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

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

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.

Original language	English
Title of host publication	ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks
Publisher	IEEE Computer Society
Pages	254-256
Number of pages	3
ISBN (Electronic)	9781728113395
DOIs	https://doi.org/10.1109/ICUFN.2019.8806033
State	Published - 07 2019
Event	11th International Conference on Ubiquitous and Future Networks, ICUFN 2019 - Zagreb, Croatia Duration: 02 07 2019 → 05 07 2019

Publication series

Name	International Conference on Ubiquitous and Future Networks, ICUFN
Volume	2019-July
ISSN (Print)	2165-8528
ISSN (Electronic)	2165-8536

Conference

Conference	11th International Conference on Ubiquitous and Future Networks, ICUFN 2019
Country/Territory	Croatia
City	Zagreb
Period	02/07/19 → 05/07/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

MFCC
acoustic sensing technology (AST)
array microphone
embedded controller

Access to Document

10.1109/ICUFN.2019.8806033

Cite this

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. In ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks (pp. 254-256). Article 8806033 (International Conference on Ubiquitous and Future Networks, ICUFN; Vol. 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. in ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks., 8806033, International Conference on Ubiquitous and Future Networks, ICUFN, vol. 2019-July, IEEE Computer Society, pp. 254-256, 11th International Conference on Ubiquitous and Future Networks, ICUFN 2019, Zagreb, Croatia, 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 et al.
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; Vol. 2019-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 - http://www.scopus.com/inward/record.url?scp=85071840866&partnerID=8YFLogxK

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

SP - 254

EP - 256

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this