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Dynamic resistance based intelligent...

El-Banna, Mahmoud.

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Dynamic resistance based intelligent resistance welding.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Dynamic resistance based intelligent resistance welding./
Author:	El-Banna, Mahmoud.
Description:	150 p.
Notes:	Source: Dissertation Abstracts International, Volume: 67-03, Section: B, page: 1654.
Contained By:	Dissertation Abstracts International67-03B.
Subject:	Engineering, Automotive. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3210988
ISBN:	9780542595349

Dynamic resistance based intelligent resistance welding.
El-Banna, Mahmoud.

Dynamic resistance based intelligent resistance welding. - 150 p.

Source: Dissertation Abstracts International, Volume: 67-03, Section: B, page: 1654.

Thesis (Ph.D.)--Wayne State University, 2006.

Resistance spot welding (RSW) is one of the most popular processes employed for sheet metal assembly. Although used in mass production for several decades, RSW poses several major problems, most notably, huge variation in weld quality. The strategy employed by the automobile OEMs to reduce the risk of part failure is to often require more welds to be performed than would be needed to maintain structural integrity if each weld was made reliably. Advances over the last decade in the area of non-intrusive electronic sensors, signal processing algorithms, and computational intelligence, coupled with drastic reductions in computing and networking hardware costs, have now made it possible to develop non-intrusive intelligent resistance welding systems that overcome the above shortcomings.

ISBN: 9780542595349Subjects--Topical Terms:

1018477
Engineering, Automotive.

Dynamic resistance based intelligent resistance welding.
LDR:03217nmm 2200325 4500 001 1828874
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008 130610s2006 eng d
020 $a 9780542595349
035 $a (UMI)AAI3210988
035 $a AAI3210988
040 $a UMI $c UMI
100 1 $a El-Banna, Mahmoud. $3 1917753
245 1 0 $a Dynamic resistance based intelligent resistance welding.
300 $a 150 p.
500 $a Source: Dissertation Abstracts International, Volume: 67-03, Section: B, page: 1654.
500 $a Advisers: Ratna Babu Chinnam; Dimitar Filev.
502 $a Thesis (Ph.D.)--Wayne State University, 2006.
520 $a Resistance spot welding (RSW) is one of the most popular processes employed for sheet metal assembly. Although used in mass production for several decades, RSW poses several major problems, most notably, huge variation in weld quality. The strategy employed by the automobile OEMs to reduce the risk of part failure is to often require more welds to be performed than would be needed to maintain structural integrity if each weld was made reliably. Advances over the last decade in the area of non-intrusive electronic sensors, signal processing algorithms, and computational intelligence, coupled with drastic reductions in computing and networking hardware costs, have now made it possible to develop non-intrusive intelligent resistance welding systems that overcome the above shortcomings.
520 $a The research develops an Intelligent Resistance Welding System that improves the weld quality and reduces the number of welds needed. In particular, there are three specific research achievements: (1) Development of a resistance welding monitoring system based on Linear Vector Quantization (LVQ) algorithm for accurate in-process non-destructive classification of nugget quality by using the dynamic resistance (or voltage) profile, (2) Development of a fuzzy control scheme for adapting the controller set point for weld quality enhancement, and (3) Development of an algorithm for on-line evaluation of the electrode condition right after tip dressing.
520 $a The fuzzy control scheme developed for adapting the welding controller set point relies on two soft sensors for expulsion detection as well as weld quality evaluation. The objective is to operate the welding process just beneath the expulsion level conditions to achieve optimum weld strength. The adaptive fuzzy control scheme was successful in reducing the number of bad welds, cold or expulsion welds, when used on Medium Frequency Direct Current (MFDC) constant current control against the traditional stepper/no stepper techniques.
520 $a Fuzzy C-means clustering algorithm implemented in a hierarchal fashion is used to evaluate the electrode condition right after tip dressing. The algorithm was successfully verified on constant current and constant heat alternating current controllers.
590 $a School code: 0254.
650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Mechanical. $3 783786
690 $a 0540
690 $a 0548
710 2 0 $a Wayne State University. $3 975058
773 0 $t Dissertation Abstracts International $g 67-03B.
790 1 0 $a Chinnam, Ratna Babu, $e advisor
790 1 0 $a Filev, Dimitar, $e advisor
790 $a 0254
791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3210988