Dynamic load identification based on deep convolution neural network
H Yang, J Jiang, G Chen, J Zhao - Mechanical Systems and Signal …, 2023 - Elsevier
The deep learning methods have been extensively studied in the field of dynamic load
identification, due to their strong direct modeling ability between vibration response and …
identification, due to their strong direct modeling ability between vibration response and …
Evaluating the safety of autonomous vehicle–pedestrian interactions: An extreme value theory approach
With the increasing advancements in autonomous vehicle (AV) technologies, the forecasts
of AV market shares seem to follow an ever-growing trend. This leads to the inherent need …
of AV market shares seem to follow an ever-growing trend. This leads to the inherent need …
Prognostics and health management for predictive maintenance: A review
C Huang, S Bu, HH Lee, CH Chan, SW Kong… - Journal of Manufacturing …, 2024 - Elsevier
In the pursuit of smart manufacturing, predictive maintenance (PdM) holds significant
importance as it allows manufacturing firms to effectively mitigate avoidable downtime and …
importance as it allows manufacturing firms to effectively mitigate avoidable downtime and …
Data-based deep learning for random vibration fatigue life prediction of car seat frame
S Wang, C Wu, B Sun, H Wang, X Ding, H Yu, W Ni… - Nonlinear …, 2025 - Springer
Seats are important components in automobiles, susceptible to vibration and fatigue caused
by random road spectra. To address this issue, we introduce three methods for predicting …
by random road spectra. To address this issue, we introduce three methods for predicting …
A new DFT-based dynamic detection framework for polygonal wear state of railway wheel
Q Wang, Z ** method for estimating extreme values of the measured non-Gaussian wind pressures including the non-stationary effect …
J Li, D Zhu, C Li - Mechanical Systems and Signal Processing, 2023 - Elsevier
The study about the extreme value estimation of non-Gaussian wind pressure signals is
crucial for structural safety or health monitoring. This is because the long tail region of the …
crucial for structural safety or health monitoring. This is because the long tail region of the …
Generation of vibration load spectrum for fatigue analysis of equipment mounted on bogie frame of railway vehicle based on fatigue damage spectrum
The equipment mounted on the bogie frame of railway vehicles is subjected to non-
stationary vibrations from the bogie frame. Currently, the vibration load spectrum for fatigue …
stationary vibrations from the bogie frame. Currently, the vibration load spectrum for fatigue …
Multi-axial load spectrum extrapolation method for fatigue durability of special vehicles based on extreme value theory
G Zheng, Y Liao, B Chen, S Zhao, H Wei - International Journal of Fatigue, 2024 - Elsevier
A method for the multi-axial load spectrum extrapolation based on extreme value theory has
been proposed herein, for the first time to the best of our knowledge. The relationship …
been proposed herein, for the first time to the best of our knowledge. The relationship …
An innovative stepwise time-domain fatigue methodology to integrate damage tolerance into system dynamics
F Guo, S Wu, J Liu, X Wu, W Zhang - Vehicle System Dynamics, 2023 - Taylor & Francis
With the development of vehicle system dynamics, the multi-body system simulation has
been proven as an effective and cost-saving way to obtain fatigue loads of high-speed …
been proven as an effective and cost-saving way to obtain fatigue loads of high-speed …
Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm
M Yang, X Sun, X Deng, Z Lu, T Wang - Agriculture, 2023 - mdpi.com
To obtain the load spectrum of the traction resistance of the three-point suspension device
under tractor-plowing conditions, a load spectrum extrapolation method based on a genetic …
under tractor-plowing conditions, a load spectrum extrapolation method based on a genetic …