Feature extraction of rotating apparatus using acoustic sensing technology

Cihun Siyong Alex Gong; Chih Hui Simon Su; Yu Chieh Chuang; Kuei Hung Tseng; Tien Hua Li; Chih Hsiung Chang; Lung Hsien Huang

doi:10.1109/ICUFN.2019.8806033

Feature extraction of rotating apparatus using acoustic sensing technology

Cihun Siyong Alex Gong
, Chih Hui Simon Su
, Yu Chieh Chuang
, Kuei Hung Tseng
, Tien Hua Li
, Chih Hsiung Chang
, Lung Hsien Huang

電機工程學系(含學碩博士班及碩士在職專班)

Chang Gung Memorial Hospital
Chang Gung University
AIGTG Group Taoyuan

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

4 引文斯高帕斯（Scopus）

摘要

This article presents a feature extraction of rotating apparatus using acoustic sensing technology (AST). The kernel algorithm is based on an acoustic signal enhancement filter (ASEF). The acoustic feature extraction algorithm is implemented by using Mel-scale frequency cepstral coefficient (MFCC) theory. The system utilizes an National Instruments (NI) cRIO-9067 embedded controller and a real-time signal sensing module to analyze rotation performance and predict malfunctions in rotating apparatus. AST can adopt low noise array microphone which the effective bandwidth is 20 to 10000 Hz. Experimental results showed that the acoustic signal method could effectively perform real-time early fault detection and prediction in proposed system. Smart AST was proposed that can distinguish the acoustic feature differences of normal and abnormal ones.

原文	英語
主出版物標題	ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks
發行者	IEEE Computer Society
頁面	254-256
頁數	3
ISBN（電子）	9781728113395
DOIs	https://doi.org/10.1109/ICUFN.2019.8806033
出版狀態	已出版 - 07 2019
事件	11th International Conference on Ubiquitous and Future Networks, ICUFN 2019 - Zagreb, 克羅地亞持續時間: 02 07 2019 → 05 07 2019

出版系列

名字	International Conference on Ubiquitous and Future Networks, ICUFN
卷	2019-July
ISSN（列印）	2165-8528
ISSN（電子）	2165-8536

Conference

Conference	11th International Conference on Ubiquitous and Future Networks, ICUFN 2019
國家/地區	克羅地亞
城市	Zagreb
期間	02/07/19 → 05/07/19

文獻附註

Publisher Copyright:
© 2019 IEEE.

存取文件

10.1109/ICUFN.2019.8806033

其它文件與鏈接

Link to publication in Scopus

引用此

Gong, C. S. A., Su, C. H. S., Chuang, Y. C., Tseng, K. H., Li, T. H., Chang, C. H., & Huang, L. H. (2019). Feature extraction of rotating apparatus using acoustic sensing technology. 於 ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks (頁 254-256). 文章 8806033 (International Conference on Ubiquitous and Future Networks, ICUFN; 卷 2019-July). IEEE Computer Society. https://doi.org/10.1109/ICUFN.2019.8806033

@inproceedings{8d37596961df4b0e8945d07f015ce719,

title = "Feature extraction of rotating apparatus using acoustic sensing technology",

abstract = "This article presents a feature extraction of rotating apparatus using acoustic sensing technology (AST). The kernel algorithm is based on an acoustic signal enhancement filter (ASEF). The acoustic feature extraction algorithm is implemented by using Mel-scale frequency cepstral coefficient (MFCC) theory. The system utilizes an National Instruments (NI) cRIO-9067 embedded controller and a real-time signal sensing module to analyze rotation performance and predict malfunctions in rotating apparatus. AST can adopt low noise array microphone which the effective bandwidth is 20 to 10000 Hz. Experimental results showed that the acoustic signal method could effectively perform real-time early fault detection and prediction in proposed system. Smart AST was proposed that can distinguish the acoustic feature differences of normal and abnormal ones.",

keywords = "MFCC, acoustic sensing technology (AST), array microphone, embedded controller",

author = "Gong, \{Cihun Siyong Alex\} and Su, \{Chih Hui Simon\} and Chuang, \{Yu Chieh\} and Tseng, \{Kuei Hung\} and Li, \{Tien Hua\} and Chang, \{Chih Hsiung\} and Huang, \{Lung Hsien\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 11th International Conference on Ubiquitous and Future Networks, ICUFN 2019 ; Conference date: 02-07-2019 Through 05-07-2019",

year = "2019",

month = jul,

doi = "10.1109/ICUFN.2019.8806033",

language = "英语",

series = "International Conference on Ubiquitous and Future Networks, ICUFN",

publisher = "IEEE Computer Society",

pages = "254--256",

booktitle = "ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks",

address = "美国",

}

Gong, CSA, Su, CHS, Chuang, YC, Tseng, KH, Li, TH, Chang, CH & Huang, LH 2019, Feature extraction of rotating apparatus using acoustic sensing technology. 於 ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks., 8806033, International Conference on Ubiquitous and Future Networks, ICUFN, 卷 2019-July, IEEE Computer Society, 頁 254-256, 11th International Conference on Ubiquitous and Future Networks, ICUFN 2019, Zagreb, 克羅地亞, 02/07/19. https://doi.org/10.1109/ICUFN.2019.8806033

Feature extraction of rotating apparatus using acoustic sensing technology. / Gong, Cihun Siyong Alex; Su, Chih Hui Simon; Chuang, Yu Chieh 等.
ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks. IEEE Computer Society, 2019. p. 254-256 8806033 (International Conference on Ubiquitous and Future Networks, ICUFN; 卷 2019-July).

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

TY - GEN

T1 - Feature extraction of rotating apparatus using acoustic sensing technology

AU - Gong, Cihun Siyong Alex

AU - Su, Chih Hui Simon

AU - Chuang, Yu Chieh

AU - Tseng, Kuei Hung

AU - Li, Tien Hua

AU - Chang, Chih Hsiung

AU - Huang, Lung Hsien

PY - 2019/7

Y1 - 2019/7

N2 - This article presents a feature extraction of rotating apparatus using acoustic sensing technology (AST). The kernel algorithm is based on an acoustic signal enhancement filter (ASEF). The acoustic feature extraction algorithm is implemented by using Mel-scale frequency cepstral coefficient (MFCC) theory. The system utilizes an National Instruments (NI) cRIO-9067 embedded controller and a real-time signal sensing module to analyze rotation performance and predict malfunctions in rotating apparatus. AST can adopt low noise array microphone which the effective bandwidth is 20 to 10000 Hz. Experimental results showed that the acoustic signal method could effectively perform real-time early fault detection and prediction in proposed system. Smart AST was proposed that can distinguish the acoustic feature differences of normal and abnormal ones.

AB - This article presents a feature extraction of rotating apparatus using acoustic sensing technology (AST). The kernel algorithm is based on an acoustic signal enhancement filter (ASEF). The acoustic feature extraction algorithm is implemented by using Mel-scale frequency cepstral coefficient (MFCC) theory. The system utilizes an National Instruments (NI) cRIO-9067 embedded controller and a real-time signal sensing module to analyze rotation performance and predict malfunctions in rotating apparatus. AST can adopt low noise array microphone which the effective bandwidth is 20 to 10000 Hz. Experimental results showed that the acoustic signal method could effectively perform real-time early fault detection and prediction in proposed system. Smart AST was proposed that can distinguish the acoustic feature differences of normal and abnormal ones.

KW - MFCC

KW - acoustic sensing technology (AST)

KW - array microphone

KW - embedded controller

UR - https://www.scopus.com/pages/publications/85071840866

U2 - 10.1109/ICUFN.2019.8806033

DO - 10.1109/ICUFN.2019.8806033

M3 - 会议稿件

AN - SCOPUS:85071840866

T3 - International Conference on Ubiquitous and Future Networks, ICUFN

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BT - ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks

PB - IEEE Computer Society

T2 - 11th International Conference on Ubiquitous and Future Networks, ICUFN 2019

Y2 - 2 July 2019 through 5 July 2019

ER -

Feature extraction of rotating apparatus using acoustic sensing technology

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