Single Fault Diagnosis Method of Sensors in Cascade System Based on Data-Driven.

Wenbo Na, Siyu Guo, Yanfeng Gao, Jianxing Yang, Junjie Huang

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

5 authors.

Wenbo NaCollege of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.

Siyu GuoCollege of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.

Yanfeng GaoCollege of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.

Jianxing YangCollege of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.

Junjie HuangCollege of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.

Funding

Nature Science Foundation of Zhejiang Province LGG20F030005

6 · The paper itself

Abstract

The reliability and safety of the cascade system, which is widely applied, have attached attention increasingly. Fault detection and diagnosis can play a significant role in enhancing its reliability and safety. On account of the complexity of the double closed-loop system in operation, the problem of fault diagnosis is relatively complex. For the single fault of the second-order valued system sensors, a real-time fault diagnosis method based on data-driven is proposed in this study. Off-line data is employed to establish static fault detection, location, estimation, and separation models. The static models are calibrated with on-line data to obtain the real-time fault diagnosis models. The real-time calibration, working flow and anti-interference measures of the real-time diagnosis system are given. Experiments results demonstrate the validity and accuracy of the fault diagnosis method, which is suitable for the general cascade system.

Indexed as

Reproducibility of ResultsCalibrationcascade systemdata-drivenfault diagnosissensor

Identifiers

PMID34770645

DOI10.3390/s21217340

PMCPMC8588395

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.