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.