A Lagrangian approach for the electromechanical model of single-stage spur gear with tooth root cracks

Kumar, Vikash; Rai, Ayush; Mukherjee, Subrata; Sarangi, Somnath

doi:10.1016/j.engfailanal.2021.105662

Cited by 15 publications

(5 citation statements)

References 27 publications

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“…Randall et al [162] used a cepstrum based method to measure the resonant frequency of accelerometer and detected the installation failure of accelerometer. Kumar et al [163] used cepstrum analysis method for residual stator current signal of the gearbox to extract crack fault features of gears. Kim et al [164] combined cepstrum analysis, empirical wavelet transform and envelope spectrum to complete demodulation and fault diagnosis of gearbox fault signal.…”

Section: Early Application 321 Diagnosis Of Harmonics or Sidebandsmentioning

confidence: 99%

Review of spectrum analysis in fault diagnosis for mechanical equipment

Wang,

Sun

2023

Eng. Res. Express

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Various mechanical equipment play a crucial role, and their health or status may affect efficiency and safety seriously. Spectrum analysis of the corresponding signal has been widely used to diagnose the fault in the past decades. The diagnosis method based on spectrum analysis technology covers almost all aspects of mechanical fault diagnosis. However, there is a lack of review of diagnostic methods of spectrum analysis technologies in the field of mechanical equipment fault diagnosis. In order to fill this gap, this paper reviews the spectrum analysis technology in mechanical equipment diagnosis in detail. First of all, in order to let the researchers who are in contact with spectrum analysis technology for the first time quickly understand this field, the principles of spectrum are systematically sorted out, including spectrum, cepstrum, energy spectrum, power spectrum, higher-order spectrum, Hilbert spectrum, marginal spectrum, envelope spectrum, singular spectrum and so on. Furthermore, the characteristics of corresponding spectrum analysis technologies are summarized, and their advantages and disadvantages are analyzed and compared. High-quality references in recent ten years are cited for illustration to enhance persuasiveness. Finally, the prospect of spectrum analysis technology is summarized, and the future development trend of spectrum analysis technology is pointed out. It is believed that the joint diagnosis of fault severity, variable speed fault diagnosis, combined with deep learning and multiple spectrum analysis technologies should be given more attention in the future. This paper is expected to provide a comprehensive overview of mechanical fault diagnosis based on spectrum analysis theory, and help to develop corresponding spectrum analysis technologies in practical engineering.

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Section: Early Application 321 Diagnosis Of Harmonics or Sidebandsmentioning

confidence: 99%

Review of spectrum analysis in fault diagnosis for mechanical equipment

Wang,

Sun

2023

Eng. Res. Express

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“…Lin et al (2022) established an eccentric surface gear transmission system based on the Lagrangian equation and analyzed its dynamic characteristics. Kumar et al (2021) established an electromechanical model of single-stage spur gear with tooth root cracks based on the Lagrangian approach, and then they investigated the dynamic response.…”

Section: Introductionmentioning

confidence: 99%

A Lagrangian approach for the railway vehicle with gear system coupled model considering wheel polygonal faults under traction conditions

Zhao

Yang

et al. 2023

Journal of Vibration and Control

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The gear transmission system is one of the essential subsystems of railway vehicles. The wheel polygonalization can affect the gear transmission system’s condition monitoring and fault diagnosis, causing fatigue failure of the gear system and influencing driving safety. Therefore, to explore the mechanism of the wheel polygonalization in the gear system, this paper develops a Lagrangian form dynamic model of a railway vehicle with a gear transmission system. The model validation uses the data from the field test. The analysis explores the influence of the wheel polygonal fault on the gear transmission system under the traction condition. The results indicate that the wheel polygonal fault has amplitude/frequency modulation effects on the time/frequency response of the gear system. Also, the wheel polygonal fault causes the envelope of the speed curve to fluctuate periodically at a low frequency under traction conditions. The waveform asymmetry is gradually apparent as the traction continues. In the non-resonant region, the statistical analysis of the rotational speed fluctuation illustrates that the order of the wheel polygonal fault has more impact on the rotational speed fluctuation than the amplitude. Besides, in the resonance region, the eigenvalues of the system determine the magnitude of the amplitude.

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“…Fault diagnosis of the gearbox system can be done based on the vibration [1][2][3][4], current [5][6], acoustic or oil-based signal analysis etc. [2,7].…”

Section: Introductionmentioning

confidence: 99%

Assessment of water stability and water quality status of urban Patna (Bihar), India

Kumar¹,

Kumar²,

Singh³

2023

AIP Conference Proceedings

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Gearbox fault diagnosis is one of the most important parts in any industrial systems. Failure of components inside gearbox can lead to a catastrophic failure, uneven breakdown, and financial losses in industrial organization. In that case intelligent maintenance of the gearbox comes into context. This paper presents an integrated gearbox fault diagnosis approach which can easily deploy in online condition monitoring. This work introduces a nonparametric data preprocessing technique i.e., calculus enhanced energy operator (CEEO) to preserve the characteristics frequencies in the noisy and inferred vibrational signal. A set of time domain and spectral domain features are calculated from the raw and CEEO vibration signal and inputted to the multiclass support vector machine (MCSVM) to diagnose the faults on the system. An effective comparison between raw signal and CEEO signal are presented to show the impact of CEEO in gearbox fault diagnosis. The obtained results of this work look very promising and can be implemented in any type of industrial system due to its nonparametric nature.

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A Lagrangian approach for the electromechanical model of single-stage spur gear with tooth root cracks

Cited by 15 publications

References 27 publications

Review of spectrum analysis in fault diagnosis for mechanical equipment

Review of spectrum analysis in fault diagnosis for mechanical equipment

A Lagrangian approach for the railway vehicle with gear system coupled model considering wheel polygonal faults under traction conditions

Assessment of water stability and water quality status of urban Patna (Bihar), India

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