Comparative analysis study of resistance characteristics of backhoe hydraulic excavators DOI Creative Commons
Tianyu Li, Zhigui Ren, Xiaoping Pang

et al.

Mechanics & Industry, Journal Year: 2024, Volume and Issue: 25, P. 36 - 36

Published: Jan. 1, 2024

Resistance characteristics research lays a foundation for establishing and improving excavator performance evaluation. Therefore, thorough understanding of the general laws governing excavation resistance is particularly significant. Based on experimental data from 8 sets conditions involving two types 20 t backhoe hydraulic excavator, this paper first conducted comparative analysis distribution trends concentration coefficients, moment angles, differential component rotation angular velocities. Subsequently, employing response surface optimization theory, main value intervals relevant under different were obtained, impact scenarios type variations these was explored. Finally, principal applied to calculate verify theoretical digging force. The results indicate differences in conditions, with machine having more significant influence than condition. Variations lead changes evaluation metrics excavator. Under front-end working unit maintains stable operational speed.

Language: Английский

A novel method for remaining useful life of solid-state lithium-ion battery based on improved CNN and health indicators derivation DOI

Yan Ma,

Zhenxi Wang,

Jinwu Gao

et al.

Mechanical Systems and Signal Processing, Journal Year: 2024, Volume and Issue: 220, P. 111646 - 111646

Published: July 1, 2024

Language: Английский

Citations

20
Data-driven hydraulic pressure prediction for typical excavators using a new deep learning SCSSA-LSTM method DOI
Hao Feng, Hao Zhou, Donghui Cao

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127078 - 127078

Published: Feb. 1, 2025

Language: Английский

Citations

0
Application of physics-informed machine learning in performance degradation and RUL prediction of hydraulic piston pumps DOI
Yadong Zhang, Shaoping Wang, Chao Zhang

et al.

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: unknown, P. 111108 - 111108

Published: April 1, 2025

Language: Английский

Citations

0
Physics-informed neural network for velocity prediction in electromagnetic launching manufacturing DOI
Hao Sun, Yuxuan Liao, Hao Jiang

et al.

Mechanical Systems and Signal Processing, Journal Year: 2024, Volume and Issue: 220, P. 111671 - 111671

Published: June 25, 2024

Language: Английский

Citations

2
Data-physics hybrid-driven external forces estimation method on excavators DOI
Yuying Shen, Jixin Wang,

Chenlong Feng

et al.

Mechanical Systems and Signal Processing, Journal Year: 2024, Volume and Issue: 223, P. 111902 - 111902

Published: Sept. 2, 2024

Language: Английский

Citations

2
Mining Trajectory Planning of Unmanned Excavator Based on Machine Learning DOI Creative Commons
Zhong Jin,

Mingde Gong,

Dingxuan Zhao

et al.

Mathematics, Journal Year: 2024, Volume and Issue: 12(9), P. 1298 - 1298

Published: April 25, 2024

Trajectory planning plays a crucial role in achieving unmanned excavator operations. The quality of trajectory results heavily relies on the level rules extracted from objects such as scenes and optimization objectives, using traditional theoretical methods. To address this issue, study focuses professional operators employs machine learning methods for job planning, thereby obtaining planned trajectories which exhibit excellent characteristics similar to those operators. Under typical working conditions, data collection analysis are conducted operators, with key points being extracted. Machine is then utilized train models under different parameters order obtain optimal model. ensure sufficient samples training, bootstrap method employed adequately expand sample size. Compared spline curve method, generated by reduce maximum speeds boom arm, dipper stick, bucket, swing joint 8.64 deg/s, 10.24 18.33 1.6 respectively; moreover, error does not exceed 2.99 deg when compared curves drawn operators; and, finally, model continuously differentiable without position or velocity discontinuities, their overall performance surpasses that method. This paper proposes generation combines establishes learning-based trajectory-planning eliminates need manually establishing complex rules. It applicable motion path various conditions excavators.

Language: Английский

Citations

0
Dynamic Prediction Modeling of Loader's Loading Resistance Under Different Loading Trajectories DOI

Binyun Wu,

Liang Hou, Shaojie Wang

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Comparative analysis study of resistance characteristics of backhoe hydraulic excavators DOI Creative Commons
Tianyu Li, Zhigui Ren, Xiaoping Pang

et al.

Mechanics & Industry, Journal Year: 2024, Volume and Issue: 25, P. 36 - 36

Published: Jan. 1, 2024

Resistance characteristics research lays a foundation for establishing and improving excavator performance evaluation. Therefore, thorough understanding of the general laws governing excavation resistance is particularly significant. Based on experimental data from 8 sets conditions involving two types 20 t backhoe hydraulic excavator, this paper first conducted comparative analysis distribution trends concentration coefficients, moment angles, differential component rotation angular velocities. Subsequently, employing response surface optimization theory, main value intervals relevant under different were obtained, impact scenarios type variations these was explored. Finally, principal applied to calculate verify theoretical digging force. The results indicate differences in conditions, with machine having more significant influence than condition. Variations lead changes evaluation metrics excavator. Under front-end working unit maintains stable operational speed.

Language: Английский

Citations

0