An automatic and integrated self-diagnosing system for the silting disease of drainage pipelines based on SSAE-TSNE and MS-LSTM

•Siltation diagnosing systems of drainage pipes cannot achieve full coverage.•Generative adversarial network solves the small data sample problem.•Guided faster R-CNN and parallel multiscale U-Net improves flow measurement.•Stochastic neighbour embedding is better at compressing key silting features...

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Bibliographic Details

Published in:	Tunnelling and underground space technology Vol. 136; p. 105076
Main Authors:	Di, Danyang, Wang, Dianchang, Fang, Hongyuan, He, Qiang, Zhou, Lifen, Chen, Xianming, Sun, Bin, Zhang, Jinping
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.06.2023
Subjects:	Drainage pipeline Long short-term memory (LSTM) Self-diagnosing system Silting disease Stacked sparse autoencoder (SSAE) Unmanned pipeline measuring device (UPM) Drainage pipeline Stacked sparse autoencoder (SSAE) Silting disease Unmanned pipeline measuring device (UPM) Long short-term memory (LSTM) Self-diagnosing system
ISSN:	0886-7798, 1878-4364
Online Access:	Get full text
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