Acoustic Condition Monitoring: Signal Analysis for Large Machinery Halls-Reference-Cited by-同舟云学术

Acoustic Condition Monitoring: Signal Analysis for Large Machinery Halls

Published:2022-05-16 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
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Author:

Pichler C.¹,Neumayer M.¹,Schweighofer B.¹,Feilmayr C.²,Schuster S.²,Puttinger S.³,Wegleiter H.¹

Affiliation:

1. Graz University of Technology,Christian Doppler Laboratory for Measurement Systems for Harsh Operating Conditions Institute of Electrical Measurement and Sensor Systems,Graz,Austria,A-8010

2. Voestalpine Stahl GmbH,Austria,A-4020

3. Johannes Kepler University,Department of Particulate Flow Modelling,Linz,Austria,A-4040

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9806445/9806446/09806680.pdf?arnumber=9806680

Reference14 articles.

1. Application of Clustering Methods for Online Tool Condition Monitoring and Fault Diagnosis in High-Speed Milling Processes

2. A machine learning approach for the condition monitoring of rotating machinery

3. Acoustic Signal Processing for Anomaly Detection in Machine Room Environments

4. Roc graphs: Notes and practical considerations for researchers;fawcett;Machine Learning,2004

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