Cargando…
Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing
In the manufacturing industry, grinding is used as a major process for machining difficult-to-cut materials. Grinding is the most complicated and precise machining process. For grinding machines, continuous generating gear grinding machines are widely used to machine gears which are essential machin...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435638/ https://www.ncbi.nlm.nih.gov/pubmed/32708041 http://dx.doi.org/10.3390/s20154092 |
_version_ | 1783572368804806656 |
---|---|
author | Liu, Chien-Sheng Ou, Yang-Jiun |
author_facet | Liu, Chien-Sheng Ou, Yang-Jiun |
author_sort | Liu, Chien-Sheng |
collection | PubMed |
description | In the manufacturing industry, grinding is used as a major process for machining difficult-to-cut materials. Grinding is the most complicated and precise machining process. For grinding machines, continuous generating gear grinding machines are widely used to machine gears which are essential machine elements. However, due to its complicated process, it is very difficult to design a reliable measurement method to identify the grinding wheel loading phenomena during the grinding process. Therefore, this paper proposes a measurement method to identify the grinding wheel loading phenomenon in the grinding process for continuous generating gear grinding machines. In the proposed approach, an acoustic emission (AE) sensor was embedded to monitor the grinding wheel conditions; an offline digital image processing technique was used to determine the loading areas over the surface of Al(2)O(3) grinding wheels; and surface roughness of the ground workpiece was measured to quantify its machining quality. Then these three data were analyzed to find their correlation. The experimental results have shown that there are two stages of grinding in the grinding process and the proposed measurement method can provide a quantitative grinding wheel loading evaluation from the AE signals online. |
format | Online Article Text |
id | pubmed-7435638 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74356382020-08-28 Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing Liu, Chien-Sheng Ou, Yang-Jiun Sensors (Basel) Article In the manufacturing industry, grinding is used as a major process for machining difficult-to-cut materials. Grinding is the most complicated and precise machining process. For grinding machines, continuous generating gear grinding machines are widely used to machine gears which are essential machine elements. However, due to its complicated process, it is very difficult to design a reliable measurement method to identify the grinding wheel loading phenomena during the grinding process. Therefore, this paper proposes a measurement method to identify the grinding wheel loading phenomenon in the grinding process for continuous generating gear grinding machines. In the proposed approach, an acoustic emission (AE) sensor was embedded to monitor the grinding wheel conditions; an offline digital image processing technique was used to determine the loading areas over the surface of Al(2)O(3) grinding wheels; and surface roughness of the ground workpiece was measured to quantify its machining quality. Then these three data were analyzed to find their correlation. The experimental results have shown that there are two stages of grinding in the grinding process and the proposed measurement method can provide a quantitative grinding wheel loading evaluation from the AE signals online. MDPI 2020-07-22 /pmc/articles/PMC7435638/ /pubmed/32708041 http://dx.doi.org/10.3390/s20154092 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Chien-Sheng Ou, Yang-Jiun Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing |
title | Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing |
title_full | Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing |
title_fullStr | Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing |
title_full_unstemmed | Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing |
title_short | Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing |
title_sort | grinding wheel loading evaluation by using acoustic emission signals and digital image processing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435638/ https://www.ncbi.nlm.nih.gov/pubmed/32708041 http://dx.doi.org/10.3390/s20154092 |
work_keys_str_mv | AT liuchiensheng grindingwheelloadingevaluationbyusingacousticemissionsignalsanddigitalimageprocessing AT ouyangjiun grindingwheelloadingevaluationbyusingacousticemissionsignalsanddigitalimageprocessing |