4.6 Article

A tilted orbital grinding technique for hole-making of CFRP composite laminates

Journal

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s00170-019-03904-x

Keywords

CFRP; Hole-making; Grinding; Thrust force; Cutting temperature; Delamination

Funding

  1. Natural Science Foundation of Jiangxi Province [20171BAB206033, 20171BBE50011]

Ask authors/readers for more resources

Carbon fiber reinforced polymer (CFRP) laminates have been widely employed in the manufacturing of airplane. Usually, hole-making is the final machining process to join CFRP laminates with other components. However, CFRP laminates are considered as hard-to-machine materials, which results in some serious failures during hole-making process such as fiber pull-out, fiber break, and matrix delamination. To improve the hole-making quality, a tilted orbital grinding (TOG) method was proposed in this study. In the proposed TOG method, a grinding wheel was used as the machining tool and its axis was set as tilted against the axis of the hole with a small angle. Through replacing the revolving motion of the tool in conventional helical milling with conical pendulum motion of the grinding wheel, a hole could be made by a grinding process. The thrust forces, cutting temperatures, and the quality of the holes in the proposed TOG process were investigated by experimental methods. The results show that the thrust forces and cutting temperatures in TOG process are greatly less than those in the conventional orbital milling process. Scanning electron microscope (SEM) images of the hole that made by TOG method show that there is no crack generated in the entrance side of the hole, and the pull-out delamination in the exit side of the hole is significantly reduced. The experimental results indicate that the proposed TOG method has a potential application in the hole-making of CFRP laminates.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Automation & Control Systems

Cutting force, chip formation, and tool wear during the laser-assisted machining a near-alpha titanium alloy BTi-6431S

Yanfeng Gao, Gui Wang, Michael J. Bermingham, Matthew S. Dargusch

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2015)

Article Automation & Control Systems

The development of an ultrasonic vibration hand-held pneumatic drill for hole-machining on CFRP composite materials

Yanfeng Gao, Xing Yang, Jianhua Xiao, Hua Zhang

Summary: A novel ultrasonic vibration hand-held pneumatic drill was developed and successfully applied for drilling CFRP materials. The use of this device significantly reduces hand shakes and thrust forces, leading to a reduction in matrix resin peel-off and delamination defects during the drilling process.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2021)

Article Automation & Control Systems

Research on the deviation sensing of V-groove weld seam based on a novel two channel acoustic sensor

Yanfeng Gao, Jianhua Xiao, Genliang Xiong, Hua Zhang

Summary: A novel acoustic sensor was developed in this study to detect the deviation of weld seam by collecting sound signals. Experimental results demonstrate that the developed sensor has a linear property for detecting the deviation of V-groove weld seam. This research provides a new method for weld seam tracking.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2022)

Article Metallurgy & Metallurgical Engineering

Weld penetration identification with deep learning method based on auditory spectrum images of arc sounds

Yanfeng Gao, Qisheng Wang, Jianhua Xiao, Genliang Xiong, Hua Zhang

Summary: This study uses arc sound signals and convolutional neural networks to achieve real-time monitoring and identification of penetration states of weld seam. By simulating the functions of the human auditory system, the proposed identification method's anti-interference ability is improved. Experimental results show that even when the signal-to-noise ratio is less than 5 dB, the accuracy rate of identification remains above 95%.

WELDING IN THE WORLD (2022)

Article Engineering, Electrical & Electronic

Machine Motion Trajectory Detection Based on Siamese Graph-Attention Adaptive Network

Jianbo Yu, Yihao Huang, Yanfeng Gao, Qingfeng Li

Summary: This article proposes an anti-interference machine motion trajectory detection method based on the Siamese graph-attention adaptive network (SiamGAAN). A graph attention-based feature matching method is introduced to transfer template feature information to the search feature in the feature extraction network of SiamGAAN. The regression network based on an adaptive anchor-free mechanism predicts the distance between the sampling points and the boundary of the target region directly. The proposed quality determination-based index in the classification network improves the accuracy of the target box. SiamGAAN achieves a 1.5% accuracy rate and 1.9% tracking success rate improvement on the benchmark dataset OTB2015 compared with typical methods, and a tracking success rate of 90.58% in the robotic arm's motion trajectory simulating the real operation in the workshop.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2023)

Article Engineering, Industrial

Penetration state identi fication of lap joints in gas tungsten arc welding process based on two channel arc sounds

Yanfeng Gao, Qisheng Wang, Jianhua Xiao, Hua Zhang

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY (2020)

No Data Available