Evidence map›Paper›PMID 37214726›Full record

ReviewACS omega2023

Early Detection of Coal Spontaneous Combustion by Complex Acoustic Waves in a Concealed Fire Source.

Jun Guo, Haoyu Shang, Guobin Cai, Yongfei Jin, Kaixuan Wang, Shuai Li

Open access · goldAbstract readReview
In one paragraph

Review in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
5.5field-weighted citation impact, top 4% of its field
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

1 citing paper in PubMed, 28 citations in OpenAlex.

  1. Review
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

6 authors at 1 institution in 1 country.

Jun GuoCollege of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Haoyu ShangCollege of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Guobin CaiCollege of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.ORCID https://orcid.org/0000-0002-9558-9043
Yongfei JinCollege of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Kaixuan WangCollege of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Shuai LiCollege of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Xi'an University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prevention and control of coal spontaneous combustion are key to coal mining and storage. Existing technologies for the detection of coal spontaneous combustion have limitations, but coal spontaneous combustion creates some serious disasters in areas of the world where coal mining and/or storage exists. New technologies to detect coal spontaneous combustion are urgently needed to reduce the loss of life and resources. The article reviews the main techniques employed to detect coal spontaneous combustion and their advantages and disadvantages; it also reviews the good application prospect of acoustic temperature measurement technology on coal spontaneous combustion and introduces the basic principle of acoustic coal temperature measurement. The evolution of combustion sound and the propagation and attenuation of acoustic waves in quasi-porous media are discussed to form the basis for the development of acoustic thermometry technologies that can be used to accurately identify acoustic signals and temperature fields in loose coal. The concept of "single-source" coal temperature measurement to "dual-source" coal temperature measurement achieved by using combustion sound and an additional sound source device in the automatic combustion of loose coal in the mined area is discussed. The deep learning methods and correlation analyses are available to map the relationships between combustion sound, coal temperature, and sound velocity, and acquire coal temperature from dual source composite acoustic signals. The study lays the foundation for the development of acoustic thermometry technologies that have applications in different stages of combustion and applied to the early warning, prevention, and control of spontaneous combustion in coal, and it contributes to improving the environmental safety and efficiency of coal mining and storage.

Identifiers

PMID37214726
PMCPMC10193550
OpenAlexW4367625576

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.