# Research on the Application of THz-TDS in Coal-Rock Interface Recognition
## 1 Introduction  
Coal, used to supply a large proportion of energy consumption, is expected to remain irreplaceable for a long time [1]. With advancements in coal mining technology, the depth of coal mines continues to increase. However, the common occurrence of rock bursts, fire, water inrush and other disasters casts a great dark cloud over this field; thus, it is essential to provide necessary warnings, in the face of the increasingly complex coal mining environment, to prevent loss of life and property [2]. Intelligent mining, that is, unmanned mining, is the ultimate goal of coal mine safety production, and research on coal-rock identification is a crucial step in achieving this goal [3, 4, 5]. Moreover, intelligent identification of coal-rock interface can maximize the efficient utilization of coal resources, replacing the existing manual identification, which not only reduces the safety risk for frontline coal miners but also avoids the waste of coal resources. It is noted that automatic height adjustment of the coal cutter drum is a key aspect of coal-rock interface identification technology. In recent years, considerable research efforts have been made in the field of coal-rock interface recognition technology, such as image detection, cutting force detection, intelligent sensing technology, ground-penetrating radar (GPR) detection, and infrared detection [6]. In 2019, [PERSON] et al. [7] used the finite-difference time-domain method to build models ofdifferent coal-rock combinations and conduct numerical simulations to obtain radar detection signals, demonstrating the applicability of radar detection technology in coal-rock interface recognition. In 2020, [PERSON] et al. [8] used a dynamic visualization modeling method to characterize the complex structure of coal seams to address the problem of stepwise transparency in coal seams. In 2021, [PERSON] [9] conducted a comparative study of LSM and RELB-based coal-rock identification methods, explaining their applicability in the field of coal and rock identification. [PERSON] et al. [10] classified coal by analyzing coal color and frequency histograms to obtain reflectance distributions. [PERSON] et al. [11] assessed the stress state of coal and rock mass in the coal cutting area and reconstructed a three-dimensional stress field of coal and rock mass through coal layer tomography and evaluation of the horizontal component of the external stress field. [PERSON] et al. [12] proposed a numerical method for simulating the coupled fluid-solid process during the failure of fractured coal-rock bodies by considering the characteristics of regional stress in the steep coal seam, providing a reliable theoretical basis for optimizing roof weakening in steep coal seam mining. Terahertz (THz) waves, with a frequency range from 0.1 THz to 10 THz, fall between microwaves and infrared waves in the electromagnetic spectrum. Due to their high resolution, non-contact and non-destructive properties, THz waves have been applied in diverse fields such as medical testing, space communication, and non-destructive testing [13; 14]. In recent years, THz time-domain spectroscopy has been applied to the study of coal-rock interfaces. Researchers such as [PERSON] et al. [15] from Tohoku University and Akita University in Japan measured the transmission spectra of dry and non-dry coal powder and polyethylene mixed with laminated samples in the range of 1-5 THz to estimate the water content in coal. [PERSON] [16] conducted an analysis of THz wave transmission properties in reservoir layers, revealing the transmission characteristics of THz waves in rocks, which is helpful to improve the efficiency of THz time-domain spectroscopy and enrich oil field exploration methods. In the realm of coal-rock identification, [PERSON] et al.