4.7 Article

A two-level adaptive chirp mode decomposition and tangent entropy in estimation of single-valued neutrosophic cross-entropy for detecting impeller defects in centrifugal pump

期刊

APPLIED ACOUSTICS
卷 197, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apacoust.2022.108905

关键词

Monoblock centrifugal pump; Adaptive chirp mode decomposition; Tangent entropy; Neutrosophic set; Symmetric cross entropy

资金

  1. All India Council for Technical Education (AICTE) , New Delhi, India [8-29/RIFD/RPS-NDF/Policy -1/2018-19]

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A novel approach for identifying impeller defects in a centrifugal pump is demonstrated using single-valued neutrosophic cross-entropy (SVNCE) extracted from adaptive chirp mode decomposition (ACMD). ACMD decomposes acoustic signals into different modes by estimating instantaneous frequencies. The proposed scheme incorporates novel tangent entropy to select prominent modes and improve the performance of ACMD. The energy of each prominent mode is calculated under different health conditions of the impeller to determine energy interval ranges for unknown impeller defect conditions. These ranges are further converted into single-valued neutrosophic sets (SVNSs) for recognition of different impeller defects using the minimum argument principle.
A novel approach for identifying the impeller defects in the centrifugal pump has been demonstrated by extracting the single-valued neutrosophic cross-entropy (SVNCE) of adaptive chirp mode decomposition (ACMD). ACMD decomposes the acoustic signals into different modes by estimating the instantaneous frequencies. The ACMD is incorporated with novel tangent entropy which helps in selecting the promi-nent modes and enhances the performance of ACMD. The energy of each prominent mode is computed under different health conditions of the impeller. The energy eigen values set the energy interval ranges for unknown impeller defect conditions which are further converted into single-valued neutrosophic sets (SVNSs). The minimum argument principle utilizes the least SVNCE values between SVNSs of testing sam-ples (obtained from unknown impeller conditions) and SVNSs of training samples (obtained from known impeller conditions) to recognize the different impeller defects of the pump. The proposed scheme has been compared with other techniques such as EEMD, VMD, permutation entropy and corrected condi-tional entropy. The results of the comparison suggested the superiority of the proposed method.(c) 2022 Elsevier Ltd. All rights reserved.

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