On-Line Detection of Drill Wear

1990 ◽  
Vol 112 (3) ◽  
pp. 299-302 ◽  
Author(s):  
T. I. Liu ◽  
S. M. Wu
Keyword(s):  
Prediction Model ◽  
Flank Wear ◽  
Vision System ◽  
Line Detection ◽  
Wear Area ◽  
Line System ◽  
Fusion Strategy ◽  
Linear Classifier ◽  
On Line ◽  
Percent Success

An on-line system for drill wear detection has been developed by using a sensor fusion strategy. Both acceleration and thrust signals were analyzed. Flank wear area was used to evaluate drill wear states. The drill wear area was measured by a vision system and classified into two groups: usable and worn-out. The wear prediction model was obtained by a two-category linear classifier. On-line detection tests indicate that the prediction model has over a 90 percent success rate.

On-Line Flank Wear Estimation Using an Adaptive Observer and Computer Vision, Part 2: Experiment

1993 ◽  
Vol 115 (1) ◽  
pp. 37-43 ◽  
Author(s):  
Jong-Jin Park ◽  
A. Galip Ulsoy
Keyword(s):  
Computer Vision ◽  
Flank Wear ◽  
Vision System ◽  
Adaptive Observer ◽  
Cutting Conditions ◽  
Model Parameters ◽  
Computer Vision System ◽  
Integrated Method ◽  
On Line ◽  
The Difference

An on-line flank wear estimation system, using the integrated method presented in Part 1 of the paper, is implemented in a laboratory environment, and its performance is evaluated through turning experiments. A computer vision system is developed using an image processing algorithm, a commercially available computer vision system, and a microscopic lens. The developed algorithm is based on the difference between the intensity of the reflected light from a flank wear surface and that from the background. The difference is very significant and an appropriate selection of the intensity threshold level yields an acceptable binary image of the flank wear. This image is used by the vision computer for the calculation of the flank wear. The flank wear model parameters that need to be known a priori are determined through several preliminary experiments, or from data available in the literature. Cutting conditions are selected to satisfy the assumptions made on the design of the adaptive observer presented in Part 1. The resulting cutting conditions are typical of those used in finishing cutting operations. The integrated method is tested in turning experiments under both constant and time varying cutting conditions, and yields very accurate on-line estimation of the flank wear development.

On line detection of defective apples using computer vision system combined with deep learning methods

2020 ◽  
Vol 286 ◽  
pp. 110102 ◽  
Author(s):  
Shuxiang Fan ◽  
Jiangbo Li ◽  
Yunhe Zhang ◽  
Xi Tian ◽  
Qingyan Wang ◽  
...  
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Line Detection ◽  
Computer Vision System ◽  
Learning Methods ◽  
On Line

Development of Glucose On-line Detection System for Fermentation Process

2013 ◽  
Vol 40 (12) ◽  
pp. 1945-1949
Author(s):  
Xue-Jin GAO ◽  
Guang-Sheng LIU ◽  
Li CHENG ◽  
Ling-Xiao GENG ◽  
Ji-Xing XUE ◽  
...  
Keyword(s):  
Fermentation Process ◽  
Detection System ◽  
Line Detection ◽  
On Line

Research Situation Analysis of On-line Detection Technology for Power Transformer Winding Deformation

2020 ◽  
Vol 13 (6) ◽  
pp. 823-832
Author(s):  
Zhenhua Li ◽  
Weihui Jiang ◽  
Li Qiu ◽  
Zhenxing Li ◽  
Yanchun Xu
Keyword(s):  
Detection Method ◽  
Theoretical Research ◽  
Line Detection ◽  
Response Analysis ◽  
Advantages And Disadvantages ◽  
Detection Technology ◽  
The Future ◽  
Transformer Winding ◽  
On Line ◽  
Winding Deformation

Background: Winding deformation is one of the most common faults in power transformers, which seriously threatens the safe operation of transformers. In order to discover the hidden trouble of transformer in time, it is of great significance to actively carry out the research of transformer winding deformation detection technology. Methods: In this paper, several methods of winding deformation detection with on-line detection prospects are summarized. The principles and characteristics of each method are analyzed, and the advantages and disadvantages of each method as well as the future research directions are expounded. Finally, aiming at the existing problems, the development direction of detection method for winding deformation in the future is prospected. Results: The on-line frequency response analysis method is still immature, and the vibration detection method is still in the theoretical research stage. Conclusion: The ΔV − I1 locus method provides a new direction for on-line detection of transformer winding deformation faults, which has certain application prospects and practical engineering value.

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