Research on Modeling Mapping Relationship between Cutting Load and Spindle Motor Current

2011 ◽  
Vol 305 ◽  
pp. 353-356
Author(s):  
Xi Li ◽  
Dan Feng Feng
Keyword(s):  
Intelligent Control ◽  
Spindle Motor ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Intelligent Control System ◽  
Motor Current ◽  
Spindle Motor Current ◽  
Identification Theory ◽  
The Relationship ◽  
Spindle Current

The relationship between cutting load and motor current of CNC machine tools is an important part for research in intelligent control system. In this paper, the process of processing the error spindle current signal averaging, filtering, signal preprocessing, At the base of feature analysis and extraction, using system identification theory get the mapping model from current of the spindle to cutting load. Finally, the actual cutting data used to verify the model is reasonable.

The Achievement of Intelligent Lubrication Adjustment Function of CNC Machine Tools Based on SSAS

2014 ◽  
Vol 556-562 ◽  
pp. 1454-1459
Author(s):  
Dong Sheng You
Keyword(s):  
Machine Tools ◽  
Sensor Data ◽  
Lubricating Oil ◽  
Cnc Machine Tools ◽  
Signal Acquisition ◽  
Cnc Machine ◽  
Lubrication Mode ◽  
Free Function ◽  
And Control ◽  
The Relationship

The use of CNC machine tools signal acquisition, two-way transmission of the temperature sensor data, the ladder design and macro program guide and other methods on the implementation of a temperature sensing system of smart lubrication function. It is not only low-end CNC machine tools can compensate for deficiencies in equipment protection features and maintenance-free function, but also enhance the diversity of processing. Ultimately by analyzing the different lubrication mode, the relationship between the lubricating oil pressure and temperature and other factors, to draw the function in the lubrication in a stabilizing effect on oil pressure and control bearings and nut seat temperature. It is simple and practical, has important theoretical significance and great value.

Digital twin of the chip formation process

2020 ◽  
pp. 81-86
Author(s):  
Yu.G. Kabaldin ◽  
D.A. Shatagin ◽  
M.S. Anosov ◽  
A.M. Kuz'mishina
Keyword(s):  
Neural Network ◽  
Control System ◽  
Crystal Lattice ◽  
Network Model ◽  
Intelligent Control ◽  
Neural Network Model ◽  
Formation Process ◽  
Chip Formation ◽  
Intelligent Control System ◽  
The Relationship

The formation of chips during the processing of various materials was studied. The relationship between the type of chips, the type of crystal lattice of the material and the number of sliding systems is shown. A neural network model of chip formation is developed, which allows predicting the type of chips. An intelligent control system for the process of chip formation during cutting is proposed. Keywords: chip formation, crystal lattice, neural network model, type of chips. [email protected]

Experimental Assessment of Effect of Backlash Control Parameters on Quadrant Protrusions of Circular Tests for CNC Machine Tools

2020 ◽  
Vol 19 (01) ◽  
pp. 65-85
Author(s):  
Chuan-Hsun Hsu ◽  
Chi-Hsiang Wang ◽  
Syh-Shiuh Yeh
Keyword(s):  
Machine Tool ◽  
Feed Rate ◽  
Machine Tools ◽  
Search Algorithm ◽  
Cnc Machine Tools ◽  
Control Parameters ◽  
Cnc Machine ◽  
Circular Test ◽  
Binary Search Algorithm ◽  
The Relationship

Backlash, friction, and servo lag factors often result in protrusion or segment difference phenomenon in the moving speed reversal of a machine tool’s moving table. This phenomenon can be improved by adjusting the backlash control parameters of the machine tool controller, but the control parameters must vary with the feed rate and payload of the moving table. Therefore, this study performed the circular test process for CNC machine tools, and used different feed rate, radius, and payload motion conditions to discuss the effect of backlash control parameters on quadrant protrusions. First, this study used parameter-range reduction combined with the Taguchi method and the binary search algorithm to search for the optimal backlash control parameters in the parameter setting range, so that the machine tool could have preferable quadrant protrusion performance when executing circular tests. Afterward, the correlation of the moving table feed rate, radius, and payload to the quadrant protrusion was analyzed according to the experimental results. The results indicated that the machine tool moving table feed rate had the most apparent effect on quadrant protrusions, and the relationship between the payload and quadrant protrusion was influenced by the moving table feed rate and circular radius simultaneously.

Monitoring Cutting Forces In Turning: A Model-Based Approach

2000 ◽  
Vol 124 (1) ◽  
pp. 26-31 ◽  
Author(s):  
Jeffrey L. Stein ◽  
Kunsoo Huh
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
Spindle Motor ◽  
Turning Process ◽  
Motor Current ◽  
Model Based ◽  
Cnc Lathe ◽  
Spindle Motor Current ◽  
Force Monitoring

The importance of monitoring the cutting force in the turning process has been well recognized in industry as well as in the open literature. This paper proposes a cutting force monitoring approach that does not utilize force dynamometers but rather estimates the cutting force based on the spindle motor current and speed as well as a model that relates these measurements to the cutting force. Motor current and speed can not only be inexpensively and reliably measured but, in addition, can be shown, along with the properly chosen model for the model-based estimator, to accurately estimate the cutting force. This method is demonstrated on a CNC lathe and its advantages and limitations are discussed.

Face Milling Tool Wear Condition Monitoring Based on Wavelet Transform and Shannon Entropy

2014 ◽  
Vol 541-542 ◽  
pp. 1419-1423 ◽  
Author(s):  
Min Zhang ◽  
Hong Qi Liu ◽  
Bin Li
Keyword(s):  
Wavelet Transform ◽  
Tool Wear ◽  
Condition Monitoring ◽  
Shannon Entropy ◽  
Spindle Motor ◽  
Face Milling ◽  
Motor Current ◽  
Milling Tool ◽  
Spindle Motor Current ◽  
Wear Condition

Tool condition monitoring is an important issue in the advanced machining process. Existing methods of tool wear monitoring is hardly suitable for mass production of cutting parameters fluctuation. In this paper, a new method for milling tool wear condition monitoring base on tunable Q-factor wavelet transform and Shannon entropy is presented. Spindle motor current signals were recorded during the face milling process. The wavelet energy entropy of the current signals carries information about the change of energy distribution associated with different tool wear conditions. Experiment results showed that the new method could successfully extract significant signature from the spindle-motor current signals to effectively estimate tool wear condition during face milling.

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