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Fault Diagnoses of Hydraulic Turbine Using the Dimension Root Similarity Measure of Single-valued Neutrosophic Sets

Jun Ye

Department of Electrical and Information Engineering, Shaoxing University, 508 Huancheng West Road, Shaoxing, Zhejiang Province 312000, P.R. China

* Corresponding Author: Jun Ye,

Intelligent Automation & Soft Computing 2018, 24(1), 1-8.


This paper proposes a dimension root distance and its similarity measure of single-valued neutrosophic sets (SVNSs), and then develops the fault diagnosis method of hydraulic turbine by using the dimension root similarity measure of SVNSs. By the similarity measures between the fault diagnosis patterns and a testing sample with single-valued neutrosophic information and the relation indices, we can determine the main fault type and the ranking order of various vibration faults for predicting some possible fault trend. Then, the comparison of the fault diagnoses of hydraulic turbine based of the proposed dimension root similarity measure and the existing cotangent similarity measure of SVNSs is provided to demonstrate the effectiveness and rationality of the proposed fault diagnosis method. The fault diagnosis results of hydraulic turbine show that the proposed fault diagnosis method not only gives the main fault types of hydraulic turbine, but also provides useful information for multifault analyses and future possible fault trends. The developed fault diagnosis method is effective and reasonable in the fault diagnosis of hydraulic turbine under single-valued neutrosophic environment.


Cite This Article

J. Ye, "Fault diagnoses of hydraulic turbine using the dimension root similarity measure of single-valued neutrosophic sets," Intelligent Automation & Soft Computing, vol. 24, no.1, pp. 1–8, 2018.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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