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Wind Turbine Pitch System Fault Detection Using ssODM-DSTA

Overview of attention for article published in Frontiers in Energy Research, October 2021
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Title
Wind Turbine Pitch System Fault Detection Using ssODM-DSTA
Published in
Frontiers in Energy Research, October 2021
DOI 10.3389/fenrg.2021.750983
Authors

Mingzhu Tang, Jiahao Hu, Huawei Wu, Zimin Wang

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 October 2021.
All research outputs
#20,710,927
of 23,310,485 outputs
Outputs from Frontiers in Energy Research
#1,332
of 3,446 outputs
Outputs of similar age
#361,467
of 439,624 outputs
Outputs of similar age from Frontiers in Energy Research
#138
of 302 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,446 research outputs from this source. They receive a mean Attention Score of 1.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 439,624 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 302 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.