Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

Mechanical Systems and Signal Processing

Volumn 52-53, Issue 1, 2015, Pages 436-446

  Jegadeeshwaran, R ^a   Sugumaran, V ^a  

^a VIT UNIVERSITY   (India)

Author keywords

C4.5 algorithm; Decision tree; Kernel function; RBF; Statistical features; SVM

Indexed keywords

CONDITION MONITORING; DATA ACQUISITION; DATA MINING; DECISION TREES; FAULT DETECTION; HYDRAULIC BRAKES; HYDRAULIC MACHINERY; PATIENT MONITORING; TREES (MATHEMATICS); ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS;

C4.5 ALGORITHM; C4.5 DECISION TREE ALGORITHM; DATA ACQUISITION SYSTEM; KERNEL FUNCTION; MACHINE LEARNING APPROACHES; ONLINE CONDITION MONITORING; STATISTICAL FEATURES; VIBRATION CHARACTERISTICS; RBF; SVM;

SUPPORT VECTOR MACHINES;

EID: 84922888685     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2014.08.007     Document Type: Article

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