Evidence map›Paper›PMID 33542269›Full record

ArticleScientific reports2021

A novel diagnostic method based on filter bank theory for fast and accurate detection of thermoacoustic instability.

Seongpil Joo, Jongwun Choi, Namkeun Kim, Min Chul Lee

Abstract read
In one paragraph

Article in Scientific reports, 2021. 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

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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

4 authors.

Seongpil Joo *Gas Turbine Laboratory, National Research Council of Canada, Ottawa, ON, Canada.
Jongwun Choi *Department of Mechanical Engineering, Incheon National University, Incheon, 22012, Republic of Korea.
Namkeun KimDepartment of Mechanical Engineering, Incheon National University, Incheon, 22012, Republic of Korea. nkim@inu.ac.kr.
Min Chul LeeDepartment of Safety Engineering, Incheon National University, Incheon, 22012, Republic of Korea. LMC@inu.ac.kr.

Funding

Korea Electric Power Corporation R20XO02-34National Research Foundation of Korea (NRF) NRF-2019R1C1C1009739
6 · The paper itself

Abstract

This study proposes and analyzes a novel methodology that can effectively detect multi-mode combustion instability (CI) in a gas turbine combustor. The experiment is conducted in a model gas turbine combustor, and dynamic pressure (DP) and flame images are examined during the transition from stable to unstable flame, which is driven by changing fuel compositions. As a powerful technique for early detection of CI in multi-mode as well as in single mode, a new filter bank (FB) method based on spectral analysis of DP is proposed. Sequential processing using a triangular filter with Mel-scaling and a Hamming window is applied to increase the accuracy of the FB method, and the instability criterion is determined by calculating the magnitude of FB components. The performance of the FB method is compared with that of two conventional methods that are based on the root-mean-squared DP and temporal kurtosis. From the results, the FB method shows comparable performance in detection speed, sensitivity, and accuracy with other parameters. In addition, the FB components enable the analysis of various frequencies and multi-mode frequencies. Therefore, the FB method can be considered as an additional prognosis tool to determine the multi-mode CI in a monitoring system for gas turbine combustors.

Identifiers

PMID33542269
PMCPMC7862267

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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.