Compensation Control of Cutting Tool Position in Machining Non-Axisymmetric Optic Mirror Surface

2006 ◽  
Vol 505-507 ◽  
pp. 181-186
Author(s):  
Yuan Liang Zhang ◽  
Zhi Min Zhou ◽  
Xu Zhang
Keyword(s):  
Nonlinear Response ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Mirror Surface ◽  
Maximum Displacement ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Compensation Control ◽  
Servo Mechanism ◽  
Tool Position

Piezoelectric servo mechanism, with its existing nonlinear response and hysteresis, restricts the precision greatly when applied to manufacturing of non-axisymmetric optic mirror. On the basis of theory analysis and experiments, this paper builds three kinds of feed-forward model of piezoelectric servo cutting system. According to these mathematical models, we make the compensation control to the cutting tool position, which results the maximum displacement error less than 0.04μm. And based on this method, experiments on machining non-axisymmetric optic surface of wave front corrector shows the Zernike relative error is less than 10%. So the compensation control of feed-forward control model of cutting tools position can efficiently counteract the influence of nonlinear response and hysteresis, which improves machining precision of non-axisymmetric optic mirror surface.

scholarly journals Model-based feed-forward control for time-varying systems with an example for SRF cavities

2020 ◽  
Vol 53 (2) ◽  
pp. 1331-1336
Author(s):  
Sven Pfeiffer ◽  
Annika Eichler ◽  
Holger Schlarb
Keyword(s):  
Time Varying ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Model Based ◽  
Time Varying Systems ◽  
Srf Cavities

scholarly journals Evaluation of Cutting-Tool Coating on the Surface Roughness and Hole Dimensional Tolerances during Drilling of Al6061-T651 Alloy

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1783
Author(s):  
Hamza A. Al-Tameemi ◽  
Thamir Al-Dulaimi ◽  
Michael Oluwatobiloba Awe ◽  
Shubham Sharma ◽  
Danil Yurievich Pimenov ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Good Practice ◽  
Cutting Tools ◽  
Statistical Design ◽  
Cutting Parameters ◽  
Statistical Design Of Experiments ◽  
Hole Quality ◽  
Coated Tools ◽  
Tool Coating

Aluminum alloys are soft and have low melting temperatures; therefore, machining them often results in cut material fusing to the cutting tool due to heat and friction, and thus lowering the hole quality. A good practice is to use coated cutting tools to overcome such issues and maintain good hole quality. Therefore, the current study investigates the effect of cutting parameters (spindle speed and feed rate) and three types of cutting-tool coating (TiN/TiAlN, TiAlN, and TiN) on the surface finish, form, and dimensional tolerances of holes drilled in Al6061-T651 alloy. The study employed statistical design of experiments and ANOVA (analysis of variance) to evaluate the contribution of each of the input parameters on the measured hole-quality outputs (surface-roughness metrics Ra and Rz, hole size, circularity, perpendicularity, and cylindricity). The highest surface roughness occurred when using TiN-coated tools. All holes in this study were oversized regardless of the tool coating or cutting parameters used. TiN tools, which have a lower coating hardness, gave lower hole circularity at the entry and higher cylindricity, while TiN/TiAlN and TiAlN seemed to be more effective in reducing hole particularity when drilling at higher spindle speeds. Finally, optical microscopes revealed that a built-up edge and adhesions were most likely to form on TiN-coated tools due to TiN’s chemical affinity and low oxidation temperature compared to the TiN/TiAlN and TiAlN coatings.

scholarly journals Remaining Useful Life Prediction of Cutting Tools Using an Inverse Gaussian Process Model

2021 ◽  
Vol 11 (11) ◽  
pp. 5011
Author(s):  
Yuanxing Huang ◽  
Zhiyuan Lu ◽  
Wei Dai ◽  
Weifang Zhang ◽  
Bin Wang
Keyword(s):  
Surface Roughness ◽  
Failure Criterion ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Remaining Useful Life ◽  
Model Parameters ◽  
Inverse Gaussian ◽  
Wear Process ◽  
Useful Life ◽  
Dynamic Wear

In manufacturing, cutting tools gradually wear out during the cutting process and decrease in cutting precision. A cutting tool has to be replaced if its degradation exceeds a certain threshold, which is determined by the required cutting precision. To effectively schedule production and maintenance actions, it is vital to model the wear process of cutting tools and predict their remaining useful life (RUL). However, it is difficult to determine the RUL of cutting tools with cutting precision as a failure criterion, as cutting precision is not directly measurable. This paper proposed a RUL prediction method for a cutting tool, developed based on a degradation model, with the roughness of the cutting surface as a failure criterion. The surface roughness was linked to the wearing process of a cutting tool through a random threshold, and accounts for the impact of the dynamic working environment and variable materials of working pieces. The wear process is modeled using a random-effects inverse Gaussian (IG) process. The degradation rate is assumed to be unit-specific, considering the dynamic wear mechanism and a heterogeneous population. To adaptively update the model parameters for online RUL prediction, an expectation–maximization (EM) algorithm has been developed. The proposed method is illustrated using an example study. The experiments were performed on specimens of 7109 aluminum alloy by milling in the normalized state. The results reveal that the proposed method effectively evaluates the RUL of cutting tools according to the specified surface roughness, therefore improving cutting quality and efficiency.

Flatness Feed-Forward Control Model Based on Neural Networks

2014 ◽  
Vol 989-994 ◽  
pp. 3386-3389
Author(s):  
Zhu Wen Yan ◽  
Hen An Bu ◽  
Dian Hua Zhang ◽  
Jie Sun
Keyword(s):  
Neural Networks ◽  
Rolling Mill ◽  
Rolling Force ◽  
Work Roll ◽  
Control Model ◽  
Good Effect ◽  
Feed Forward ◽  
Force Fluctuations ◽  
Feed Forward Control ◽  
Roll Bending

The influence on the shape of the strip from rolling force fluctuations has been analyzed. The combination of intermediate roll bending and work roll bending has been adopted. The principle of rolling force feed-forward control has been analyzed. The feed-forward control model has been established on the basis of neural networks. The model has been successfully applied to a rolling mill and a good effect has been achieved.

scholarly journals Feed-forward control of preshaping in the rat is mediated by the corticospinal tract

2010 ◽  
Vol 32 (10) ◽  
pp. 1678-1685 ◽  
Author(s):  
Jason B. Carmel ◽  
Sangsoo Kim ◽  
Marcel Brus-Ramer ◽  
John H. Martin
Keyword(s):  
Corticospinal Tract ◽  
Feed Forward ◽  
Feed Forward Control
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