Evidence map›Paper›PMID 41978053›Full record

ArticleSensors (Basel, Switzerland)2026

Novel Technology for Unbalance Diagnosis for Dual-Speed Wind Turbines.

Amir R Askari, Len Gelman, Russell King, Daryl Hickey, Mehdi Behzad

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.

Amir R AskariDepartment of Engineering, School of Computing and Engineering, The University of Huddersfield, Huddersfield HD1 3DH, UK.ORCID 0000-0002-8090-7926
Len GelmanDepartment of Engineering, School of Computing and Engineering, The University of Huddersfield, Huddersfield HD1 3DH, UK.ORCID 0000-0001-5464-6227
Russell KingSensonics Ltd., 3 Northbridge Rd., Berkhamsted HP4 1EF, UK.
Daryl HickeyNatural Power, 120 Bath St., Glasgow G2 2EN, UK.
Mehdi BehzadDepartment of Mechanical Engineering, Sharif University of Technology, Tehran 11155-11365, Iran.ORCID 0000-0003-1675-1928

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unbalance diagnosis for non-constant speed systems is challenging because the 1X fundamental rotational harmonic magnitude, commonly used as an unbalance indicator, depends on shaft rotational speed. This dependency makes it difficult to separate speed effects from unbalance effects. It has been shown that 1X magnitudes become speed-invariant if they are normalized with respect to the rotational speed in power four for variable-speed wind turbines. However, the applicability of this diagnostic technology to dual-speed machines remains unclear. This study experimentally investigates unbalance diagnosis technologies for dual-speed wind turbines, for which speed-dependent interference is present. Vibration data are collected from the main bearings of two dual-speed wind turbines. Novel residual-based, speed-invariant unbalance diagnostic technology is proposed. The experimental results show consistent statistical distributions of the new diagnosis indicator across low and high-speed operating regimes. These findings confirm the suitability of the proposed technology for unbalance diagnosis for dual-speed rotating machinery.

Indexed as

fault diagnosisrotating machinerysignal processing

Identifiers

PMID41978053
PMCPMC13075278

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Registered trials

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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.