Fault Recognition

  • Nishchal K. VermaEmail author
  • Al Salour
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 256)


This chapter details the last module of the fault diagnosis framework, i.e., fault recognition. After the collection of relevant subsets of the features, as detailed in the Chap.  5, classification is performed to decide the machine state. Chapter  2 provides details about different kinds of machine faults. Classification is the task to categorize the given object by learning the relationship between the selected set of features and their class label. Since fault recognition is also treated as a classification process; here, the description of different classification techniques, such as k-means clustering, k-nearest neighbour (k-NN), Naive Bayes classifier, Support Vector Machine (SVM), Multiclass classification algorithms, etc., is provided in this chapter.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Inter-disciplinary Program in Cognitive ScienceIndian Institute of Technology KanpurKanpurIndia
  2. 2.Boeing Research and TechnologySaint LouisUSA

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