Analytical lump model for the nonlinear dynamic response of bolted flanges in aero-engine casings

Beaudoin, Marc-Antoine; Behdinan, Kamran

doi:10.1016/j.ymssp.2018.05.056

Cited by 75 publications

(32 citation statements)

References 24 publications

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“…(4) e hybrid prediction models, including CEEMDAN-PE-IGMMW, EMD-PE-IGMMW, and CEEMDAN-IGMMW, have better forecasting results than other five single models, which illustrates that series decomposition is helpful to enhance the prediction performance of single models. (5) e forecasting ability of IGMMW for most of the jumping IDI points is better than that of other single models, which indicates the sensitivity of Figure 14: Comparisons of the forecasting results of eight models in the degradation tendency prediction. Complexity the constructed model for data fluctuations.…”

Section: Degradation Tendency Prediction Of Aircraft Enginesmentioning

confidence: 98%

“…With the gradual improvement of mechanical system's integration and complexity, reasonable and complete health state monitoring is of great signi cance for ensuring stable and reliable operation of equipment [1][2][3]. As an essential component and core power source of aircraft, the operational stability of aeroengine has important impact on system safety and maintenance costs [4][5][6]. In recent years, with the proposal of condition-based maintenance (CBM), the fault response mode has converted from passive treatment to active prevention [7,8].…”

Section: Introductionmentioning

confidence: 99%

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Multistep Degradation Tendency Prediction for Aircraft Engines Based on CEEMDAN Permutation Entropy and Improved Grey–Markov Model

et al. 2019

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As an essential component and core power source of aircraft, the operational stability of aeroengine has important impact on system safety and reliability. Accurate degradation tendency prediction on an engine can not only improve its operational stability but also significantly reduce the maintenance costs. In this paper, a novel forecasting method that combines CEEMDAN permutation entropy and improved Grey–Markov model is proposed to perform multistep degradation tendency prediction of aircraft engines. In order to accurately quantify the degradation level of engines, a new integrated degradation index (IDI) is innovatively designed by multidimensional sensory data. And then, because of high speed and excellent performance, CEEMDAN algorithm is specifically employed to decompose the generated IDI series to eliminate the potential influence of stochastic fluctuations. Aiming at the complexity of intrinsic mode functions (IMFs) generated by CEEMDAN, an IMFs reconstruction strategy based on permutation entropy is developed to better characterize the degradation states. Finally, on the basis of above achievements and for higher forecasting efficiency and accuracy, an improved Grey–Markov model combined with the moving window algorithm, which is unique, is constructed to realize multistep degradation trend prediction of engines. The proposed method is applied to the degradation tendency prediction of aircraft engines. The experimental results validate the effectiveness and superiority of the proposed method, and it is more suitable for engineering applications in comparison with other methods.

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Section: Degradation Tendency Prediction Of Aircraft Enginesmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Multistep Degradation Tendency Prediction for Aircraft Engines Based on CEEMDAN Permutation Entropy and Improved Grey–Markov Model

et al. 2019

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“…Jalaliet al provided a new linear joint model and investigated the influence of preload and surface roughness quality on the identified equivalent stiffness [7]. A new lump model applied in finite element analysis was given by Beaudoin et al for the nonlinear dynamic response of bolted flanges [8]. With these interfaces withstanding contact pressures and frictions, the contact problems in engineering include geometry errors, microscopic roughness, lubrication, coating, conduction of heat, and electricity, which are nonlinear and complicated.…”

Section: Introductionmentioning

confidence: 99%

Dynamic and Stability Analysis of Multibolt Plane Joints under Normal Forces

Zhang

et al. 2019

Applied Sciences

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In this paper, a stiffness model of contact surfaces based on a modified three-dimensional fractal contact model is built, which is in accordance with the experiment results. Additionally, the static, dynamic, and stable behaviors of the bolt joint between the spindle box and the machine bed are analyzed. The mathematical relationship between fractal parameters of the surface topography and the stiffness of the system was established to accurately study its static behaviors. Asymmetric curves are observed from the load–deflection results and the nonlinear stiffness characteristic is also presented. It is shown that both the stress and the stiffness increase with the increase of the displacement near the static equilibrium position. Meanwhile, a simplified model without the consideration of roughness is compared with joint interfaces composed from milling, scraping, and grinding surfaces. Numerical calculation was employed to investigate effects of design parameters on the system under harmonic excitation when the processing method, excitation force, bolt pre-tightening force, topography parameters, and other structural parameters, i.e., nominal contact area, joint thickness and bolt number, are eventually regarded as the control parameters. The aim of the article is to analysis the influence of these parameters, including surface morphology, on nonlinear characteristics of the bolt interface with fractal contact surfaces andto provide some references to improve the characteristics.

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“…With the growing complexity of mechanical systems, such as aircraft engines, electricity-producing devices, and high-speed vehicles, the increasing requirements of online health monitoring based on distributed sensor networks have become a focal point for the purpose of stable and reliable operation [1][2][3][4]. As the core component and power source of aircrafts, the operational reliability of an aero engine has significant impact on the personal safety and maintenance costs [5][6][7][8]. Recently, with the development of condition-based maintenance (CBM), the fault response pattern experienced a transformation from passive reply to active prevention [9,10].…”

Section: Introductionmentioning

confidence: 99%

Degradation Tendency Measurement of Aircraft Engines Based on FEEMD Permutation Entropy and Regularized Extreme Learning Machine Using Multi-Sensor Data

Jiang

Shan

et al. 2018

Energies

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As the core component and main power source for aircrafts, the reliability of an aero engine is vital for the security operation of aircrafts. Degradation tendency measurement on an engine can not only improve its safety, but effectively reduce the maintenance costs. In this paper, a hybrid method using multi-sensor data based on fast ensemble empirical mode decomposition permutation entropy (FEEMD-PE) and regularized extreme learning machine (RELM), systematically blending the signal processing technology and trend prediction approach, is proposed for aircraft engine degradation tendency measurement. Firstly, a synthesized degradation index was designed utilizing multi-sensor data and a data fusion technique to evaluate the degradation level of the engine unit. Secondly, in order to eliminate the irregular data fluctuation, FEEMD was employed to efficiently decompose the constructed degradation index series. Subsequently, considering the complexity of intrinsic mode functions (IMFs) obtained through sequence decomposition, a permutation entropy-based reconstruction strategy was innovatively developed to generate the refactored IMFs (RIMFs), which have stronger ability for describing the degradation states and contribute to improving the prediction accuracy. Finally, RIMFs were used as the inputs of the RELM model to measure the degradation tendency. The proposed method was applied to the degradation tendency measurement of aircraft engines. The results confirm the effectiveness and superiority of the proposed method, and it is more suitable for actual applications compared with other existing approaches.

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Analytical lump model for the nonlinear dynamic response of bolted flanges in aero-engine casings

Cited by 75 publications

References 24 publications

Multistep Degradation Tendency Prediction for Aircraft Engines Based on CEEMDAN Permutation Entropy and Improved Grey–Markov Model

Multistep Degradation Tendency Prediction for Aircraft Engines Based on CEEMDAN Permutation Entropy and Improved Grey–Markov Model

Dynamic and Stability Analysis of Multibolt Plane Joints under Normal Forces

Degradation Tendency Measurement of Aircraft Engines Based on FEEMD Permutation Entropy and Regularized Extreme Learning Machine Using Multi-Sensor Data

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