Study of Ultrasonic Data Collection System for Anomaly Detection for Mechanical Equipment
Author:
Affiliation:
1. Kyushu Institute of Technology,Fukuoka,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10216364/10216365/10216770.pdf?arnumber=10216770
Reference5 articles.
1. Machine Fault Detection Based on Filter Bank Similarity Features Using Acoustic and Vibration Analysis
2. Unsupervised Detection of Anomalous Sound Based on Deep Learning and the Neyman–Pearson Lemma
3. Optimizing acoustic feature extractor for anomalous sound detection based on Neyman-Pearson lemma
4. Development of a Wireless Communication System for Reliable Acoustic Data Collection Toward Anomaly Detection in Mechanical Equipment
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1. Efficient Frequency Bandwidth Limitation for Wireless-Based Ultrasonic Data Collection Systems;Journal of Signal Processing;2024-07-01
2. The Effect of Compliant Backplate on Capacitive MEMS Microphones;IEEE Sensors Journal;2024-06-01
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