A5101924354- Advanced machining processes and optimization
- Advanced MEMS and NEMS Technologies
- Advanced Machining and Optimization Techniques
- Manufacturing Process and Optimization
- Acoustic Wave Resonator Technologies
- Advanced Measurement and Metrology Techniques
- Microwave Engineering and Waveguides
- Advanced Manufacturing and Logistics Optimization
- Civil and Geotechnical Engineering Research
- Advanced Numerical Analysis Techniques
- Injection Molding Process and Properties
- Photonic and Optical Devices
- Landslides and related hazards
- Soil, Finite Element Methods
- Metal Alloys Wear and Properties
- Semiconductor Lasers and Optical Devices
- Advanced Surface Polishing Techniques
- Industrial Technology and Control Systems
- Geomechanics and Mining Engineering
- Advanced Sensor and Control Systems
- Advanced Multi-Objective Optimization Algorithms
- Wireless Power Transfer Systems
- Optimization and Packing Problems
- Petri Nets in System Modeling
- 3D IC and TSV technologies
Southeast University
2006-2025
Guangxi University
2014-2024
Guangzhou Urban Planning Survey & Design Institute
2024
South China Institute of Collaborative Innovation
2024
Central South University of Forestry and Technology
2006-2013
Central South University
2006-2013
Northwest Research Institute of Chemical Industry
2012
Hunan University
2010
China Railway Corporation
2010
Huazhong University of Science and Technology
2006
Abstract Revealing the surface effect of nanoparticles (NPs) is one key prerequisites for understanding their extraordinary properties at nanometer scale. However, active NPs frequently suffer from oxidation and contamination, which hinders realization delicate surface‐related properties. Upon this issue, paper develops an in situ evaporation deposition ( ‐E&D) method inside a transmission electron microscope (TEM), by with ultra‐clean surfaces can be controllably fabricated examined....
It is difficult to accurately predict the response of some stochastic and complicated manufacturing processes. Data‐driven learning methods which can mine unseen relationship between influence parameters outputs are regarded as an effective solution. In this study, support vector machine (SVM) applied develop prediction models for machining Kernel function loss Gaussian radial basis ε‐insensitive function, respectively. To improve accuracy reduce parameter adjustment time SVM model,...
To address the issues of workpiece distortion and excessive material melting caused by heat accumulation during laser cutting thin-walled sheet metal components, this paper proposes a segmented optimization method for process parameters in considering thermal effects. The focuses on predetermined perforation points machining paths. Firstly, an innovative temperature prediction model Tpr,t is established nth point process, with error less than 10%. Secondly, using PSO-BP-constructed quality...
This article deals with the packing problem of irregular items allocated into a rectangular sheet to minimize waste. Conventional solution is not visual during process. It obtains reasonable and relatively satisfactory between nesting time solution. adopts physical method that uses rubber band algorithm simulate wrapping those items. The simulation shows fast resultant force applied in translate, rotate, slide them make area decrease obtain high density. An improved analogy QuickHull...
Precise tool wear prediction is the key to improving productivity of entire workpiece. Reliable technology can reduce machine downtime caused by change process, and also make machining process more efficient. This paper briefly reviews research technology, then uses ARIMA (p, d, q) model in time series LSTM predict respectively. The results show that has better performance.
Purpose The purpose of this paper is to establish a paint deposition pattern model applied robotic air spray painting in order achieve the accuracy and uniformity film thickness on free‐form surface. Design/methodology/approach opts for an exploratory study using curvature circle method surface construct gun model. First, ellipse dual‐ β distribution fitted basic experimental data from painting. Second, proposed theoretical result coincident with verification experiment spraying cylinder...
In engineering applications, Gaussian process (GP) regression method is a new statistical optimization approach, to which more and attention paid. It does not need pre-assuming specified model just requires small amount of initial training samples. Based on the design experiment (DOE), determining reasonable sample space an important part for GP surrogate model. this paper, novel intelligent DOE, translational propagation algorithm, employed obtain optimal Latin hypercube designs (TPLHDs)....
In this study, RuT400(σb ≥ 500 MPa) was milled with different cutting speeds, feeding rates and depths to construct force surface roughness prediction models via response method (RSM). The milling parameters were optimised surface, contour map iterative algorithm. results show that rate depth are factors significantly affect the force. Similarly, speed found be significant in regards roughness. multivariate linear equations yield more accurate predictions than fitting linearised non-linear...