Feature extraction and selection from acoustic emission signals with an application in grinding wheel condition monitoring

T. Warren Liao

doi:10.1016/j.engappai.2009.09.004

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Feature extraction and selection from acoustic emission signals with an application in grinding wheel condition monitoring

T. Warren Liao

Year: 2009 Journal: Engineering Applications of Artificial Intelligence Vol: 23 (1)Pages: 74-84 Publisher: Elsevier BV

DOI: 10.1016/j.engappai.2009.09.004

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Keywords:

Computer science Feature extraction Feature selection Pattern recognition (psychology) Classifier (UML) Acoustic emission Artificial intelligence Grinding Ant colony optimization algorithms Autoregressive model Wavelet Engineering Acoustics Mathematics

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112

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8.37

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0.97

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Topics

Advanced machining processes and optimization

Physical Sciences → Engineering → Mechanical Engineering

Mineral Processing and Grinding

Physical Sciences → Engineering → Mechanical Engineering

Advanced Machining and Optimization Techniques

Physical Sciences → Engineering → Electrical and Electronic Engineering

Feature extraction and selection from acoustic emission signals with an application in grinding wheel condition monitoring

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Citation History

Topics

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