Crack characteristic analysis of multi-fault rotor system based on whirl orbits

Xiang, Ling; Zhang, Yue; Hu, Aijun

doi:10.1007/s11071-018-4715-y

Cited by 25 publications

(9 citation statements)

References 27 publications

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“…However, the fault frequency cannot be detected in FFT spectra in Figure 25 The vibration signals are hard to be distinguished because the vibrations induced by crack and other factors are mixed in real-world gear systems, especially for the early crack. As an effective reference (Xiang et al, 2018), the analysis of nonlinear dynamics of a rotor system was used for fault detection, which is interesting and worth exploring on gear system.…”

Section: Effects Of the Crack Depthmentioning

confidence: 99%

“…Yang et al (2019b) analyzed the dynamics with clearance nonlinearity and discussed the vibration behaviors with fault. In the field of rotor dynamics, Xiang et al (2018) built up a nonlinear model of a multi-fault rotor system and analyzed the influence of crack on dynamics through the whirl orbits, bifurcation diagram and frequency spectra, where a method for crack detection was proposed. Moreover, the experimental results agree with the theoretical ones, which confirms the contribution of nonlinear dynamics and offers a new perspective for fault diagnosis.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear dynamics of a spur gear pair with tooth root crack based on an amplitude modulation function

Gao

Wang

Bajwa

2021

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PurposeGear transmissions are widely utilized in practice. This paper aims to uncouple the crack feature from the cracked time-varying mesh stiffness (TVMS) and investigate the effects of the crack on the nonlinear dynamics of a spur gear pair.Design/methodology/approachAn approximate method to simulate the cracked TVMS is proposed by using an amplitude modulation function. The ratio of mesh stiffness loss is introduced to estimate the TVMS with different crack depths and angles. The dynamic responses are obtained by solving a torsional model which takes the non-loaded static transmission error, the backlash and the cracked TVMS into account. By using the bifurcation diagram, the largest Lyapunov exponent (LLE) and dynamic mesh force, the influences of crack on nonlinear behaviors are examined. The dynamic characteristics are identified from the phase diagram, Poincaré map, dynamic mesh force, time series and FFT spectra.FindingsThe comparison between the healthy and cracked gear pairs indicates that the crack affects the system motions, such as the obvious changes of impact force and unpredictable instability. Besides, the additive and difference combination frequencies can be found in periodic-1 and -2 motions, but they are covered in periodic-3 and chaotic motions. Deeper crack is an important determinant of the nonlinear behaviors at a higher speed.Originality/valueThe research provides an interesting perspective on cracked TVMS and reveals the connection between crack and nonlinear behaviors of the gear pairs.

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Section: Effects Of the Crack Depthmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nonlinear dynamics of a spur gear pair with tooth root crack based on an amplitude modulation function

Gao

Wang

Bajwa

2021

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“…Catastrophic failures of rotating machinery may start with small defects and cracks on the shaft, thus it's important to study the vibrations of cracked rotor and provide theoretical and experimental basis for detection and online monitoring [38]. Xiang et al [39] established a nonlinear model, which took the rub-impact forces, the time varying stiffness of cracked shaft and the nonlinear oil-film forces into account. The dynamic responses of rotor were reflected by orbits, bifurcation diagrams, time series and frequency spectra.…”

Section: Introductionmentioning

confidence: 99%

Torsional vibration responses of the engine crankshaft-gearbox coupled system with misfire and breathing slant crack based on instantaneous angular speed

Liu

Ding

et al. 2022

Mechanical Systems and Signal Processing

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“…Xiang et al studied coupled faults of crack, rub-impact, and oil-film instability [16][17][18]. A simple mathematical model, consistent in shaft, disc, and two bearings as supports, is proposed, where effects of shear, torsional vibration, and gyroscopic couple were neglected.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Validation of Experimentally Optimised Parameters Used in a Vibration-Based Machine-Learning Model for Fault Diagnosis in Rotating Machines

Espinoza-Sepulveda

Sinha

2021

Machines

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Mathematical models have been widely used in the study of rotating machines. Their application in dynamics has eased further research since they can avoid time-consuming and exorbitant experimental processes to simulate different faults. The earlier vibration-based machine-learning (VML) model for fault diagnosis in rotating machines was developed by optimising the vibration-based parameters from experimental data on a rig. Therefore, a mathematical model based on the finite-element (FE) method is created for the experimental rig, to simulate several rotor-related faults. The generated vibration responses in the FE model are then used to validate the earlier developed fault diagnosis model and the optimised parameters. The obtained results suggest the correctness of the selected parameters to characterise the dynamics of the machine to identify faults. These promising results provide the possibility of implementing the VML model in real industrial systems.

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Crack characteristic analysis of multi-fault rotor system based on whirl orbits

Cited by 25 publications

References 27 publications

Nonlinear dynamics of a spur gear pair with tooth root crack based on an amplitude modulation function

Nonlinear dynamics of a spur gear pair with tooth root crack based on an amplitude modulation function

Torsional vibration responses of the engine crankshaft-gearbox coupled system with misfire and breathing slant crack based on instantaneous angular speed

Mathematical Validation of Experimentally Optimised Parameters Used in a Vibration-Based Machine-Learning Model for Fault Diagnosis in Rotating Machines

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