Diffraction pattern analysis for real time monitoring of tool wear in turning processes

2009 ◽  
Vol 2 (5/6) ◽  
pp. 515
Author(s):  
A.A.G. Bruzzone ◽  
P.M. Lonardo ◽  
A. Traverso
Keyword(s):  
Tool Wear ◽  
Diffraction Pattern ◽  
Real Time ◽  
Pattern Analysis ◽  
Real Time Monitoring

scholarly journals Research on a Real-Time Monitoring Method for the Wear State of a Tool Based on a Convolutional Bidirectional LSTM Model

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1233 ◽  
Author(s):  
Chen ◽  
Xie ◽  
Yuan ◽  
Huang ◽  
Li
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Tool Wear ◽  
Real Time ◽  
Original Data ◽  
Attention Mechanism ◽  
Cnc Machining ◽  
Numerical Control ◽  
Real Time Monitoring ◽  
Monitoring Method

To monitor the tool wear state of computerized numerical control (CNC) machining equipment in real time in a manufacturing workshop, this paper proposes a real-time monitoring method based on a fusion of a convolutional neural network (CNN) and a bidirectional long short-term memory (BiLSTM) network with an attention mechanism (CABLSTM). In this method, the CNN is used to extract deep features from the time-series signal as an input, and then the BiLSTM network with a symmetric structure is constructed to learn the time-series information between the feature vectors. The attention mechanism is introduced to self-adaptively perceive the network weights associated with the classification results of the wear state and distribute the weights reasonably. Finally, the signal features of different weights are sent to a Softmax classifier to classify the tool wear state. In addition, a data acquisition experiment platform is developed with a high-precision CNC milling machine and an acceleration sensor to collect the vibration signals generated during tool processing in real time. The original data are directly fed into the depth neural network of the model for analysis, which avoids the complexity and limitations caused by a manual feature extraction. The experimental results show that, compared with other deep learning neural networks and traditional machine learning network models, the model can predict the tool wear state accurately in real time from original data collected by sensors, and the recognition accuracy and generalization have been improved to a certain extent.

On-line diffraction pattern analysis and phase identification using a JEM 2000FX AEM with a macintosh-based program

1994 ◽  
Vol 52 ◽  
pp. 1006-1007
Author(s):  
C. R. Hills ◽  
G. A. Poulter
Keyword(s):  
Electron Diffraction ◽  
Diffraction Pattern ◽  
Real Time ◽  
Pattern Analysis ◽  
Reciprocal Lattice ◽  
Computer Software ◽  
Crystallographic Analysis ◽  
Lattice Points ◽  
Phase Identification ◽  
Reciprocal Lattice Point

A number of computer programs have been written to aid in the indexing of transmission electron diffraction pattcrns. These programs are useful for determining crystallographic orientation and for phase identification and often simplify the analysis of complex patterns. Over the last few years there has been a trend toward automated electron microscopy. It is natural to extend this automation to real time diffraction pattern analysis and phase identification using A/D data acquisition boards and computer software to interface the modern AEM with an electron diffraction database (EDD). This paper describes a real-time Macintosh-based system (hardware and software) for automated electron diffraction pattern analysis and phase identification developed for the JEM 2000FX AEM. Crystallographic analysis with this system is attractive because of the rapid analysis time, ease of implementation, and it is inexpensive compared to buying a digitizing board and video system.Computer-aided diffraction pattern-indexing programs typically require the user to input reciprocal lattice point spacings (r-spacings) and the interplanar angle measurements for at least three non-colinear lattice points in the pattern. It is also necessary to know the crystal structure and lattice constants of the sample.

scholarly journals Dynamics Pattern Analysis of Paddy Fields in Indonesia for Developing a Near Real-time Monitoring System Using MODIS Satellite Images

2016 ◽  
Vol 33 ◽  
pp. 108-116 ◽  
Author(s):  
Yudi Setiawan ◽  
Liyantono ◽  
Alvin Fatikhunnada ◽  
Prita Ayu Permatasari ◽  
Muhammad Rizky Aulia
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Satellite Images ◽  
Pattern Analysis ◽  
Paddy Fields ◽  
Real Time Monitoring ◽  
Modis Satellite Images

An Interactive Minicomputer Program for the Indexing and Simulation of Electron Diffraction Patterns

1976 ◽  
Vol 34 ◽  
pp. 542-543
Author(s):  
R.P. Goehner ◽  
W.T. Hatfield ◽  
Prakash Rao
Keyword(s):  
Electron Diffraction ◽  
Real Time ◽  
Pattern Analysis ◽  
Flow Diagram ◽  
Hard Copy ◽  
Time Analysis ◽  
Real Time Analysis ◽  
Transmission Electron ◽  
One Step ◽  
Diffraction Patterns

Computer programs are now available in various laboratories for the indexing and simulation of transmission electron diffraction patterns. Although these programs address themselves to the solution of various aspects of the indexing and simulation process, the ultimate goal is to perform real time diffraction pattern analysis directly off of the imaging screen of the transmission electron microscope. The program to be described in this paper represents one step prior to real time analysis. It involves the combination of two programs, described in an earlier paper(l), into a single program for use on an interactive basis with a minicomputer. In our case, the minicomputer is an INTERDATA 70 equipped with a Tektronix 4010-1 graphical display terminal and hard copy unit.A simplified flow diagram of the combined program, written in Fortran IV, is shown in Figure 1. It consists of two programs INDEX and TEDP which index and simulate electron diffraction patterns respectively. The user has the option of choosing either the indexing or simulating aspects of the combined program.

1618: Real-Time Monitoring of Nitric Oxide and Blood Flow During Ischemia-Reperfusion in the Rat Testis

2006 ◽  
Vol 175 (4S) ◽  
pp. 521-521
Author(s):  
Motoaki Saito ◽  
Tomoharu Kono ◽  
Yukako Kinoshita ◽  
Itaru Satoh ◽  
Keisuke Satoh
Keyword(s):  
Nitric Oxide ◽  
Blood Flow ◽  
Real Time ◽  
Ischemia Reperfusion ◽  
Real Time Monitoring ◽  
Rat Testis
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