Special Issue on “Process Safety and Monitoring of Intelligent and Green Mining Technology”

The safe production of mineral resources serves as a crucial cornerstone for sustaining the steady development of the national economy, and the level of its guarantee is directly linked to the overall situation of the industry’s sustainable development [1]. Against the backdrop of the transformation and upgrading of the mining industry, a mining mode that integrates intelligent technology, green concepts, and safety management has become a core driving force for advancing the high-quality development of modern mines [2,3]. To systematically present cutting-edge explorations in this field, this Special Issue focuses on the theme of “Process Safety and Monitoring of Intelligent and Green Mining Technology”. It brings together a series of high-quality research papers that collectively demonstrate key issues and innovative directions in the field of safety monitoring during the current mineral resource mining process:

One study conducted a detailed cutting height analysis for composite hard rock roof retention and chose the 12 1103 working face at the Qiuji Coal Mine as the research subject [4]. Studying and adjusting the cutting height of the working face saved drilling construction costs and improved construction efficiency.

One paper focuses on the development law of the water-conducting fracture zone (WCFZ) through comprehensive research methods, including similar simulation experiments, key layer theory, empirical formulas, and numerical simulations [5]. This study took the 150313 fully mechanized top coal caving face of Yinying Coal Mine as the engineering background and verified that the indoor research method is feasible for predicting the height and range of WCFZ.

Another study explored gob-side entry retaining (GSER) control technology on the surrounding rock below goaf in a near-distance coal seam (NDCS); this comprehensive control technology includes grouting transformation, and the establishment of an anchorage structure is proposed [6].

One paper established a B-G damage constitutive model in the process of studying the damage evolution and fracture mechanism of floor rock in goaf under the disturbance of static and dynamic coupling loading caused by roof caving [7]. Finally, the stress distribution expression of floor strata under concentrated and uniform dynamic loads is introduced, and the fracture criterion of goaf floor strata under a coupled static–dynamic loading disturbance is proposed.

A study combined DIC technology under biaxial compression with numerical simulation to study the crack propagation of tunnels with different sections, and the elliptical section was concluded to show the optimal bearing capacity [8]. The combination of AE, DIC technology, and PFC reveals the evolution process and failure precursor of tunnel cracks under biaxial conditions [9].

Another study introduced an improved BP neural network based on immune algorithm–particle swarm optimization was introduced to predict the mine pressure of Meihuajing Coal Mine. The final prediction results are in line with the periodic variation law of mine pressure data and consistent with the actual situation of the coal mine [10]. This study provides a reliable model for the prediction of mine pressure.

In another contribution, the rock mass fracture signal in microseismic monitoring is shown to provide guidance for the early warning of rock mass instability and stability analysis of underground caverns under blasting excavation disturbance [11].

Finally, this Special Issue also includes an experimental study on the relationship between the failure mode and energy dissipation of bolt support system [12], emphasizing the importance and influence of energy accumulation and dissipation on bolt failure.

As the Guest Editor of this Special Issue, I would like to extend my most sincere gratitude to two colleagues. First, I thank all contributing authors of MDPI. Your high-quality research achievements, rooted in the field of intelligent green mining technology, have laid the core academic value for this Special Issue and serve as the fundamental guarantee for its content quality. Second, I would like to thank all dedicated staff members. With your professional and efficient support throughout the entire process of this Special Issue, from manuscript collection and review to publication, you have ensured the smooth progress of the editing work.

It is my sincere hope that readers will gain an in-depth understanding of typical practical cases of intelligent green mining technology in the field of process safety and monitoring from the papers in this issue, as well as obtain academic inspiration and industry references therefrom.