Measurement of FRFs of coupled geared rotor system and the development of an accurate finite element model

Saxena, Ankur; Chouksey, Manoj; Parey, Anand

doi:10.1016/j.mechmachtheory.2018.01.010

Cited by 19 publications

(10 citation statements)

References 23 publications

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“…Many monitoring techniques have been developed to detect these faults. 1,2 In a study, Li et al 3 used the hidden Markov model-based fault diagnostic method for various rotor faults like rotor unbalance, rotor-to-stator rub, oil whirl, and pedestal looseness in a rotating machinery under speed-up and speed-down conditions. In other study, Surendra et al 4 worked on diagnosis of unbalance in a rotating system by using operating deflection shapes (ODSs).…”

Section: Introductionmentioning

confidence: 99%

Unbalance detection in rotating machinery based on support vector machine using time and frequency domain vibration features

Gangsar¹,

Pandey²,

Chouksey³

2021

Noise & Vibration Worldwide

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The automated diagnostics of the unbalance in a rotor system has been presented in this study based on an artificial intelligence technique called support vector machine. In order to develop a support vector machine–based unbalance diagnosis, first the raw vibration signals in time and frequency domain are measured experimentally from healthy and unbalanced rotor installed on machine fault simulator. Then, three critical statistical features, namely, standard deviation, skewness, and kurtosis are extracted from the time and frequency domain vibration signals. Further, the features are used for training and testing of the support vector machine for building the automated diagnostic system for unbalance in a rotating system. The results from the present study show that the unbalance fault diagnosis can be effectively done based on the developed support vector machine–based methodology. The automated diagnosis of unbalance is possible with the time domain as well as frequency domain features. The results are better with time domain features than frequency domain features. In addition, the diagnosis is performed and found to be robust at most of the operating speeds of the rotor; however, the diagnosis should be avoided to attempt using the present methodology at very lower operating speeds.

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Section: Introductionmentioning

confidence: 99%

Unbalance detection in rotating machinery based on support vector machine using time and frequency domain vibration features

Gangsar¹,

Pandey²,

Chouksey³

2021

Noise & Vibration Worldwide

Self Cite

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“…To sum up, at present, there are various and more accurate methods to solve the time-varying meshing stiffness, but most of the gear transmission systems use the lumped mass method to establish the model, ignoring the flexibility of the transmission shaft, so that the final solution error is large. In order to solve the above problems, Saxena et al [9] established a dynamic model of singlestage gear transmission system based on the finite element method. The results show that the system response is more practical after considering the shaft flexibility.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on Dynamic Characteristics of Two-Stage Gear System With Gear and Shaft Cracks Considering the Shaft Flexibility

et al. 2020

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To analyze the vibration characteristic differences of a gear transmission system with gear and shaft cracks, an improved computational method for deriving the shaft stiffness matrix with breathing cracks is developed. Also, the three-dimensional contact model of spur gear with a crack is established via the finite element method (FEM), and its meshing stiffness is calculated. Simultaneously, considering bearing stiffness and shaft flexibility, the finite element dynamic models of two-stage gear transmission system with gear and shaft cracks are established. Based on this, different source fault vibration responses are compared and the influencing factors are explored. In addition, a novel signal processing method based on the particle swarm optimization, maximum correlated kurtosis deconvolution, variational, mode decomposition and fast spectral kurtosis (PSO-MCKD-VMD-FSK) is utilized to extract fault characteristics for the signal-to-noise ratio and uneven energy distribution problems. Results show that a system with gear cracks mainly presents periodic impact in the time domain, while in the frequency domain it impacts rotation frequency modulation near the meshing frequency and its multiple frequencies. However, the shaft crack breathing effect meant that the time domain mainly presents "simple harmonic" modulation, and the rotation frequency and its faulty shaft multiplication occurs in the low-frequency region of the frequency domain. The PSO-MCKD-VMD-FSK method extracts fault features in a strong noise environment and has good robustness. Results identify different source faults and provide a theoretical basis.

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“…Ma et al (2015aMa et al ( , 2016 proposed a new method to study the effects of the tooth crack and profile modification on vibrations of the gear system. Saxena et al (2018) presented a finite element (FE) model to study the gear pair contact on the modal vibrations of the gear system. Yu et al (2018) introduced a new vibration to analyze the effects of the tooth spalls on vibrations of the gear system.…”

Section: Introductionmentioning

confidence: 99%

Vibration analysis of a flexible gearbox system considering a local fault in the outer ring of the supported ball bearing

Liu

Yuan

2020

Journal of Vibration and Control

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Ball bearings are key components in the gear transmission system. Supported ball bearings have great influences on the vibrations of the gear transmission system, especially the presence of the local faults. Although some reported works formulated the local fault in the supported bearings of the gear transmission system, the box and shaft were considered as rigid bodies. To overcome this problem, a rigid-flexible coupling dynamic model for a flexible gearbox with the supported ball bearings is developed, which cannot be described by the previous multibody models. The local fault in the supported bearing is described by a time-varying impact force model with a half-sine profile. The bearing clearance, flexible shaft, and box are considered in the rigid-flexible coupling dynamic model. The flexible shaft and box are formulated by a finite element method. The damping and contact stiffness in the bearings and gears are obtained by the previous methods in the listed works. The frictions between the mating components are formulated by the Coulomb friction model. An experimental study is applied to validate the rigid-flexible coupling dynamic model. The effects of the faults on the vibration transmission characteristics are investigated. The results provide that the local fault in the supported bearings will greatly affect the vibrations of the gearbox system. Moreover, it depicts that the vibration collection point for the defective bearings should be located at the same side to obtain better singles. This work can provide a more reasonable method for understanding the vibration transmission characteristics of the gearbox system with the local faults in the supported bearings than the reported multibody models.

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Measurement of FRFs of coupled geared rotor system and the development of an accurate finite element model

Cited by 19 publications

References 23 publications

Unbalance detection in rotating machinery based on support vector machine using time and frequency domain vibration features

Unbalance detection in rotating machinery based on support vector machine using time and frequency domain vibration features

Comparative Study on Dynamic Characteristics of Two-Stage Gear System With Gear and Shaft Cracks Considering the Shaft Flexibility

Vibration analysis of a flexible gearbox system considering a local fault in the outer ring of the supported ball bearing

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