A new modeling of planetary gear set to predict modulation phenomenon

Zghal, Bacem; Graja, Oussama; Dziedziech, Kajetan; Chaari, Fakher; Jabłoński, Adam; Barszcz, Tomasz; Haddar, Mohamed

doi:10.1016/j.ymssp.2019.02.044

Cited by 38 publications

(13 citation statements)

References 43 publications

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“…The first part of the model-the phenomenological part-in contrast to the physical nature of failure modes used in some models [2,3], does not operate on primary object properties (mass, damping, and stiffness), but takes advantage of failure signal patterns, which are associated with particular failure modes. These patterns are based on the kinetostatic analysis of a particular drive train, as well as on well-accepted knowledge on vibration analysis and failure modes [21].…”

Section: Overviewmentioning

confidence: 99%

“…Generating synthetic data is far cheaper, faster, and more convenient than collecting real data from individual machine failures. Such models of machine damage are typically constructed on the basis of the physical nature of the damage [2,3] (physical models), or on the basis of data generated by the object, so-called data-driven models [4,5]. Theoretically, the physical model should generate data corresponding to any possible machine damage; however, they are burdened with a relatively high level of approximations and assumptions.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Model of Rolling-Element Bearing Vibration Signal

Jabłoński

2022

Energies

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The generation of synthetic vibration signals enables the testing of novel machine diagnostic methods without the costly introduction of real failures. One of major goals of vibration-based condition monitoring is the early detection of bearing faults. This paper presents a novel modeling technique based on the combination of the known mechanical properties of a modeled object (phenomenological part) and observation of a real object (behavioral part). The model uses the real pulse response of bearing housing, along with the external instantaneous machine speed profile. The presented method is object-oriented, so it is applicable to a large group of machinery.

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Section: Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid Model of Rolling-Element Bearing Vibration Signal

Jabłoński

2022

Energies

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“…Lei et al [17] proposed that the vibration signal model included vibration signals along the meshing lines as well as sun gear's vibration signal, where the amplitude modulation function based on rotating frequency of the planet carrier was used to reflect the transmission path effect. Different from expressing transfer path with window functions above, Zghal B et al [48] implicitly reflected the variable transmission path by expressing the displacement of each component at the transducer location before the resolution of the equation of motion, where the resultant vibration signal was obtained at the transducer location as the summation of all vibration signals. Moreover, the vibration characteristics in healthy condition were validated by experimental laboratory data in frequency domain.…”

Section: Introductionmentioning

confidence: 99%

A New Resultant Vibration Acceleration Model of a Planetary Gear Train and Fault Response Analysis

Meng

Cai

Guo

2022

Shock and Vibration

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A new resultant vibration acceleration model is proposed to reveal its signal characteristics more accurately in the healthy and faulty state. First, an analytical lateral-torsional coupled dynamic model is developed with consideration of time-varying mesh stiffness and damping, static transmission error, and gear backlash. Then, the effect of gear backlash and damping on the system is analyzed, and a numerical velocity signal in the healthy and faulty state is carried out. Considering the effects of transmission paths, the resultant acceleration signal along the vertical direction is constructed as the weighted vibration summation. This signal includes a vertical component of the vibration along the meshing lines of both sun-planet and ring-planet pairs. Moreover, it also contains the vertical component of the planet gears, sun gear, and planet carrier acceleration relative to their own supporting bearings. Finally, the simulation results from the resultant signal model are experimentally validated and analyzed in both time and frequency domains.

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“…In this research, an adaptive time series model is investigated, which is based on Bayesian model selection, to remove the non-fault-related components in the structural response of a gear assembly and to obtain a residual signal, which is robust to fluctuating operating conditions. In reference [19], a novel modelling of planetary gearbox vibration signals is proposed. The novelty of the approach is related to the modelling of the time varying transmission paths between moving planetary gears and a stationary vibration sensor.…”

Section: Introductionmentioning

confidence: 99%

Novel Instantaneous Wavelet Bicoherence for Vibration Fault Detection in Gear Systems

2021

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Higher order spectra exhibit a powerful detection capability of low-energy fault-related signal components, buried in background random noise. This paper investigates the powerful nonlinear non-stationary instantaneous wavelet bicoherence for local gear fault detection. The new methodology of selecting frequency bands that are relevant for wavelet bicoherence fault detection is proposed and investigated. The capabilities of wavelet bicoherence are proven for early-stage fault detection in a gear pinion, in which natural pitting has developed in multiple pinion teeth in the course of endurance gearbox tests. The results of the WB-based fault detection are compared with a stereo optical fault evaluation. The reliability of WB-based fault detection is quantified based on the complete probability of correct identification. This paper is the first attempt to investigate instantaneous wavelet bicoherence technology for the detection of multiple natural early-stage local gear faults, based on comprehensive statistical evaluation of the industrially relevant detection effectiveness estimate—the complete probability of correct fault detection.

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A new modeling of planetary gear set to predict modulation phenomenon

Cited by 38 publications

References 43 publications

Hybrid Model of Rolling-Element Bearing Vibration Signal

Hybrid Model of Rolling-Element Bearing Vibration Signal

A New Resultant Vibration Acceleration Model of a Planetary Gear Train and Fault Response Analysis

Novel Instantaneous Wavelet Bicoherence for Vibration Fault Detection in Gear Systems

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