article information

                Contributors
                Journal
                HVE
                High Voltage
                High Volt.
                The Institution of Engineering and Technology
                2397-7264
                April 2016
                : 1
                : 1
                : 25-33
                Affiliations
                State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University , Beijing 100084, People's Republic of China
                Article
                HVE.2016.0005 HVE.2016.0005
                10.1049/hve.2016.0005
                f4f407dd-2356-4a8f-bbb0-c5bfa67ad900

                This is an open access article published by the IET and CEPRI under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)

                History
                : 30 December 2015
                : 10 February 2016
                : 1 April 2016
                Categories
                Review Articles

                Computer science,Engineering,Artificial intelligence,Electrical engineering,Mechanical engineering,Renewable energy
                power distribution faults,fault detection technique,distribution networks,feature extraction process,power transmission faults,power transmission lines,distribution system,feature extraction,transmission line,fault classification,fault location

                Comments

                Comment on this article