A novel distribution model of multiple teeth pits for evaluating time-varying mesh stiffness of external spur gears

Chen, Taoyuan; Wang, Yanxue; Chen, Zhigang

doi:10.1016/j.ymssp.2019.04.029

Cited by 41 publications

(20 citation statements)

References 31 publications

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“…Compared with References [19,22,23], the effect of tooth fillet foundation deflection is not considered in the proposed gear model. As reported in Reference [54], an equation for the fillet foundation deflection is valid only when the normal stress at the tooth root is linearly distributed and confined usable for large gears.…”

Section: Discussionmentioning

confidence: 99%

“…Luo et al [21] proposed a curved bottom shape method to model the geometric features of gear tooth spalls and studied the effect of different shapes and severity conditions time-vary mesh stiffness by finite element analysis. Chen et al [22] presented a new two-dimensional Gaussian distribution model to depict pitting distribution. In their analysis, the overlaps of the pits and pits in the boundary of the tooth surface were considered in the computation of TVMS.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Characteristics of a Gear System with Double-Teeth Spalling Fault and Its Fault Feature Analysis

et al. 2020

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Tooth spalling is one of the most destructive surface failure models of the gear faults. Previous studies have mainly concentrated on the spalling damage of a single gear tooth, but the spalling distributed over double teeth, which usually occurs in practical engineering problems, is rarely reported. To remedy this deficiency, this paper constructs a new dynamical model of a gear system with double-teeth spalling fault and validates this model with various experimental tests. The dynamic characteristics of gear systems are obtained by considering the excitations induced by the number of spalling teeth, and the relative position of two faulty teeth. Moreover, to ensure the accuracy of dynamic model verification results and reduce the difficulty of fault feature analysis, a novel parameter-adaptive variational mode decomposition (VMD) method based on the ant lion optimization (ALO) is proposed to eliminate the background noise from the experimental signal. First, the ALO is used for the self-selection of the decomposition number K and the penalty factor â of the VMD. Then, the raw signal is decomposed into a set of Intrinsic Mode Functions (IMFs) by applying the ALO-VMD, and the IMFs whose effective weight kurtosis (EWK) is greater than zero are selected as the reconstructed signal. Combined with envelope spectrum analysis, the de-nosing ability of the proposed method is compared with that of the method known as particle swarm optimization-based variational mode decomposition (PSO-VMD), the fixed-parameter VMD, the empirical mode decomposition (EMD), and the local mean decomposition (LMD), respectively. The results indicate that the proposed dynamic model and background elimination method can provide a theoretical basis for spalling defect diagnosis of gear systems.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Characteristics of a Gear System with Double-Teeth Spalling Fault and Its Fault Feature Analysis

et al. 2020

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“…[12] proposed a curved bottom shape method to model the geometric features of gear tooth spalls and studied the effect of different shapes and severity conditions time-vary mesh stiffness by finite element analysis. Chen et al [13] presented a new two-dimensional Gaussian distribution model to depict pitting distribution. In their analysis, the overlaps of the pits and pits in the boundary of the tooth surface were considered in the computation of TVMS.…”

Section: •3•mentioning

confidence: 99%

Dynamic characteristics of a gear system with double-teeth spalling fault and its fault feature analysis

Shi

Wen

Pan

et al. 2020

Preprint

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Gear fault diagnosis has been a vital technology to enhance the reliability and reduce the maintenance cost of gear systems. Tooth spalling is one of the most destructive surface failure models of the gear faults. Revealing the dynamic characteristics of a gear system with spalling fault and extracting the fault feature are the premise and basis for effective fault diagnosis. Previous studies have mainly concentrated on the spalling damage on a single gear tooth, but the spalling distributed over double teeth which usually occurs in practical engineering problems is rarely reported. To remedy this deficiency, this paper constructs a new dynamical model of a gear system with double-teeth spalling fault and validates this model with various experimental tests. The dynamic characteristics of gear systems are obtained by considering the excitations induced by the number of spalling teeth, the relative position of two faulty teeth, and the rotational speed. The method based on the Variational Mode Decomposition (VMD) and the Fast Kurtogram (FK) is proposed to extract the features of the double-teeth spalling fault. First, the raw signal is decomposed into a set of Intrinsic Mode Functions (IMFs) by applying the VMD, and the IMFs with strong correlation are summed as a reconstructed signal. The reconstructed signal is then filtered by an optimal band-pass filter based on the FK. Combined with envelope spectrum analysis, the feature extraction ability of the proposed method is compared with that of the original FK method and the method based on the Empirical Mode Decomposition and the FK, respectively. The results indicate that the proposed dynamic model and fault feature extraction method can provide a theoretical basis for spalling defect diagnosis of gear systems.

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“…Khaldoon et al [10] analyzed the influences of tooth face wear on TMS, friction, and the vibration response of the gear system, which shows that the spectral peaks at the meshing frequency components along with their sidebands were the fault characteristics caused by wear. In order to describe the irregularity of tooth pitting, some novel models [11,12] based on probability distribution were proposed, and the influences of tooth pitting on TMS were investigated. Compared with tooth pitting, tooth spalling is a more serious form of tooth surface failure.…”

Section: Introductionmentioning

confidence: 99%

“…According to the above, the research on tooth spalling gradually led to more attention. Although some works [11][12][13][14][15][16][17][18] have been done on TMS of gear teeth with spalling or pitting, the research on vibration characteristics caused by spalling faults is still relatively few. In addition, although the bearing system is a key part of gear systems, the bearing was usually simplified to a simple spring system [1][2][3][4][5][6][7][8]19]; few references consider an accurate modeling of bearings.…”

Section: Introductionmentioning

confidence: 99%

Fault Feature Analysis of Gear Tooth Spalling Based on Dynamic Simulation and Experiments

Wan

Zheng

et al. 2021

Materials

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Gear dynamics analysis based on time-varying meshing stiffness (TMS) is an important means to understand the gear fault mechanism. Based on Jones bearing theory, a bearing statics model was established and introduced into a gear system. The lateral–torsion coupling vibration model of the gear shaft was built by using a Timoshenko beam element. The lumped parameter method was used to build the dynamic model of a gear pair. The dynamic model of a spur gear system was formed by integrating the component model mentioned above. The influence of rectangular and elliptical spalling on TMS was analyzed by the potential energy method (PEM). The fault feature of tooth spalling was studied by dynamic simulation and verified by experiments. It is found that the gear system will produce a periodic shock response owing to the periodic change of the number of meshing gear teeth. Due to the contact loss and the decrease of TMS, a stronger shock response will be generated when the spalling area is engaged. In the spectrum, some sidebands will appear in the resonance region. The results can provide a theoretical guide for the health monitoring and diagnosis of gear systems.

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A novel distribution model of multiple teeth pits for evaluating time-varying mesh stiffness of external spur gears

Cited by 41 publications

References 31 publications

Dynamic Characteristics of a Gear System with Double-Teeth Spalling Fault and Its Fault Feature Analysis

Dynamic Characteristics of a Gear System with Double-Teeth Spalling Fault and Its Fault Feature Analysis

Dynamic characteristics of a gear system with double-teeth spalling fault and its fault feature analysis

Fault Feature Analysis of Gear Tooth Spalling Based on Dynamic Simulation and Experiments

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