A vibration-based method for contact pattern assessment in straight bevel gears

Buzzoni, Marco; D’Elia, Gianluca; Mucchi, Emiliano; Dalpiaz, Giorgio

doi:10.1016/j.ymssp.2018.10.002

Cited by 18 publications

(12 citation statements)

References 25 publications

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“…The dynamic characteristics of the gear system include inherent characteristics, parameter stability, and dynamic response. 7 Moreover, inherent characteristics include natural frequency and mode shape, which are the basic problems of gear dynamics research. Therefore, these characteristics are of great significance in the dynamic response of the system, the generation and transmission of dynamic loads, and the vibration behavior of the system.…”

Section: Introductionmentioning

confidence: 99%

Model and Characteristic Simulation Analysis of a Two-Speed Transmission System

Chen¹,

Xie²,

Liu³

et al. 2021

The International Journal of Acoustics and Vibration

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One of the main tasks in the research of a helicopter two-speed transmission system was to improve its dynamic characteristics. For the low gear mode of the system, a dynamic model was established by using the lumped parameter method, the method of Runge-Kutta was used to solve the nonlinear dynamic system equations. The effect of the gear module on the dynamic transmission error, dynamic load of the gear pair and the dynamic windup angle of a one-way clutch were studied. And the effect of the one-way clutch torsional stiffness on the dynamic transmission error and dynamic load of the gear pair was also studied. The results show that: 1)~the dynamic transmission error of the gear pair decreases and the dynamic load of the gear pair increases with the increase of the gear module at the lower range of excitation frequencies; 2)~the dynamic windup angle of the one-way clutch increases with an increase of the gear module. 3)~the dynamic transmission error of the gear pair and the maximum dynamic load increases with an increase of the one-way clutch torsional stiffness at the lower and medium range of excitation frequencies. The above results can provide reference for the subsequent upgrade and improvement of the two-speed transmission system.

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Section: Introductionmentioning

confidence: 99%

Model and Characteristic Simulation Analysis of a Two-Speed Transmission System

Chen¹,

Xie²,

Liu³

et al. 2021

The International Journal of Acoustics and Vibration

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“…There are many publications in field of the bevel gear pairs having straight teeth [2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…The [7] paper deals with the development and the validation of an approach for the contact pattern evaluation in straight bevel gears within a pass/fail decision process. The developed method is based on blending vibration-based condition indicators with classification algorithms so as to distinguish adequate contact patterns from inaccurate pairs.…”

Section: Introductionmentioning

confidence: 99%

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The influence of the shaft angle value on the normal stress and displacement repartition by bevel gear pairs − a TCA investigation

Bodzás

2020

Mechanics & Industry

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Five types of bevel gear pairs having straight teeth were designed to analyze the effect of the modification of the shaft angle. This angle is the parameter − subject of TCA. After the geometric design process and the creation and assembly of the CAD models, Tooth Contact Analysis (TCA) was performed in order to get the mechanical parameters focusing of the tooth roots of the connecting teeth. We repeated this process five times since the load torques were also changed. The received mechanical parameters on the teeth connection of the pinion and the driven gear were analyzed with taking in consideration all four-tooth root surfaces that limit the contacting teeth pair. Finally, we referred to the useful selection of the appropriate gear pair for the engineering application.

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“…Fault characteristic information is submerged in strong noise, which is difficult to identify [1,2]. At present, some researchers are interested in the typical fault diagnosis of spiral-bevel gears [3][4][5], which mainly focuses on the feature extraction based on wavelet decomposition, such as the discrete wavelet-based method for the fault diagnosis of arc tooth wimble gears [4] and adaptive multiwavelet-based method for the fault diagnosis of spiral-bevel gears [5]. Generally speaking, compared with the parallel shaft gear system and planetary gear system, research on the fault diagnosis of spiral-bevel gear systems is insufficient [6,7].…”

Section: Introductionmentioning

confidence: 99%

CEEMDAN‐Based Permutation Entropy: A Suitable Feature for the Fault Identification of Spiral‐Bevel Gears

Jiang

Hongchuang

et al. 2019

Shock and Vibration

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A spiral-bevel gear is a basic transmission component and is widely used in mechanical equipment; thus, it is important to monitor and diagnose its running state to ensure safe operation of the entire equipment setup. The vibration signals of spiral-bevel gears are typically quite complicated, as they present both nonlinear and nonstationary characteristics and are interfered with by strong noise. The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method has been proven to be an effective method for analyzing this kind of signal. However, the fault feature information after CEEMDAN is not obvious and needs to be quantified. Permutation entropy can be used to quantify the randomness, complexity, and mutation of vibration time-series signals. This paper proposes to take the CEEMDAN-based permutation entropy as the sensitive feature for spiral-bevel gear fault identification. First, the raw vibration signal is decomposed by the CEEMDAN method to obtain a series of intrinsic modal functions (IMFs). The IMFs which included greater amounts fault information are selected as the optimal IMFs based on the correlation coefficient. Next, the permutation entropy values of the optimal IMFs are calculated. In order to obtain accurate permutation entropy values, the two key parameters, namely, embedding dimension and delay time, are optimized by using the overlapping parameter method. In order to assess the sensibility of the permutation entropy features, the support vector machine (SVM) is used as the classifier for fault mode identification, and the diagnostic accuracy can verify its sensibility. The permutation entropy of CEEMDAN-based/EEMD-based/EMD-based features, combined with SVM, is applied to identify three different fault modes of spiral-bevel gears. Their respective diagnostic accuracies are 100%, 88.33%, and 83.33%, which indicate that the CEEMDAN-based permutation entropy is the most sensitive feature for the fault identification of spiral-bevel gears.

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A vibration-based method for contact pattern assessment in straight bevel gears

Cited by 18 publications

References 25 publications

Model and Characteristic Simulation Analysis of a Two-Speed Transmission System

Model and Characteristic Simulation Analysis of a Two-Speed Transmission System

The influence of the shaft angle value on the normal stress and displacement repartition by bevel gear pairs − a TCA investigation

CEEMDAN‐Based Permutation Entropy: A Suitable Feature for the Fault Identification of Spiral‐Bevel Gears

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