Forced oscillations of cracked beam under the stochastic cyclic loading

Matsko, Ivan; Javorskyj, Ihor; Yuzefovych, Roman; Zakrzewski, Zbigniew

doi:10.1016/j.ymssp.2017.08.021

Cited by 19 publications

(10 citation statements)

References 35 publications

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“…The methodology for the vibration signal processing, developed in our investigations [10,17,28], has some specific content. It involves the sequential employment of the methods for the covariance and spectral analysis of the stationary random processes, the methods of searching for hidden periodicities of the first and the second order [29][30][31][32], their separation and individual analysis, empirical harmonic analysis on the basis of Fourier series and Fourier transformations, and the methods of PCRP covariance and spectral analysis [4,8,9,[34][35][36].…”

Section: Gear Fault Detection As Pcrp Estimation Issuementioning

confidence: 99%

“…As follows from the investigations already carried out [10][11][12][13][14][15][16][17][18]28], the vibration signal generated by a rotating machine acquires the properties of the periodical non-stationarity of the second order as the fault initiates. This means that the time variations of the variance and the covariance function estimators are the test indication of machine damage.…”

Section: The Analysis Of the Hidden Periodicities Of The Second Ordermentioning

confidence: 99%

“…The efficiency of the PCRP technique for early fault detection and the analysis of fault growth are illustrated by the results of processing experimental data acquired at different faulty stages of a wind turbine gearbox. This work is based on the original results obtained by authors concerning the discovery and analysis of the hidden periodicities described by PCRP and their generalizations [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

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Methods of Hidden Periodicity Discovering for Gearbox Fault Detection

Javorskyj

Matsko

Yuzefovych

et al. 2021

Sensors

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It is shown that the models of gear pair vibration, proposed in literature, are particular cases of the bi-periodically correlated random processes (BPCRPs), which describe its stochastic recurrence with two periods. The possibility of vibration and analysis within the framework of BPCRP approximation, in the form of periodically correlated random processes (PCRPs), is grounded and the implementation of vibration processing procedures using PCRP techniques, which are worked out by the authors, is given. Searching for hidden periodicities of the first and the second orders was considered as the main issue of this approach. The estimation of the non-stationary period (basic frequency) allowed us to carry out a detailed analysis of the deterministic part, the covariance structure of the stochastic part, and to form, using their parameters, the sensitive indicators for fault detection. The results of the processing of the wind turbine gearbox vibration signals are presented. The amplitude spectra of the deterministic oscillations and the time changes of the stochastic part power for different fault stages are analyzed. The most efficient indicators, which are formed using the amplitude spectra for practical applications, are proposed. The presented approach was compared with known in literature cyclostationary analysis and envelope techniques, and its advantages are shown.

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Section: Gear Fault Detection As Pcrp Estimation Issuementioning

confidence: 99%

Section: The Analysis Of the Hidden Periodicities Of The Second Ordermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Methods of Hidden Periodicity Discovering for Gearbox Fault Detection

Javorskyj

Matsko

Yuzefovych

et al. 2021

Sensors

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“…Erdogan [8] investigated the nonlinear dynamics of cracked beams by using the linear properties of nonlinear vibrating structures to extend the crack detection mechanisms. Matsko et al [34] have presented an investigation of cracked beam forced oscillations for identifying random procedures correlated periodically with the use of statistical methods. For the first time, Prawin et al [35] identified the pure spatial location of the breathing crack using a single sensor measurement based on a new vibration-based damage detection technique, which relies on the zero strain energy nodes concept.…”

Section: Related Workmentioning

confidence: 99%

Simulation and Analysis with Wavelet Transform Technique and the Vibration Characteristics for Early Revealing of Cracks in Structures

Abu‐Hamdeh

Daqrouq

Mebarek‐Oudina

2021

Mathematical Problems in Engineering

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Implementation of improved instruments is used to detect damage in an accurate manner and fully analyze its characteristics. An aluminum beam has been used in this work to identify cracks by using a vibration technique. The simulation of frequency response feature was conducted using a finite element model to provide average measures of intensities of vibration. Two forms of wavelet packet transform (WPT) entropies Shannon and log energy were applied to identify the position, width, and size of the crack. The results showed that with an increase in crack depth, the amplitude also increased at certain crack sizes and for all crack positions. For two crack depths of 1.6 mm and 0.16 mm having the same crack size and position 12 mm and 60 mm, respectively, a 4.5% increase in amplitude was observed at a crack depth of 1.6 mm. Moreover, the amplitude varied inversely with the position. A 12.6% increase in amplitude was observed at a crack depth of 1.6 mm rather than 0.16 mm, while both depths occurred at the same crack position (75 mm) and size (20 mm). Experimental validation was performed on a cantilever beam with one crack. The maximum absolute error found was 7.5% for the crack position and 9.1% for the crack size. With the increase in crack depth, the obtained results decrease the stiffness of a beam in a single crack case.

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“…After that, Liu and Barkey investigated the coupling mechanism of the dynamic response and crack growth by using a breathing crack stiffness model and a friction damping model based on a single degree of freedom system of the beam [5]. Matsko et al examined the forced vibration response of a cracked beam through statistical methods for the periodically correlated random process [6]. Jena and Parhi studied the dynamic response of a cracked cantilever beam having multiple transverse open cracks and a traversing mass [7].…”

Section: Introductionmentioning

confidence: 99%

Prediction on Remaining Life of a V‐Notched Beam by Measured Modal Frequency

Liu

Barkey

2019

Shock and Vibration

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A prediction method for the remaining life of a V-notched beam using measured modal frequencies is proposed in this article. The main purpose is to provide a new monitoring method of crack growth for a cantilever beam. At first, the fatigue crack growth characteristic and the change law of modal frequencies of a V-notched cantilever beam under cyclic loading were studied by experiments. Subsequently, the relation of modal frequencies and crack growth were analyzed. Thereafter, the decrease ratio of the first modal frequency was employed to reflect the crack damage so as to set up the relation of the modal frequency and the crack damage, and the evolution model between the crack damage and the cyclic loading numbers were set up. A prediction method for crack growth life was proposed for a cantilever beam based on the decrease ratio of the first modal frequency in the end. The remaining life of a V-notched cantilever beam can be obtained using the proposed method with a given endured loading cycles and the corresponding measured modal frequency. Results indicate that the remaining fatigue life of the V-notched cantilever beam is related to the decrease ratio of the modal frequency, and the predicted remaining life is in good agreement with the measured remaining life as the crack depth extends to a certain value.

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Forced oscillations of cracked beam under the stochastic cyclic loading

Cited by 19 publications

References 35 publications

Methods of Hidden Periodicity Discovering for Gearbox Fault Detection

Methods of Hidden Periodicity Discovering for Gearbox Fault Detection

Simulation and Analysis with Wavelet Transform Technique and the Vibration Characteristics for Early Revealing of Cracks in Structures

Prediction on Remaining Life of a V‐Notched Beam by Measured Modal Frequency

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