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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Vydané v:	Tunnelling and underground space technology Ročník 136; s. 105076
Hlavní autori:	Di, Danyang, Wang, Dianchang, Fang, Hongyuan, He, Qiang, Zhou, Lifen, Chen, Xianming, Sun, Bin, Zhang, Jinping
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.06.2023
Predmet:	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
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