Analysis of mean function discrete LSM-estimator for biperiodically nonstationary random signals

Javorskyj, Ihor; Dzeryn, O.; Yuzefovych, Roman

doi:10.23939/mmc2019.01.044

Cited by 8 publications

(3 citation statements)

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“…The points of the functional maximum for each of the considered stages, with an accuracy of up to three digits after the comma, correspond to the basic frequency estimator and are equal to 0 1 1 24.206 Hẑ = = f P (Figure 6a), Proceeding from the estimated basic frequency values, the harmonic amplitudes were calculated on the basis of expressions ( 23) and (26). The amplitude spectra of the vibration deterministic part are represented in the form of diagrams in Figure 7 and the harmonic amplitude values ( ) Proceeding from the estimated basic frequency values, the harmonic amplitudes were calculated on the basis of expressions ( 23) and (26). The amplitude spectra of the vibration deterministic part are represented in the form of diagrams in Figure 7 and the harmonic amplitude valuesÂ kf 0 are provided in Table 1.…”

Section: Analysis Of the Deterministic Oscillationsmentioning

confidence: 99%

“…The models for gearbox vibration proposed in the literature can be considered as particular cases of its representation in the form of BPCRPs [9,[24][25][26]. The mean and the covariance functions of these processes are bi-periodic time functions.…”

Section: Introductionmentioning

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: Analysis Of the Deterministic Oscillationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%