Application of Gaussian SVM Flame Detection Model Based on Color and Gradient Features in Engine Test Plume Images.

Song Yan, Yushan Gao, Zhiwei Zhang, Yi Li

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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

4 authors.

Song YanNational Key Laboratory of Aerospace Liquid Propulsion, Xi'an Aerospace Propulsion Institute, Xi'an 710100, China.

Yushan GaoAcademy of Aerospace Propulsion Technology, Xi'an 710100, China.

Zhiwei ZhangNational Key Laboratory of Aerospace Liquid Propulsion, Xi'an Aerospace Propulsion Institute, Xi'an 710100, China.

Yi LiNational Key Laboratory of Aerospace Liquid Propulsion, Xi'an Aerospace Propulsion Institute, Xi'an 710100, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a flame detection model that is based on real experimental data that were collected during turbopump hot-fire tests of a liquid rocket engine. In these tests, a MEMRECAM ACS-1 M40 high-speed camera-serving as an optical sensor within the test instrumentation system-captured plume images for analysis. To detect abnormal flame phenomena in the plume, a Gaussian support vector machine (SVM) model was developed using image features that were derived from both color and gradient information. Six representative frames containing visible flames were selected from a single test failure video. These images were segmented in the YCbCr color space using the

Indexed as

color featuresexhaust plumeflame detectiongradient featuresliquid rocket enginesupport vector machine (SVM)

Identifiers

PMID40943021

DOI10.3390/s25175592

PMCPMC12431464

What OpenQuestion holds

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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.