The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation Equations
The relationship between quality abnormality and anomalous causes in the assembly process of CNC machine was described by fuzzy relation equations, because they were not one to one. The fuzzy relation equations were established according to the fuzzy relation matrix and membership degree of abnormal...
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2014-01-01
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Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1155/2014/437364 |
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doaj-302e71b4db1141d5b26a77054b7de2a52020-11-25T03:43:56ZengSAGE PublishingAdvances in Mechanical Engineering1687-81322014-01-01610.1155/2014/43736410.1155_2014/437364The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation EquationsDong-Ying Li0Gen-Bao Zhang1Meng-Qi Li2Jian Liu3Yan-Song Cheng4 Department of Mechanical and Energy Engineering, Shaoyang University, Hunan 422000, China College of Mechanical Engineering, Chongqing University, Chongqing 400044, China Department of Mechanical and Energy Engineering, Shaoyang University, Hunan 422000, China College of Mechanical Engineering, Chongqing University, Chongqing 400044, China ChongQing Technology and Business Institute, ChinaThe relationship between quality abnormality and anomalous causes in the assembly process of CNC machine was described by fuzzy relation equations, because they were not one to one. The fuzzy relation equations were established according to the fuzzy relation matrix and membership degree of abnormality mode and were translated into optimal solution problems by fuzzy deconvolution method. The interval solution of the fuzzy relation equation was obtained by minimal mean square error of BP algorithm, realizing section locating of the contribution of anomalous causes to quality abnormality for a given problem, thereby gaining the optimal solution. Finally, the viability and effectiveness of this method were verified by the quality abnormity diagnosis in the assembly process of a NC rotary table.https://doi.org/10.1155/2014/437364 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dong-Ying Li Gen-Bao Zhang Meng-Qi Li Jian Liu Yan-Song Cheng |
spellingShingle |
Dong-Ying Li Gen-Bao Zhang Meng-Qi Li Jian Liu Yan-Song Cheng The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation Equations Advances in Mechanical Engineering |
author_facet |
Dong-Ying Li Gen-Bao Zhang Meng-Qi Li Jian Liu Yan-Song Cheng |
author_sort |
Dong-Ying Li |
title |
The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation Equations |
title_short |
The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation Equations |
title_full |
The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation Equations |
title_fullStr |
The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation Equations |
title_full_unstemmed |
The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation Equations |
title_sort |
diagnosis of abnormal assembly quality based on fuzzy relation equations |
publisher |
SAGE Publishing |
series |
Advances in Mechanical Engineering |
issn |
1687-8132 |
publishDate |
2014-01-01 |
description |
The relationship between quality abnormality and anomalous causes in the assembly process of CNC machine was described by fuzzy relation equations, because they were not one to one. The fuzzy relation equations were established according to the fuzzy relation matrix and membership degree of abnormality mode and were translated into optimal solution problems by fuzzy deconvolution method. The interval solution of the fuzzy relation equation was obtained by minimal mean square error of BP algorithm, realizing section locating of the contribution of anomalous causes to quality abnormality for a given problem, thereby gaining the optimal solution. Finally, the viability and effectiveness of this method were verified by the quality abnormity diagnosis in the assembly process of a NC rotary table. |
url |
https://doi.org/10.1155/2014/437364 |
work_keys_str_mv |
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