Fault diagnoses of hydraulic turbine using the dimension root similarity measure of single-valued neutrosophic sets

Abstract

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 measure between the fault diagnosis patterns and a testing sample with single-valued neutrosophic information and the relation indices, we can determine the fault type and rank faults. Then, the vibration fault diagnosis of hydraulic turbine is presented to demonstrate the effectiveness and rationality of the proposed diagnosis method by the comparative analysis. The fault diagnosis results of hydraulic turbine show that the proposed diagnosis method not only gives the main fault types of hydraulic turbine but also provides useful information for multi-fault analyses and future fault trends. The developed method is effective and reasonable in the fault diagnosis of hydraulic turbine under single-valued neutrosophic environment.

Generalized Distance-Based Entropy and Dimension Root Entropy for Simplified Neutrosophic Sets

“…For two SvNSs B = {< a i , T B ( a i ), U B ( a i ), F B ( a i )> | a i ∊ A } and C = {< a i , T C ( a i ), U C ( a i ), F C ( a i )> | a i ∊ A } in the universal set A , Ye [ 24 ] defined a dimension root distance of SvNSs as follows: …”

“…Motivated by distance measures and dimension root similarity measure [ 24 ], we proposed the generalized distance-based entropy and dimension root entropy of simplified NSs in this paper. As for the framework of this paper, we introduce some concepts of simplified NSs in Section 2 , and then Section 3 proposes the simplified neutrosophic generalized distance-based entropy and dimension root entropy.…”

Edas Method for Multiple Criteria Group Decision Making With Picture Fuzzy Information and Its Application to Green Suppliers Selections

“…G. W. Wei (2017c) gave some cosine similarity measures of PFSs for strategic decision making on the basis of the traditional similarity measures (Hung & Yang, 2004;D. F. Li, 2004;Szmidt & Kacprzyk, 2004;Ye, 2018;Zhai, Xu, & Liao, 2018). G. W. Wei (2017a) proposed some aggregation operators for MCDM based on the PFSs based on the traditional aggregation operators (Deng, Wei, Gao, & Wang, 2018;Gao, Lu, G. W. Wei, & Y. Wei, 2018;Z.…”

A Neutrosophic Set Based Fault Diagnosis Method Based on Multi-Stage Fault Template Data

“…Several methods based on the neutrosophic set have been proposed for fault diagnosis. For instance, Ye proposed cotangent similarity measures for SVNSs based on a cotangent function for the fault diagnosis of steam turbines [47] and the dimension root similarity measure of SVNSs for the fault diagnosis of hydraulic turbines [48], which are all used for fault diagnosis under a single-valued neutrosophic environment. Kong et al proposed the misfire fault diagnosis method for the fault diagnosis of gasoline engines [49].…”

“…Afterwards, compared with the method based on random fuzzy variables [54], the application of the neutrosophic set gives consideration to the uncertainty of the fault types and the unknown fault sample, which reflects and handles the uncertainty of fault information well. Compared with former neutrosophic set based methods for fault diagnosis [47][48][49][50], the generation of a neutrosophic set based on multi-stage fault template data in this paper can deal with uncertain information better and diagnose the faults efficiently.…”