contributor author | S. Y. Hong | |
contributor author | J. Ni | |
contributor author | S. M. Wu | |
date accessioned | 2017-05-08T23:44:52Z | |
date available | 2017-05-08T23:44:52Z | |
date copyright | February, 1994 | |
date issued | 1994 | |
identifier issn | 1087-1357 | |
identifier other | JMSEFK-27769#130_1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/113972 | |
description abstract | A 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. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Preemptive Diagnosis of Minor Machine Failure by DDS Spectrum Analysis | |
type | Journal Paper | |
journal volume | 116 | |
journal issue | 1 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.2901803 | |
journal fristpage | 130 | |
journal lastpage | 133 | |
identifier eissn | 1528-8935 | |
keywords | Machinery | |
keywords | Failure | |
keywords | Patient diagnosis | |
keywords | Emission spectroscopy | |
keywords | Motors | |
keywords | Drilling | |
keywords | Spindles (Textile machinery) | |
keywords | Gears | |
keywords | Robotics | |
keywords | Vibration | |
keywords | Computers | |
keywords | Ball bearings | |
keywords | End effectors | |
keywords | Product quality | |
keywords | Bearings | |
keywords | Signals AND Time series | |
tree | Journal of Manufacturing Science and Engineering:;1994:;volume( 116 ):;issue: 001 | |
contenttype | Fulltext | |