Enhancing Fault Classification Accuracy of Ball Bearing Using Central Tendency Based Time Domain Features

IEEE Access

Volumn 5, Issue , 2017, Pages 72-83

  Tahir, Muhammad Masood ^a   Khan, Abdul Qayyum ^b   Iqbal, Naeem ^b   Hussain, Ayyaz ^a   Badshah, Saeed ^a  

^a INTERNATIONAL ISLAMIC UNIVERSITY   (Pakistan)

^b PAKISTAN INSTITUTE OF ENGINEERING AND APPLIED SCIENCES   (Pakistan)

Author keywords

Central tendency of features; Fault diagnosis; Feature processing; Pattern recognition

Indexed keywords

BALL BEARINGS; COMPUTATIONAL EFFICIENCY; DATA HANDLING; FAILURE ANALYSIS; FAULT DETECTION; MACHINERY; PATTERN RECOGNITION;

CENTRAL TENDENCIES; DIAGNOSTIC CAPABILITIES; FAULT CLASSIFICATION ACCURACY; FEATURE DISTRIBUTION; FEATURE PROCESSING; RANDOM VIBRATIONS; STATISTICAL FEATURES; TIME DOMAIN FEATURES;

TIME DOMAIN ANALYSIS;

EID: 85014993100     PISSN: None     EISSN: 21693536     Source Type: Journal    
DOI: 10.1109/ACCESS.2016.2608505     Document Type: Article

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