Fault Detection in Axial Deformation Sensors for Hydraulic Turbine Head-Cover Fastening Bolts Using Analytical Redundancy.

Eddy Yujra Rivas, Alexander Vyacheslavov, Kirill Gogolinskiy, Kseniia Sapozhnikova, Roald Taymanov

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eddy Yujra RivasDepartment of Metrology, Instrumentation and Quality Management, Empress Catherine II Saint Petersburg Mining University, Saint Petersburg 199106, Russia.ORCID 0009-0007-3923-3644

Alexander VyacheslavovDepartment of Metrology, Instrumentation and Quality Management, Empress Catherine II Saint Petersburg Mining University, Saint Petersburg 199106, Russia.ORCID 0009-0006-0992-6039

Kirill GogolinskiyDepartment of Nuclear-Physics Research Methods, Saint Petersburg State University, Saint Petersburg 199034, Russia.ORCID 0000-0003-4908-0657

Kseniia SapozhnikovaLaboratory for Metrological Maintenance of Computerized Sensors and Measuring Systems, D.I. Mendeleyev Institute for Metrology, Saint Petersburg 199005, Russia.ORCID 0000-0003-1845-8944

Roald TaymanovLaboratory for Metrological Maintenance of Computerized Sensors and Measuring Systems, D.I. Mendeleyev Institute for Metrology, Saint Petersburg 199005, Russia.ORCID 0000-0003-2901-2040

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study proposes an analytical redundancy method that combines empirical models with a Kalman filter to ensure the reliability of measurements from axial deformation sensors in a turbine head-cover bolt-monitoring system. This integration enables the development of predictive models that optimally estimate the dynamic deformation of each bolt during turbine operation at full and partial load. The test results of the models under conditions of outliers, measurement noise, and changes in turbine operating mode, evaluated using accuracy and sensitivity metrics, confirmed their high accuracy (

Indexed as

analytical redundancybolts deformationfault detectionFrancis turbineKalman filtermonitoring system

Identifiers

PMID41682317

DOI10.3390/s26030801

PMCPMC12899857

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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.