Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093))

Qi Zhong; Enguang Xu; Yan Shi; Teiwei Jia; Yan Ren; Huayong Yang; Yanbiao Li

doi:10.1016/j.ymssp.2023.110795

Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093))

Qi Zhong^*
, Enguang Xu
, Yan Shi
, Teiwei Jia
, Yan Ren
, Huayong Yang
, Yanbiao Li

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Zhejiang University of Technology
Zhejiang University
Wenzhou University

Research output: Contribution to journal › Comment/debate

Abstract

We would like to take this opportunity to supplement the following funding information for our paper. Funding Details: This work is supported by National Natural Science Foundation of China (No. 52005441), Young Elite Scientist Sponsorship Program by CAST (No. 2022QNRC001), Natural Science Foundation of Zhejiang Province (No. LQ21E050017), China Postdoctoral Science Foundation (Nos. 2021M692777 and 2021T140594) and “Pioneer” and “Leading Goose” R&D Program of Zhejiang Province (Nos. 2022C01122 and 2022C01132).

Original language	English
Article number	110795
Journal	Mechanical Systems and Signal Processing
Volume	204
DOIs	https://doi.org/10.1016/j.ymssp.2023.110795
State	Published - 1 Dec 2023

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Zhong, Q., Xu, E., Shi, Y., Jia, T., Ren, Y., Yang, H., & Li, Y. (2023). Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093)). Mechanical Systems and Signal Processing, 204, Article 110795. https://doi.org/10.1016/j.ymssp.2023.110795

Zhong, Qi ; Xu, Enguang ; Shi, Yan et al. / Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093)). In: Mechanical Systems and Signal Processing. 2023 ; Vol. 204.

@article{f3f9bcb8dd9f4b38ae11b033287261a2,

title = "Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093))",

abstract = "We would like to take this opportunity to supplement the following funding information for our paper. Funding Details: This work is supported by National Natural Science Foundation of China (No. 52005441), Young Elite Scientist Sponsorship Program by CAST (No. 2022QNRC001), Natural Science Foundation of Zhejiang Province (No. LQ21E050017), China Postdoctoral Science Foundation (Nos. 2021M692777 and 2021T140594) and “Pioneer” and “Leading Goose” R\&D Program of Zhejiang Province (Nos. 2022C01122 and 2022C01132).",

author = "Qi Zhong and Enguang Xu and Yan Shi and Teiwei Jia and Yan Ren and Huayong Yang and Yanbiao Li",

note = "Publisher Copyright: {\textcopyright} 2023 Elsevier Ltd",

year = "2023",

month = dec,

day = "1",

doi = "10.1016/j.ymssp.2023.110795",

language = "英语",

volume = "204",

journal = "Mechanical Systems and Signal Processing",

issn = "0888-3270",

publisher = "Academic Press",

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Zhong, Q, Xu, E, Shi, Y, Jia, T, Ren, Y, Yang, H & Li, Y 2023, 'Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093))', Mechanical Systems and Signal Processing, vol. 204, 110795. https://doi.org/10.1016/j.ymssp.2023.110795

Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093)). / Zhong, Qi; Xu, Enguang; Shi, Yan et al.
In: Mechanical Systems and Signal Processing, Vol. 204, 110795, 01.12.2023.

Research output: Contribution to journal › Comment/debate

TY - JOUR

T1 - Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093))

AU - Zhong, Qi

AU - Xu, Enguang

AU - Shi, Yan

AU - Jia, Teiwei

AU - Ren, Yan

AU - Yang, Huayong

AU - Li, Yanbiao

PY - 2023/12/1

Y1 - 2023/12/1

N2 - We would like to take this opportunity to supplement the following funding information for our paper. Funding Details: This work is supported by National Natural Science Foundation of China (No. 52005441), Young Elite Scientist Sponsorship Program by CAST (No. 2022QNRC001), Natural Science Foundation of Zhejiang Province (No. LQ21E050017), China Postdoctoral Science Foundation (Nos. 2021M692777 and 2021T140594) and “Pioneer” and “Leading Goose” R&D Program of Zhejiang Province (Nos. 2022C01122 and 2022C01132).

AB - We would like to take this opportunity to supplement the following funding information for our paper. Funding Details: This work is supported by National Natural Science Foundation of China (No. 52005441), Young Elite Scientist Sponsorship Program by CAST (No. 2022QNRC001), Natural Science Foundation of Zhejiang Province (No. LQ21E050017), China Postdoctoral Science Foundation (Nos. 2021M692777 and 2021T140594) and “Pioneer” and “Leading Goose” R&D Program of Zhejiang Province (Nos. 2022C01122 and 2022C01132).

UR - https://www.scopus.com/pages/publications/85172470791

U2 - 10.1016/j.ymssp.2023.110795

DO - 10.1016/j.ymssp.2023.110795

M3 - 评论/辩论

AN - SCOPUS:85172470791

SN - 0888-3270

VL - 204

JO - Mechanical Systems and Signal Processing

JF - Mechanical Systems and Signal Processing

M1 - 110795

ER -

Zhong Q, Xu E, Shi Y, Jia T, Ren Y, Yang H et al. Corrigendum to “Fault diagnosis of the hydraulic valve using a novel semi-supervised learning method based on multi-sensor information fusion” [Mechanical Systems and Signal Processing, 189 (2023) 110093] (Mechanical Systems and Signal Processing (2023) 189, (S088832702201161X), (10.1016/j.ymssp.2022.110093)). Mechanical Systems and Signal Processing. 2023 Dec 1;204:110795. doi: 10.1016/j.ymssp.2023.110795

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