On-Line Grinding Chatter Detection Based on Minimum Entropy Deconvolution and Autocorrelation Function

2021 ◽  
Author(s):  
Dan He ◽  
Zexing Ni ◽  
Xiufeng Wang
Keyword(s):  
Autocorrelation Function ◽  
Line Detection ◽  
Detection Accuracy ◽  
Minimum Entropy ◽  
Chatter Detection ◽  
Vibration Signals ◽  
Grinding Chatter ◽  
Grinding Conditions ◽  
On Line ◽  
Periodic Impulse

Abstract On-line detection of chatter is one of the key techniques to avoid the harmful effects caused by chatter in grinding process. The key to chatter detection is to capture reliable chatter features and thresholds. To achieve this, it is important to make clear and extract the essential characteristics of the grinding chatter signal, which has not yet been well studied. In this paper, we are going to investigate the essential characteristics of the grinding chatter signal and propose a new approach for on-line detection of grinding chatter. The proposed approach for on-line detection of grinding chatter is based on minimum entropy deconvolution and autocorrelation function, in which the minimum entropy deconvolution is employed to deconvolve the effect of transmission path, and further to restore the essential characteristics of the chatter signals. To eliminate the interference of the non-periodic impulse signals in the measured vibration signals, an autocorrelation function is introduced. Kurtosis is employed to indicate chatter according to the changes of the processed signal. The validity of the proposed method is demonstrated through the measured vibration signals obtained from grinding processes and the presented chatter detection index is independent from the grinding conditions with excellent detection accuracy and permissible computational efficiency. This demonstrates the effectiveness of proposed method in on-line implementation.

On-Line Chatter Detection Using Wavelet-Based Parameter Estimation

2000 ◽  
Author(s):  
Taejun Choi ◽  
Yung C. Shin
Keyword(s):  
Parameter Estimation ◽  
Estimation Algorithm ◽  
Cutting Process ◽  
High Dimensional ◽  
Detection Accuracy ◽  
Chatter Detection ◽  
Ml Estimation ◽  
On Line ◽  
Low Dimensional ◽  
Low Dimensional Dynamics

Abstract A new method for on-line chatter detection is presented. The proposed method characterizes the significant transition from high dimensional to low dimensional dynamics in the cutting process at the onset of chatter. Based on the likeness of the cutting process to the nearly-1/f process, this wavelet-based maximum likelihood (ML) estimation algorithm is applied for on-line chatter detection. The presented chatter detection index γ is independent of the cutting conditions and gives excellent detection accuracy and permissible computational efficiency, which makes it suitable for on-line implementation. The validity of the proposed method is demonstrated through the tests with extensive actual data obtained from turning and milling processes.

On-Line Detection Method for Automobile Frame Side Rail Process Holes

2012 ◽  
Vol 616-618 ◽  
pp. 1993-1996
Author(s):  
Yu Zhuo Men ◽  
Hai Bo Yu ◽  
Hua Wang ◽  
Jin Gang Gao ◽  
Xin Pan
Keyword(s):  
Machine Vision ◽  
Detection Method ◽  
Detection System ◽  
Ccd Camera ◽  
Line Detection ◽  
Detection Accuracy ◽  
Side Rail ◽  
On Line ◽  
System Prototype

On-line detection method for automobile frame side rail process holes is proposed in this articled. It is achieved by virtue of machine vision technology detection method. Many images captured by CCD camera are processed and analyzed to finally complete the automatic detection of automobile chassis frame process holes. Machine vision technology is applied to achieve the on-line detection of machining quality of frame side rail mounting holes. The developed detection system prototype has very high detection accuracy.

On-Line Chatter Detection Using Wavelet-Based Parameter Estimation

2003 ◽  
Vol 125 (1) ◽  
pp. 21-28 ◽  
Author(s):  
Taejun Choi ◽  
Yung C. Shin
Keyword(s):  
Parameter Estimation ◽  
Estimation Algorithm ◽  
High Dimensional ◽  
Detection Accuracy ◽  
Chatter Detection ◽  
Ml Estimation ◽  
Fractal Patterns ◽  
On Line ◽  
Low Dimensional ◽  
Low Dimensional Dynamics

A new method for on-line chatter detection is presented. The proposed method characterizes the significant transition from high dimensional to low dimensional dynamics in the cutting process at the onset of chatter. Based on the observation that cutting signals contain fractal patterns, a wavelet-based maximum likelihood (ML) estimation algorithm is applied to on-line chatter detection. The presented chatter detection index γ is independent of the cutting conditions and gives excellent detection accuracy and permissible computational efficiency, which makes it suitable for on-line implementation. The validity of the proposed method is demonstrated through the tests with extensive actual data obtained from turning and milling processes.

Printing Defects Detection Based on Two-Times Difference Image Method

2013 ◽  
Vol 340 ◽  
pp. 512-516 ◽  
Author(s):  
Yan Yan Guan ◽  
Yi Cheng Ye
Keyword(s):  
Threshold Value ◽  
Line Detection ◽  
Image Method ◽  
Detection Accuracy ◽  
False Detection ◽  
Difference Image ◽  
Printing Quality ◽  
Template Image ◽  
On Line ◽  
Standard Template

With an aim at printing quality on-line detection, a method based on two-times difference image algorithm was proposed. Firstly, a standard template image and a gray threshold value image were calculated by using statistical methods. Secondly, an abnormal spots image was obtained through two-times difference image of the detection image, the standard template image and gray threshold value image. Lastly, the defects can be detected by analysis of connected region of the abnormal spots image. The results demonstrated that the problems of false detection and omission detection due to edge of image can be solved effectively, and the detection accuracy can be improved through this method.

Research on the Impact of CNC Servo Dynamic Characteristic for the On-Line Detection Precision

2014 ◽  
Vol 511-512 ◽  
pp. 286-289
Author(s):  
Cheng Rong Pian ◽  
Qing Zhang ◽  
Nan Wu
Keyword(s):  
Dynamic Characteristic ◽  
Error Model ◽  
Cnc Machining ◽  
Machining Process ◽  
Cnc Machine Tools ◽  
Line Detection ◽  
Detection Accuracy ◽  
Cnc Machine ◽  
On Line ◽  
The Impact

CNC machine tools are widely used in precision machining and automation production. The on-line detection technology provides an efficient testing method for quality control in CNC machining process. And the CNC servo dynamic characteristic is an important factor affecting the accuracy of on-line detection. In order to study the effects of servo dynamic characteristic, CNC servo system mathematical model was set up, probe system error model was established based on probe measuring time sequence and on-line detection error model was built. The cylindrical feature measurement example shows that on-line detection accuracy is improved through the secondary trigger measurement method and the probe path planning.

A Model Based Computationally Efficient Method for On-Line Detection of Chatter in Milling

2013 ◽  
Author(s):  
Lei Ma ◽  
Shreyes Melkote ◽  
James Castle
Keyword(s):  
Efficient Method ◽  
Chip Thickness ◽  
Line Detection ◽  
Chatter Detection ◽  
Computationally Efficient ◽  
Model Based ◽  
Force Signal ◽  
On Line ◽  
Regeneration Effect ◽  
Milling Chatter

This paper presents a model-based computationally efficient method for detecting milling chatter in its incipient stages. Based on a complex exponentials model for the dynamic chip thickness, the chip regeneration effect is amplified and isolated from the cutting force signal for early chatter detection. The proposed method is independent of the cutting conditions. With the aid of a one tap adaptive filter, the proposed method is also found to be able to distinguish between chatter and the dynamic transients in the cutting forces due to sudden changes in workpiece geometry and tool entry/exit. The proposed method is experimentally validated.

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