A HYBRID APPROACH TO HYDRAULIC VANE PUMP CONDITION MONITORING AND FAULT DETECTION

2006 ◽  
Vol 49 (4) ◽  
pp. 1203-1211 ◽  
Author(s):  
K. M. Hancock ◽  
Q. Zhang
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Hybrid Approach ◽  
Vane Pump

Condition monitoring and fault detection in wind turbines based on cointegration analysis of SCADA data

2018 ◽  
Vol 116 ◽  
pp. 107-122 ◽  
Author(s):  
Phong B. Dao ◽  
Wieslaw J. Staszewski ◽  
Tomasz Barszcz ◽  
Tadeusz Uhl
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Wind Turbines ◽  
Cointegration Analysis

scholarly journals Fault severity detection of a worm gearbox based on several feature extraction methods through a developed condition monitoring system

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Berkan Hızarcı ◽  
Rafet Can Ümütlü ◽  
Zeki Kıral ◽  
Hasan Öztürk
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Extraction Methods ◽  
Poincaré Plot ◽  
Vibration Data ◽  
Sliding Motion ◽  
Fault Severity ◽  
Fault Features ◽  
Gearbox Vibration ◽  
Condition Monitoring System

AbstractThis study presents the severity detection of pitting faults on worm gearbox through the assessment of fault features extracted from the gearbox vibration data. Fault severity assessment on worm gearbox is conducted by the developed condition monitoring instrument with observing not only traditional but also multidisciplinary features. It is well known that the sliding motion between the worm gear and wheel gear causes difficulties about fault detection on worm gearboxes. Therefore, continuous monitoring and observation of different types of fault features are very important, especially for worm gearboxes. Therefore, in this study, time-domain statistics, the features of evaluated vibration analysis method and Poincaré plot are examined for fault severity detection on worm gearbox. The most reliable features for fault detection on worm gearbox are determined via the parallel coordinate plot. The abnormality detection during worm gearbox operation with the developed system is performed successfully by means of a decision tree.

scholarly journals Fault Detection and Severity Identification of Ball Bearings by Online Condition Monitoring

2019 ◽  
Vol 66 (10) ◽  
pp. 8136-8147 ◽  
Author(s):  
Osama Abdeljaber ◽  
Sadok Sassi ◽  
Onur Avci ◽  
Serkan Kiranyaz ◽  
Abdelrahman Aly Ibrahim ◽  
...  
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Ball Bearings

Residual-based fault detection using soft computing techniques for condition monitoring at rolling mills

2014 ◽  
Vol 259 ◽  
pp. 304-320 ◽  
Author(s):  
Francisco Serdio ◽  
Edwin Lughofer ◽  
Kurt Pichler ◽  
Thomas Buchegger ◽  
Hajrudin Efendic
Keyword(s):  
Fault Detection ◽  
Soft Computing ◽  
Condition Monitoring ◽  
Rolling Mills ◽  
Soft Computing Techniques
Sign in / Sign up

Export Citation Format

Share Document