Evidence map›Paper›PMID 34573817›Full record

ArticleEntropy (Basel, Switzerland)2021

A Satellite Incipient Fault Detection Method Based on Decomposed Kullback-Leibler Divergence.

Ge Zhang, Qiong Yang, Guotong Li, Jiaxing Leng, Mubiao Yan

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 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

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.

Ge ZhangInnovation Academy for Microsatellites of CAS, Shanghai 201203, China.ORCID 0000-0001-7127-9940
Qiong YangInnovation Academy for Microsatellites of CAS, Shanghai 201203, China.
Guotong LiInnovation Academy for Microsatellites of CAS, Shanghai 201203, China.
Jiaxing LengInnovation Academy for Microsatellites of CAS, Shanghai 201203, China.
Mubiao YanInnovation Academy for Microsatellites of CAS, Shanghai 201203, China.

Funding

Beidou Navigation In-orbit Support System JKBDZGDH01
6 · The paper itself

Abstract

Detection of faults at the incipient stage is critical to improving the availability and continuity of satellite services. The application of a local optimum projection vector and the Kullback-Leibler (KL) divergence can improve the detection rate of incipient faults. However, this suffers from the problem of high time complexity. We propose decomposing the KL divergence in the original optimization model and applying the property of the generalized Rayleigh quotient to reduce time complexity. Additionally, we establish two distribution models for subfunctions F1(w) and F3(w) to detect the slight anomalous behavior of the mean and covariance. The effectiveness of the proposed method was verified through a numerical simulation case and a real satellite fault case. The results demonstrate the advantages of low computational complexity and high sensitivity to incipient faults.

Indexed as

condition monitoringfault detectiongeneralized Rayleigh quotient (GRQ)incipient faultKullback–Leibler (KL) divergenceoptimum projection vector (PV)

Identifiers

PMID34573817
PMCPMC8472508

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.