The Manipulator Tool Fault Diagnostics Based on Vibration Analysis in the Frequency Domain

2016 ◽  
Vol 817 ◽  
pp. 234-244 ◽  
Author(s):  
Piotr Gierlak ◽  
Marcin Szuster
Keyword(s):  
Neural Networks ◽  
Vibration Analysis ◽  
Cutting Tool ◽  
Measurement Data ◽  
Current Control ◽  
Ceramic Fiber ◽  
Fiber Breakage ◽  
Time Saving ◽  
High Effectiveness ◽  
Vibratory Motion

The issues presented in the article, relate to the detection of damage of a cutting tool used in robotised machining. Due to the time saving requirements, it is desirable to carry out the current control of the tool mounted in the holder of the robotic manipulator. The tool is a ceramic fiber brush used for grinding. A typical damage of the brush is fiber breakage, which leads to an unbalance of the tool and vibrations. The phenomenon of vibrations and parameters of the vibratory motion of the tool have been used as a carrier of information about the state of the tool. On the basis of the measurement data, obtained during tests of tools with varying degrees of damage, classifiers of the tool state were built. Two types of classifiers were tested: decision trees and artificial neural networks. The results confirm that it is possible to build a classifier of the tool state with high effectiveness reaching up to 99,875%.

scholarly journals Localization of Scattering Objects Using Neural Networks

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 11
Author(s):  
Domonkos Haffner ◽  
Ferenc Izsák
Keyword(s):  
Neural Networks ◽  
Plane Waves ◽  
Measurement Data ◽  
Scattered Wave ◽  
Training Data ◽  
Data Set ◽  
Main Compound ◽  
Incident Plane ◽  
The Neural Networks ◽  
Simulation Package

The localization of multiple scattering objects is performed while using scattered waves. An up-to-date approach: neural networks are used to estimate the corresponding locations. In the scattering phenomenon under investigation, we assume known incident plane waves, fully reflecting balls with known diameters and measurement data of the scattered wave on one fixed segment. The training data are constructed while using the simulation package μ-diff in Matlab. The structure of the neural networks, which are widely used for similar purposes, is further developed. A complex locally connected layer is the main compound of the proposed setup. With this and an appropriate preprocessing of the training data set, the number of parameters can be kept at a relatively low level. As a result, using a relatively large training data set, the unknown locations of the objects can be estimated effectively.

scholarly journals Improving the Performance of Steel Machining Processes through Cutting by Vibration Control

Materials ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 5712
Author(s):  
Mihaela Oleksik ◽  
Dan Dobrotă ◽  
Mădălin Tomescu ◽  
Valentin Petrescu
Keyword(s):  
Fourier Transformation ◽  
Vibration Analysis ◽  
Cutting Tool ◽  
Cutting Process ◽  
Manufacturing Processes ◽  
Machining Processes ◽  
Short Time ◽  
Short Time Fourier Transformation ◽  
Dynamic Phenomena

Machining processes through cutting are accompanied by dynamic phenomena that influence the quality of the processed surfaces. Thus, this research aimed to design, make, and use a tool with optimal functional geometry, which allowed a reduction of the dynamic phenomena that occur in the cutting process. In order to carry out the research, the process of cutting by front turning with transversal advance was taken into account. Additionally, semi-finished products with a diameter of Ø = 150 mm made of C45 steel were chosen for processing (1.0503). The manufacturing processes were performed with the help of two tools: a cutting tool, the classic construction version, and another that was the improved construction version. In the first stage of the research, an analysis was made of the vibrations that appear in the cutting process when using the two types of tools. Vibration analysis considered the following: use of the Fast Fourier Transform (FFT) method, application of the Short-Time Fourier-Transformation (STFT) method, and observation of the acceleration of vibrations recorded during processing. After the vibration analysis, the roughness of the surfaces was measured and the parameter Ra was taken into account, but a series of diagrams were also drawn regarding the curved profiles, filtered profiles, and Abbott–Firestone curve. The research showed that use of the tool that is the improved constructive variant allows accentuated reduction of vibrations correlated with an improvement of the quality of the processed surfaces.

scholarly journals Use of Neural Networks in Tool Wear Prediction

2019 ◽  
Vol 299 ◽  
pp. 04003
Author(s):  
Juraj Kundrík ◽  
Marek Kočiško ◽  
Martin Pollák ◽  
Monika Telišková ◽  
Anna Bašistová ◽  
...  
Keyword(s):  
Neural Networks ◽  
Tool Wear ◽  
Production Process ◽  
Machine Tools ◽  
Cutting Tool ◽  
Production Quality ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Tool Wear Prediction ◽  
Status Data

Modern CNC machine tools include a number of sensors that collect machine status data. These data are used to control the production process and for control of the CNC machine status. No less importantpart of the production process is also a machine tool. The condition of the cutting tool is important for the production quality and its failure can cause serious problems. Monitoring the condition of thecutting tool is complicated due to its dimensions and working conditions. The article describes how the tool wear can be predicted from the measured values of vibration and pressure by using neural networks.

Enhancement of Turning Process Using Vibration Signature Analysis

2005 ◽  
Author(s):  
Marlon C. Batey ◽  
Hamid R. Hamidzadeh
Keyword(s):  
Manufacturing Process ◽  
Vibration Analysis ◽  
Manufacturing System ◽  
Cutting Tool ◽  
Operating Conditions ◽  
Turning Process ◽  
Analysis Problem ◽  
Frequency Domains ◽  
Vibration Signature ◽  
Vibration Signatures

Analytical and experimental vibration analyses are conducted for a lathe system to detect the possibility of faults and develop an accurate cutting process. The data acquisition system utilized for this purpose processes the analog input from the manufacturing system and displays the response in both the real time and frequency domains. The vibration signatures for different arrangements are recorded to determine the dynamic characteristics of the system which includes work pieces, tool, and lathe components. These vibration signatures were analyzed to determine cause of inaccuracy in the manufacturing process and the faulty components. In this study, two major problem causing sources were identified using vibration analysis for the system under different operating conditions. In addition to the identified problems, the phenomena of cutting tool chatter with various intensities was examined and recorded during testing. In this study the best possible operating conditions for a specific turning process were determined using vibration analysis. Problem causing components for several case studies (different speeds, feed rates, and tool lengths) were identified and guidelines for improving a typical manufacturing process were recommended.

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