SVD principle analysis and fault diagnosis for bearings based on the correlation coefficient

Qiao, Zijian; Pan, Zhengrong

doi:10.1088/0957-0233/26/8/085014

Cited by 130 publications

(79 citation statements)

References 21 publications

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“…It shows the statistical relationships between two or more random variables or observed data values. It has been used in the chromosomes' similarity analysis [16], the relationship analysis between cerebral venous thrombosis and oral contraceptives in adult women [17], and the mechanical vibration signal similarity analysis [18,19]. In this paper, Pearson's correlation coefficient is used and can be measured by…”

Section: Ivmd-teo Time-frequency Analysis Methodsmentioning

confidence: 99%

Time-Frequency Analysis Based on Improved Variational Mode Decomposition and Teager Energy Operator for Rotor System Fault Diagnosis

Liu

Tang

Wang

et al. 2016

Mathematical Problems in Engineering

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A time-frequency analysis method based on improved variational mode decomposition and Teager energy operator (IVMD-TEO) is proposed for fault diagnosis of turbine rotor. Variational mode decomposition (VMD) can decompose a multicomponent signal into a number of band-limited monocomponent signals and can effectively avoid model mixing. To determine the number of monocomponents adaptively, VMD is improved using the correlation coefficient criterion. Firstly, IVMD algorithm is used to decompose a multicomponent signal into a number of monocompositions adaptively. Second, all the monocomponent signals’ instantaneous amplitude and instantaneous frequency are demodulated via TEO, respectively, because TEO has fast and high precision demodulation advantages to monocomponent signal. Finally, the time-frequency representation of original signal is exhibited by superposing the time-frequency representations of all the monocomponents. The analysis results of simulation signal and experimental turbine rotor in rising speed condition demonstrate that the proposed method has perfect multicomponent signal decomposition capacity and good time-frequency expression. It is a promising time-frequency analysis method for rotor fault diagnosis.

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Section: Ivmd-teo Time-frequency Analysis Methodsmentioning

confidence: 99%

Time-Frequency Analysis Based on Improved Variational Mode Decomposition and Teager Energy Operator for Rotor System Fault Diagnosis

Liu

Tang

Wang

et al. 2016

Mathematical Problems in Engineering

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“…In order to improve the accuracy of the coordinates of laser tracer stations obtained by the self-calibration algorithm, the Singular Value Decomposition (SVD) transformation [16,17] of the covariance matrix is used for plane fitting. The coordinates of m laser tracer stations obtained by self-calibration algorithm are fitted into a plane.…”

Section: Optimizing Coordinates Of Laser Tracer Stationsmentioning

confidence: 99%

Calibration Method for Angular Positioning Deviation of a High-Precision Rotary Table Based on the Laser Tracer Multi-Station Measurement System

et al. 2019

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This paper proposes a calibration method for angular positioning deviation of a high-precision rotary table based on the laser tracer multi-station measurement system. The algorithm error of the calibration method for angular positioning deviation of a high-precision rotary table based on the laser tracer multi-station measurement system was mainly discussed. During the experiments, the laser tracer was fixed on the work surface of the rotary table, and the rotary was fixed on the work surface of the coordinate measurement machine (CMM). The rotary table was rotated with the same angular interval. In this case, an optimization method for calculating the coordinates of a laser tracer station by using Levenberg–Marquardt algorithm and singular value decomposition transform was proposed. Then, the angular positioning deviation of the rotary table was calibrated by an established geometric relationship model between the coordinates of laser tracer stations and the rotation angle of the rotary table. The angular positioning deviation of the high-precision rotary table was as low as ±0.9″, and the error of the calibration method was ±0.4″. The experimental results proved the feasibility of the proposed calibration method. The calibration method proposed in this paper is suitable for the case that the rotary table is not linked with the CMM, especially for large high-precision rotary tables.

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“…However, the faulty signal acquired from the bearing is usually weak or submerged in strong noise [3,4]. Traditional weak signal detection methods, such as empirical mode decomposition (EMD) [5], wavelets transform (WT) [6], singular value decomposition (SVD) [7], and variational mode decomposition (VMD) [8], mainly reduced noise to improve signal-to-noise ratio (SNR) and extract fault characteristics, which inevitably weakened useful fault signal characteristic information. In contrast, SR can utilize noise to enhance weak signal energy.…”

Section: Introductionmentioning

confidence: 99%

A New Second-Order Tristable Stochastic Resonance Method for Fault Diagnosis

Yuan

Wang

et al. 2019

Symmetry

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Vibration signals are used to diagnosis faults of the rolling bearing which is symmetric structure. Stochastic resonance (SR) has been widely applied in weak signal feature extraction in recent years. It can utilize noise and enhance weak signals. However, the traditional SR method has poor performance, and it is difficult to determine parameters of SR. Therefore, a new second-order tristable SR method (STSR) based on a new potential combining the classical bistable potential with Woods-Saxon potential is proposed in this paper. Firstly, the envelope signal of rolling bearings is the input signal of STSR. Then, the output of signal-to-noise ratio (SNR) is used as the fitness function of the Seeker Optimization Algorithm (SOA) in order to optimize the parameters of SR. Finally, the optimal parameters are used to set the STSR system in order to enhance and extract weak signals of rolling bearings. Simulated and experimental signals are used to demonstrate the effectiveness of STSR. The diagnosis results show that the proposed STSR method can obtain higher output SNR and better filtering performance than the traditional SR methods. It provides a new idea for fault diagnosis of rotating machinery.

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SVD principle analysis and fault diagnosis for bearings based on the correlation coefficient

Cited by 130 publications

References 21 publications

Time-Frequency Analysis Based on Improved Variational Mode Decomposition and Teager Energy Operator for Rotor System Fault Diagnosis

Time-Frequency Analysis Based on Improved Variational Mode Decomposition and Teager Energy Operator for Rotor System Fault Diagnosis

Calibration Method for Angular Positioning Deviation of a High-Precision Rotary Table Based on the Laser Tracer Multi-Station Measurement System

A New Second-Order Tristable Stochastic Resonance Method for Fault Diagnosis

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