A modified normal contact stiffness model considering effect of surface topography

Zhao, Bin; Zhang, Song; Man, Jia; Zhang, Qing; Chen, Yan

doi:10.1177/1350650114558099

Cited by 18 publications

(14 citation statements)

References 30 publications

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“…When a gearbox fails, the detection signal usually exhibits nonlinear and nonstationary characteristics [1,2]. Combined Time-Frequency Analysis is a hotspot of signal processing research [3,4].…”

Section: Introductionmentioning

confidence: 99%

Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis

Wang

Cai

et al. 2019

Complexity

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In industrial production, it is highly essential to extract faults in gearbox accurately. Specifically, in a strong noise environment, it is difficult to extract the fault features accurately. LMD (local mean decomposition) is widely used as an adaptive decomposition method in fault diagnosis. In order to improve the mode mixing of LMD, ELMD (ensemble Local Mean Decomposition) is proposed as local mode mixing exists in noisy environment, but white noise added in ELMD cannot be completely neutralized leading to the influence of increased white noise on PF (product function) component. This further leads to the increase in reconstruction errors. Therefore, this paper proposes a composite fault diagnosis method for gearboxes based on an improved ensemble local mean decomposition. The idea is to add white noise in pairs to optimize ELMD, defined as CELMD (Complementary Ensemble Local Mean Decomposition) then remove the decomposed high noise component by PE (Permutation Entropy) while applying the SG (Savitzky-Golay) filter to smooth out the low noise in PFs. The method is applied to both simulated signal and experimental signal, which overcomes mode mixing phenomenon and reduces reconstruction error. At the same time, this method avoids the occurrence of pseudocomponents and reduces the amount of calculation. Compared with LMD, ELMD, CELMD, and CELMDAN, it shows that improved ensemble local mean decomposition method is an effective method for extracting composite fault features.

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Section: Introductionmentioning

confidence: 99%

Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis

Wang

Cai

et al. 2019

Complexity

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“…The next task was to analyze the distribution and the geometrical information of the asperities, including their locations (x, y), heights z, equivalent summit radii R v and tangential offsets r between different asperities. The authors have studied the relevant method to determine these parameters in the previous work [24]. The asperity summits were located obeying the mathematical expression:…”

Section: Topography Measurement and Asperity Analysismentioning

confidence: 99%

Analytical asperity interaction model and numerical model of multi-asperity contact for power hardening materials

Zhao

Zhang

Zheng

2015

Tribology International

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“…Assume that the asperity deformation of elastic surface under the normal load is elastic and the asperity heights are in normal distribution. In addition, the normal distribution curve above the average is fitted by the exponential function, then the contact load P(d) and the number of asperities contacting with the rotor N(d) can be expressed as follows [17][18][19][20] Pðd…”

Section: Distributed Mass Equivalent Dynamic Modelmentioning

confidence: 99%

Dynamic analysis of finger seal in the complex working state

Zhao

Chen

Wang

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part G:

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With the development of aero-engine industry technology, the operating conditions for finger seal become more horrible, including that high temperature, assembly type of finger seal, rotor tilt, and impact of rotor coexist. Unfortunately, the coupled effect on the dynamic performance of finger seal is not studied in previous works for the dynamic of finger seal. In this paper, the parameters of equivalent dynamic model for finger seal, including the equivalent structure stiffness of finger stick, the contact stiffness between finger stick and rotor, the friction heat between finger boot and rotor and the rotor displacement excitation, are corrected when the coupled effect of rotor tilt, assembly condition, temperature, and impact are considered. In addition, the distributed mass equivalent dynamic model is developed for considering the complex working conditions (including rotor tilt, assembly condition, temperature effect, and impact effect). Based on this model, the dynamic performance of finger seal in the complex working state is analyzed, and the influence of the complex working state on the dynamic performance is also studied. The results indicate that effect of the complex working state on the leakage performance and wear performance of finger seal is complex. The work in this paper demonstrates the necessity of considering the complex working conditions in the analysis of the dynamic performance of finger seal.

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A modified normal contact stiffness model considering effect of surface topography

Cited by 18 publications

References 30 publications

Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis

Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis

Analytical asperity interaction model and numerical model of multi-asperity contact for power hardening materials

Dynamic analysis of finger seal in the complex working state

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