Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy

Li, Yuxing; Gao, Peiyuan; Tang, Bingzhao; Yi, Yingmin; Zhang, Jianjun

doi:10.3390/e24010022

Cited by 52 publications

(29 citation statements)

References 38 publications

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“…In 2021, fluctuation-based reverse DE (FEDE) was presented by combining the fluctuation and distance information of FDE and RDE. In addition, with the development of entropy theory, some new complexity indicators have been proposed and applied to the field of fault diagnosis and underwater acoustics, such as bubble entropy (BE), slope entropy (SE), and their improved versions [17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Four Nonlinear Dynamic Characteristics in Feature Extraction of Bearing Fault Diagnosis

Zhang

Liang

2022

Journal of Sensors

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To effectively extract the fault features of bearing signals in complex environments, four common nonlinear dynamic characteristics are used to analyze and compare the simulated signals and measured bearing fault signals in this paper, including Lempel-Ziv complexity (LZC), dispersion entropy (DE), Lyapunov exponent (LE), and fractal dimension (FD). Three groups of simulation experiments were carried out, and the simulation results show that all nonlinear dynamic characteristics can reflect the complexity change trend of MIX signal; compared with LZC and LE, DE and FD can better reflect the frequency change of amplitude modulated trend of chirped signal; only DE can reflect the amplitude change trend of amplitude modulated chirped signal. The experiments of feature extraction and classification are carried out for bearing fault signals. It concluded that compared with LZC, LE, and DE, FD has better stability and classification performance with the minimum standard deviation and the highest recognition rate.

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Section: Introductionmentioning

confidence: 99%

A Comparative Study of Four Nonlinear Dynamic Characteristics in Feature Extraction of Bearing Fault Diagnosis

Zhang

Liang

2022

Journal of Sensors

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“…The Chirp signal frequency varies linearly over the pulse width. The analysis of the dynamics of the received acoustic signals by means of nonlinear dynamics metric [ 39 , 40 ] shows that if the loudspeaker’s response is inadequate, this can result in intermodulation distortion of the output acoustic signal. The signal conditioner also causes harmonic distortion of the signal after it has been received by the microphone, leading to a non-linear [ 41 ] relationship between frequency and time of the acoustic signal.…”

Section: Principle Of Acoustic Ranging and Thermometrymentioning

confidence: 99%

A Time-of-Flight Estimation Method for Acoustic Ranging and Thermometry Based on Digital Lock-In Filtering

Liu

Zhou

Zhang

et al. 2022

Sensors

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Accurate ranging and real-time temperature monitoring are essential for metrology and safety in electrical conduit applications. This paper proposes an acoustic time-of-flight (TOF) estimation method based on the digital lock-in filtering (DLF) technique for conduit ranging and thermometry. The method establishes the relationship between the frequency and the time domain by applying a linear frequency modulated Chirp signal as the sound source and using the DLF technique to extract the first harmonic of the characteristic frequencies of the transmitted and received signals. Acoustic TOF estimation in the conduit is then achieved by calculating the mathematical expectation of the time difference between each characteristic frequency in the time-frequency relationship of the two signals. The experimental results with enhanced noise interference on different conduit lengths and various temperature conditions, proved that the proposed DLF method can establish a robust linear time-frequency relationship according to the characteristics of the Chirp signal, and the measurement accuracy of TOF has also been confirmed. Compared to the conventional method, the DLF method provides the lowest absolute error and standard deviation for both distance and temperature measurements with an enhanced robustness.

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“…In 2019, SlEn was first proposed by David Cuesta-Frau, and successively applied it to the classification of electroencephalographic (EEG) records and electromyogram (EMG) records [27], classify the activity records of patients with bipolar disorder [28], and the features extraction of fever time series [29]. Then SlEn is also used to extract the features of ship radiated noise signals [30] and bearing fault signals [31].…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization Fractional Slope Entropy: A New Time Series Complexity Indicator for Bearing Fault Diagnosis

Gao

2022

Fractal Fract

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Slope entropy (SlEn) is a time series complexity indicator proposed in recent years, which has shown excellent performance in the fields of medical and hydroacoustics. In order to improve the ability of SlEn to distinguish different types of signals and solve the problem of two threshold parameters selection, a new time series complexity indicator on the basis of SlEn is proposed by introducing fractional calculus and combining particle swarm optimization (PSO), named PSO fractional SlEn (PSO-FrSlEn). Then we apply PSO-FrSlEn to the field of fault diagnosis and propose a single feature extraction method and a double feature extraction method for rolling bearing fault based on PSO-FrSlEn. The experimental results illustrated that only PSO-FrSlEn can classify 10 kinds of bearing signals with 100% classification accuracy by using double features, which is at least 4% higher than the classification accuracies of the other four fractional entropies.

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Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy

Cited by 52 publications

References 38 publications

A Comparative Study of Four Nonlinear Dynamic Characteristics in Feature Extraction of Bearing Fault Diagnosis

A Comparative Study of Four Nonlinear Dynamic Characteristics in Feature Extraction of Bearing Fault Diagnosis

A Time-of-Flight Estimation Method for Acoustic Ranging and Thermometry Based on Digital Lock-In Filtering

Particle Swarm Optimization Fractional Slope Entropy: A New Time Series Complexity Indicator for Bearing Fault Diagnosis

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