An energy-based fatigue life estimation and optimization of an electric mining dump truck welded frame

Mi, Chengji; Shi, Yuanquan; Ming, Rui; Xiao, Xuewen; Liu, Xianghuan; Tang, Jiachang; Liu, Jidong

doi:10.1007/s40430-023-04040-0

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…Meng et al [13] proposed the GMM-SOMVSA-CO detailed model and calculation process to solve the RBMDO problem, so that there is no need to consider the uncertainties caused by other disciplines in the process of single-discipline analysis and optimization. Mi et al [14] studied the estimation and optimization of fatigue life of welded structures of electric mining dump trucks, proposed an interval strain energy density method to evaluate the fatigue life of welded structures, estimated the interval fatigue life of the locations where fatigue failure may occur, in order to extend the service life of the frame and achieve its lightweight, a multi-objective optimization design based on the kriging proxy model was carried out.…”

Section: Introducementioning

confidence: 99%

“…Finally, based on the constructed two-condition approximation model, a multi-objective genetic algorithm (MOGA) is used to optimize the mass, bending stiffness and sixth-order frequency. Mi et al [14] calculated the cyclic stresses and strains of the welded frame structure of the mining electric dump truck by nonlinear finite element analysis, and estimated the interval fatigue life of the possible fatigue failure locations. Based on the constructed evaluation system, Han et al [34] established a performance evaluation model based on analytic hierarchy process, entropy weight method and topological object metamodel.…”

Section: Introducementioning

confidence: 99%

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Multi-condition stability analysis and lightweight research of mining wide-body dump truck compartment

Liu,

Tian

et al. 2024

Meas. Sci. Technol.

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This paper proposes a multi-condition optimization method based on single condition optimization and weight. This method analyzes and discusses various working states of the wide-body dump truck and optimize its structure. Firstly, the modal shape and natural frequency of the carriage under modal conditions are analyzed using the finite element method. Combined with the mechanic’s theory, the carriage's force, deformation, and stress are studied under the turning and partial load conditions. This part provides a basis for subsequent stability analysis and lightweight research. According to the filtering white noise method and differential equation method, the f-class road model and the vehicle system dynamics model are established in MATLAB to study the influence of road vibration on the stability of the dump truck during operation. The carriage vibration data prove that the road vibration causes the low order resonance of the carriage and affects the stability of the dump truck. This part provides a basis for the subsequent stability optimization. Based on the above analysis, a multi-objective genetic algorithm (MOGA) based on the response surface is used to optimize the structural parameters of the carriage under partial load conditions, turning conditions and modal conditions, to realize the optimization of stability, mass, stress and deformation of the carriage. Finally, the entropy weight method is used to fuse the optimization results of the three working conditions. The correctness of the comprehensive optimization results is verified, and the wide-body dump truck carriage optimization is realized, proving the feasibility of the proposed method.

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Section: Introducementioning

confidence: 99%

Section: Introducementioning

confidence: 99%

Multi-condition stability analysis and lightweight research of mining wide-body dump truck compartment

Liu,

Tian

et al. 2024

Meas. Sci. Technol.

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Reliability analysis and optimization design of magnetic fluid dynamic seal shell structure under thermal/mechanical load

Mi,

Liu,

Zhang

et al. 2024

Journal of Magnetism and Magnetic Materials

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A modified Manson-Halford model based on improved WOA for fatigue life prediction under multi-level loading

Yang,

Zou,

Cao

et al. 2024

International Journal of Damage Mechanics

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The Manson-Halford (M-H) nonlinear cumulative damage model is widely applied for fatigue life analysis problems under multi-level loading. In this model, the influence of loading sequence on the fatigue life can be better considerer, but the loading interaction effect is ignored. An improved whale optimization algorithm (IWOA) by integrating multiple strategies is proposed. The ability of global search and local exploitation is balanced and improved through nonlinear convergence factor, adaptive weighting factors and the Cauchy reverse learning strategies. In order to fully account for loading interaction effect, loading weighting factors are introduced to modify the M-H model, and the parameters are optimized through the global search properties of IWOA. The model is evaluated on multi-level loading fatigue experimental data from five metal materials and two aluminum alloy welded joints. The results suggest that the proposed IWOA has better optimization accuracy compared to the standard whale optimization algorithm (WOA). The proposed modified M-H model has better prediction performance compared to the four traditional cumulative damage models, which can be effectively applied to multi-level loading fatigue life analysis problems under actual working conditions. The proposed model is useful for the study of fatigue life evaluation methods.

show abstract

An energy-based fatigue life estimation and optimization of an electric mining dump truck welded frame

Cited by 3 publications

References 26 publications

Multi-condition stability analysis and lightweight research of mining wide-body dump truck compartment

Multi-condition stability analysis and lightweight research of mining wide-body dump truck compartment

Reliability analysis and optimization design of magnetic fluid dynamic seal shell structure under thermal/mechanical load

A modified Manson-Halford model based on improved WOA for fatigue life prediction under multi-level loading

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