An adaptive trajectory planning algorithm for robotic belt grinding of blade leading and trailing edges based on material removal profile model

In the robotic belt grinding process, the elastic contact condition between the flexible tool and the workpiece is a critical issue which extremely influences the surface quality of the manufactured part. The existing analysis of elastic removal mechanism is based on the statistic contact condition but ignoring the dynamic removal phenomenon. In this paper, we discussed the dynamic contact pressure distribution caused by the non-unique removal depth in the grinding process. Based on the analysis of the equivalent removal depth of a single grit and the trajectories of grits in manufacturing procedure, an elastic grinding surface topography model was established with the consideration of the dynamic contact condition in the removing process. Robotic belt grinding experiments were accomplished to validate the precision of this model, while the result showed that the surface roughness prediction error could be confined to 11.6%, which meant this model provided higher accuracy than the traditional predicting methods.

show abstract

“…, u g p total H H a  (10) where，a p,total is the totally removal depth，which can be obtained by Preston Equation, as Eq.11 [19].…”

Section: The Dynamic Model Of Contact Pressurementioning

confidence: 99%

“…tan + mn y x b   (19) Figure 4. The grit morphology characteristics where， ψ is the angle between the robotic feeding orientation and the cutting velocity orientation， b mn is the offset of grain trajectory relative to the contact area center point.…”

Section: Tan = 22mentioning

confidence: 99%

Experimental and numerical study on surface generated mechanism of robotic belt grinding process considering the dynamic deformation of elastic contact wheel

Liu

Gong

Sun

et al. 2022

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…Wang et al [3] proposed an abrasive belt polishing path planning method for precise material removal based on Hertz contact theory. Lv et al [4] carried out adaptive trajectory planning for the leading and trailing edges of the blades by using robot abrasive belt polishing.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning of Robot-assisted Abrasive Cloth Wheel Polishing Blade based on Flexible Contact

Zhang

Liu

Yang

2021

Preprint

View full text Add to dashboard Cite

Industrial robot-assisted abrasive cloth wheel (ACW) accurately polish blades is considered to be a challenging task, and it is necessary to realize the digitalization of the process. Due to the flexible contact characteristics of abrasive cloth wheel and the change of blade surface curvature, the amount of microscopic material removal and the topographical errors of the blade surface are not uniform. So the surface roughness value is larger. In this paper, considering the flexible deformation of the blade and the abrasive cloth wheel during polishing contact, the polishing contact model of the blade and the abrasive cloth wheel is established and simulated. Firstly, based on the Preston equation and Hertz contact theory, the material removal profile in the contact area of the blade and the abrasive cloth wheel is analyzed. Secondly, the step length is optimized by considering the deformation of the abrasive cloth wheel in thedirection, and the line spacing is optimized by considering the material removal uniformity in thedirection. The NURBS curve is used to extract the blade polishing area curve and generate the polishing trajectory data points. Then, two methods of rigid trajectory planning and flexible adaptive trajectory planning of abrasive cloth wheel are simulated and analyzed by offline programming software. Finally, experiments were carried out on a four-station wheel changing polishing platform. Simulation and experiments results show that the proposed flexible adaptive trajectory planning method can make the surface roughness of the convex and the concave, the surface roughness of the leading and trailing edge, the total polishing efficiency increased by about 9.4%.

show abstract

“…As a kind of precision machining technology, belt grinding is widely used for the grinding of free-form surfaces in aerospace and naval ships area [1][2][3]. With the successive development of industrial field and the continuous improvement of machining precision and surface quality requirements for parts, the requirements of abrasive belt grinding accuracy are also higher and higher [4][5]. The precision of grinding process depends on the precise material removal model which are usually affected by many factors, such as grinding parameters, workpiece parameters and abrasive belt wear status [6].…”

Section: Introductionmentioning

confidence: 99%

A Novel Monitoring Method for Belt Wear State Based on Machine Vision and Image-processing Under Varying Grinding Parameters

Wang¹,

Zhang²,

Ren³

et al. 2021

Preprint

View full text Add to dashboard Cite

The wear state of abrasive belt is one of the important factors affecting the grinding precision of belt grinding processes. Accurate monitoring of abrasive belt wear can not only provide the basis for accurate material removal model to improve grinding accuracy, but also can replace the belt to avoid surface burn in time. However, most of the existing abrasive belt wear monitoring methods are only suitable for monitoring the belt wear state under specific grinding parameters, are not universal. This paper introduces a method of belt wear state monitoring based on machine vision and image-processing. All the surface images of the belt were obtained from the new belt to the worn-out of the belt by a non-contact electron microscope. The features of abrasive belt surface images are extracted from RGB color space and wavelet texture. By analyzing the trendency of the extracted features in the whole grinding process, the wear state is divided into three categories. Three image features related to the wear state are selected: the first order distance of color component R, the entropy of horizontal subgraph, and vertical subgraph of texture feature. Based on the selected features and the random forest classification algorithm, the wear state classifier of abrasive belt is established. The performance of the classifier is verified and evaluated by using the data subset of different images. The results show that the proposed method has high recognition accuracy for the belt wear state, and the accuracy can reach 99% in the accelerated wear stage. The proposed method is suitable for the monitoring of the belt wear state by the surface images of the abrasive belt measured under different grinding parameters and different measurement parameters.

show abstract

An adaptive trajectory planning algorithm for robotic belt grinding of blade leading and trailing edges based on material removal profile model

Cited by 86 publications

References 35 publications

Experimental and numerical study on surface generated mechanism of robotic belt grinding process considering the dynamic deformation of elastic contact wheel

Experimental and numerical study on surface generated mechanism of robotic belt grinding process considering the dynamic deformation of elastic contact wheel

Trajectory Planning of Robot-assisted Abrasive Cloth Wheel Polishing Blade based on Flexible Contact

A Novel Monitoring Method for Belt Wear State Based on Machine Vision and Image-processing Under Varying Grinding Parameters

Contact Info

Product

Resources

About