ReviewACS omega2023
Early Detection of Coal Spontaneous Combustion by Complex Acoustic Waves in a Concealed Fire Source.
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.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed, 28 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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
What OpenQuestion holds
Registered trials
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.