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contributor authorS. Y. Hong
contributor authorJ. Ni
contributor authorS. M. Wu
date accessioned2017-05-08T23:44:52Z
date available2017-05-08T23:44:52Z
date copyrightFebruary, 1994
date issued1994
identifier issn1087-1357
identifier otherJMSEFK-27769#130_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/113972
description abstractA preemptive diagnostic system has been developed to detect minor machine failures before machine breakdown for a computer controlled robotic drilling end-effector. By using the Dynamic Data System (DDS) approach, a set of discrete time series data taken from the continuous vibration signal of the machine is analyzed to detect machine failure and to distinguish failures due to the spindle, gears, air motors, and ball bearings of the machine drive system. Experiments validate that the proposed diagnostic method can identify spindle, air motors, gear, and bearing defects in the Robotic Drilling Unit.
publisherThe American Society of Mechanical Engineers (ASME)
titlePreemptive Diagnosis of Minor Machine Failure by DDS Spectrum Analysis
typeJournal Paper
journal volume116
journal issue1
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.2901803
journal fristpage130
journal lastpage133
identifier eissn1528-8935
keywordsMachinery
keywordsFailure
keywordsPatient diagnosis
keywordsEmission spectroscopy
keywordsMotors
keywordsDrilling
keywordsSpindles (Textile machinery)
keywordsGears
keywordsRobotics
keywordsVibration
keywordsComputers
keywordsBall bearings
keywordsEnd effectors
keywordsProduct quality
keywordsBearings
keywordsSignals AND Time series
treeJournal of Manufacturing Science and Engineering:;1994:;volume( 116 ):;issue: 001
contenttypeFulltext


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