The Diagnosis of Abnormal Assembly Quality Based on Fuzzy Relation Equations

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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Main Authors: Dong-Ying Li, Gen-Bao Zhang, Meng-Qi Li, Jian Liu, Yan-Song Cheng
Format: Article
Language:English
Published: SAGE Publishing 2014-01-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1155/2014/437364
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spelling 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
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