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An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’. / Lu, Siliang; Wang, Xiaoxian; Ju, Bin et al.
Communications in Computer and Information Science. Singapore: Springer, 2023. p. 220-230 (Communications in Computer and Information Science).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Lu, S, Wang, X, Ju, B, Liu, Y, Xie, F & Xia, M 2023, An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’. in Communications in Computer and Information Science. Communications in Computer and Information Science, Springer, Singapore, pp. 220-230. https://doi.org/10.1007/978-981-99-2449-3_20

APA

Lu, S., Wang, X., Ju, B., Liu, Y., Xie, F., & Xia, M. (2023). An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’. In Communications in Computer and Information Science (pp. 220-230). (Communications in Computer and Information Science). Springer. https://doi.org/10.1007/978-981-99-2449-3_20

Vancouver

Lu S, Wang X, Ju B, Liu Y, Xie F, Xia M. An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’. In Communications in Computer and Information Science. Singapore: Springer. 2023. p. 220-230. (Communications in Computer and Information Science). doi: 10.1007/978-981-99-2449-3_20

Author

Lu, Siliang ; Wang, Xiaoxian ; Ju, Bin et al. / An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’. Communications in Computer and Information Science. Singapore : Springer, 2023. pp. 220-230 (Communications in Computer and Information Science).

Bibtex

@inproceedings{513ba2c7836e4ef68f5ffe22cae6216e,
title = "An Experimental Case Study for the Course of {\textquoteleft}Testing Technology and Data Processing{\textquoteright}",
abstract = "{\textquoteleft}Testing Technology and Data Processing (TTDP){\textquoteright} is one of the core courses for the undergraduates in mechanical engineering subject. This paper designs an experimental case to improve the students{\textquoteright} abilities in signal acquisition, preprocessing, feature extraction, and artificial intelligence (AI)-based pattern recognition. The case study is based on an internet of things (IoT) node that integrating with accelerometer, microphone, and magnetic sensors. The order tracking algorithm and a double-layer bidirectional long short-term memory (DBiLSTM) model are used to process the multi-sensor data for condition monitoring and fault diagnosis of a motor. The students{\textquoteright} feedback demonstrates that the designed case improves their interests to this course, and also improves their abilities in engineering practice.",
author = "Siliang Lu and Xiaoxian Wang and Bin Ju and Yongbin Liu and Feng Xie and Min Xia",
year = "2023",
month = may,
day = "16",
doi = "10.1007/978-981-99-2449-3_20",
language = "English",
isbn = "9789819924486",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "220--230",
booktitle = "Communications in Computer and Information Science",

}

RIS

TY - GEN

T1 - An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’

AU - Lu, Siliang

AU - Wang, Xiaoxian

AU - Ju, Bin

AU - Liu, Yongbin

AU - Xie, Feng

AU - Xia, Min

PY - 2023/5/16

Y1 - 2023/5/16

N2 - ‘Testing Technology and Data Processing (TTDP)’ is one of the core courses for the undergraduates in mechanical engineering subject. This paper designs an experimental case to improve the students’ abilities in signal acquisition, preprocessing, feature extraction, and artificial intelligence (AI)-based pattern recognition. The case study is based on an internet of things (IoT) node that integrating with accelerometer, microphone, and magnetic sensors. The order tracking algorithm and a double-layer bidirectional long short-term memory (DBiLSTM) model are used to process the multi-sensor data for condition monitoring and fault diagnosis of a motor. The students’ feedback demonstrates that the designed case improves their interests to this course, and also improves their abilities in engineering practice.

AB - ‘Testing Technology and Data Processing (TTDP)’ is one of the core courses for the undergraduates in mechanical engineering subject. This paper designs an experimental case to improve the students’ abilities in signal acquisition, preprocessing, feature extraction, and artificial intelligence (AI)-based pattern recognition. The case study is based on an internet of things (IoT) node that integrating with accelerometer, microphone, and magnetic sensors. The order tracking algorithm and a double-layer bidirectional long short-term memory (DBiLSTM) model are used to process the multi-sensor data for condition monitoring and fault diagnosis of a motor. The students’ feedback demonstrates that the designed case improves their interests to this course, and also improves their abilities in engineering practice.

U2 - 10.1007/978-981-99-2449-3_20

DO - 10.1007/978-981-99-2449-3_20

M3 - Conference contribution/Paper

SN - 9789819924486

T3 - Communications in Computer and Information Science

SP - 220

EP - 230

BT - Communications in Computer and Information Science

PB - Springer

CY - Singapore

ER -