Constant Cutting Force Control for CNC Machining Using Dynamic Characteristic-Based Fuzzy Controller

Liu, Hengli; Wang, Tao; Wang, Dong

doi:10.1155/2015/406294

Cited by 8 publications

(4 citation statements)

References 19 publications

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“…Then, the on-line optimization cutting is carried out adapting the off-line optimal results according to the method in reference. 20 According to the actual situation of the processing platform, in order to protect the machine tool, cutting tool and workpiece, the allowable maximum current value is set at 8 A . Taking the change of cutting depth as the variable factor, the off-line and on-line optimization system is adopted to carry out the processing experiment.…”

Section: Experimental Verificationmentioning

confidence: 99%

Application of combined optimization strategy and system of CNC machining parameter

Liu

Wang

Dong

2022

Advances in Mechanical Engineering

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This paper presents an efficient optimization method of combining off-line optimization with on-line adaptive control for CNC (Computerized Numerical Control) machining parameter, and develops the corresponding system, aims to multi-objective optimization and cutting force stability. Firstly, the multi-objective optimization solution of machining parameters is obtained by off-line optimization based on Pareto genetic algorithm and TRIZ theory. Then, on this basis, feed speed is adjusted online based on adaptive control system. Next, current is used as feedback to control cutting force, and cutting force can be kept at a set value by the on-line adjusting. We obtain the relationship between off-line optimization and on-line adaptive control. Finally, we build the combined optimization module and embed the self-developed CNC machining system. Based on the system, the experimental results verify that the optimized process parameters make the processing time reduced by 14 s, and no matter how cutting conditions change, cutting force can be stabilized as soon as possible by adjusting feed speed online for keeping the cutting process stability. From the perspective of building the parameter optimization function module, it provides a new idea for the self-development of CNC machining system.

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Section: Experimental Verificationmentioning

confidence: 99%

Application of combined optimization strategy and system of CNC machining parameter

Liu

Wang

Dong

2022

Advances in Mechanical Engineering

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“…For example, a fuzzy adaptive control algorithm is applied in [4] with instant cutting force and vibration data. In [5], a dynamic characteristic-based fuzzy adaptive control algorithm is presented to avoid the influence of cutting force's variation, where the cutting force is indirectly evaluated in real-time by monitoring the motorized spindle current. This kind of online optimization approaches must have additional setup attached to each CNC machine and the cost of such setup is high.…”

Section: B Related Workmentioning

confidence: 99%

Progressive segmentation for MRR-based feed-rate optimization in CNC machining

Chan

Wang

2015

2015 IEEE International Conference on Automation Science and Engineering (CASE)

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Keeping a constant cutting force in CNC machining is very important for obtaining better stability of cutting operation and improving topography, texture and geometry of the machined surface. This paper presents a feed-rate optimization approach based on Material Removal Rate (MRR). Given a tool-path with predefined feed-rates, the geometry of raw material, and the shape of cutter, the histogram of MRR in very fine resolution can be efficiently computed by using a GPU-based geometric modeling kernel. Starting from the evaluation given on the finest histogram of MRR, errorcontrolled subdivision algorithms are developed to progressively segment the tool-path into user-specified number of sub-regions. Different feed-rates are assigned to different sub-regions so that nearly constant MRR can be achieved while keeping the shape of the given tool-path unchanged. Experimental tests taken on real examples verify the effectiveness of this method.

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“…A number of real-time control systems have been developed by researchers using various approaches to control the cutting force, such as model-based control, 7,14,15 fuzzy logic control, 16–18 and neural network control. 8,19,20 Compared with other cutting processes, more factors affect the cutting force of gear hobbing.…”

Section: Introductionmentioning

confidence: 99%

“…The spindle torque signal is the characteristic signal of the cutting force and has been widely used in cutting force monitoring. 16,22,23 Moreover, the signal is provided by most numerical control systems. Therefore, it is the suitable signal to be used as the feedback signal for cutting force control.…”

Section: Introductionmentioning

confidence: 99%

High-efficiency gear hobbing technics based on fuzzy adaptive control of spindle torque

Liu

Zhao

Mei

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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In this paper, the problem of relatively low efficiency of the current gear hobbing process is addressed through fuzzy adaptive control of the cutting force. The paper studies the influencing factors of the cutting torque of gear hobbing, and the relationship between the feed rate and the cutting torque is established. Based on the relationship and the fuzzy adaptive control method, a high efficiency gear hobbing method is designed. A methodology using the static spindle torque rather than the dynamic one as the feedback signal of the fuzzy controller is also presented, which can deal with the severe cutting torque fluctuations during gear hobbing. The input and the output scaling factors of the fuzzy controller can also be tuned online to adapt to different types of gears or various cutting conditions. The key issue of determining the reference value of the spindle torque is also resolved through analysis of the spindle torque data in a trial cut. The proposed method is simulated and implemented on a numerical control gear hobbing machine, which cuts spur gears and helical gears. The simulation and experimental results are in a good consistency. The efficiency is improved considerably, which saves as high as 40% and 30% cutting time of the gear hobbing process in the first and second set of experiments, respectively.

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Constant Cutting Force Control for CNC Machining Using Dynamic Characteristic-Based Fuzzy Controller

Cited by 8 publications

References 19 publications

Application of combined optimization strategy and system of CNC machining parameter

Application of combined optimization strategy and system of CNC machining parameter

Progressive segmentation for MRR-based feed-rate optimization in CNC machining

High-efficiency gear hobbing technics based on fuzzy adaptive control of spindle torque

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