The safety valves of powered supports control the maximum working resistance, and their statuses must be known to ensure the safety of both the support and the overlying strata. However, the inspection of powered support valves involves manual or semiautomated operations, the costs of which are high. In this study, an extreme point extraction method was developed for the determination of the characteristic parameters of safety valves using roof pressure data, and a safety valve state monitoring module was constructed. Using the longwall face of 0116³06 with top coal caving in the Mindong Mine as an example, the characteristic parameters of the safety valves were extracted, including the peak, reseating, and blowdown pressures, as well as the recovery and unloading durations. The results of the field tests showed the following: (1) The amplitude threshold method based on extreme points can be used to accurately extract characteristic parameters, and the distribution of the characteristic parameters of the safety valves follows either a Gaussian or an exponential distribution. (2) The mining pressure analysis results, derived from the characteristic parameters, closely align with the in situ mining pressure observations. This method can be used for the online monitoring of safety valve conditions, increasing the operational efficiency and quality of safety valve inspections.

The precise detection of stratum interfaces holds significant importance in geological discontinuity recognition and roadway support optimization. In this study, the model for locating rock interfaces through change point detection was proposed, and a drilling test on composite strength mortar specimens was conducted. With the logistic function and the particle swarm optimization algorithm, the drilling specific energy was modulated to detect the stratum interface. The results indicate that the drilling specific energy after the modulation of the logistic function showed a good anti-interference quality under stable drilling and sensitivity under interface drilling, and its average recognition error was 2.83 mm, which was lower than the error of 6.56 mm before modulation. The particle swarm optimization algorithm facilitated the adaptive matching of drive parameters to drilling data features, yielding a substantial 50.88% decrease in the recognition error rate. This study contributes to enhancing the perception accuracy of stratum interfaces and eliminating the potential danger of roof collapse.

In deep coal mines characterized by high temperature, high humidity, high-salinity water, and elevated ground stress, stress corrosion cracking (SCC) of bolts is widespread, causing frequent instability of roadway surrounding rock and hindering long-term stability. This study systematically examines the failure characteristics of anchorage materials in highly corrosive roadways and clarifies the effects of deep-mine temperature and humidity on material corrosion. Long-term corrosion tests on bolts reveal changes in mechanical properties and macroscopic morphology and elucidate the intrinsic mechanisms of SCC. The results show that with the increase in corrosion time, the yield strength, ultimate load and elongation of the anchor rod decrease by up to 11.8%, 13.6%, and 7.08%, respectively. Under high stress, localized corrosion pits form on bolt surfaces, rupturing the oxide film and initiating rapid anodic dissolution and cathodic hydrogen evolution. Interaction between corroded surfaces and microcracks produced by internal impurities leads to progressive damage accumulation and ultimate fracture of the bolts. These findings provide guidance for corrosion protection of coal mine roadway support materials and for improving the long-term performance of roadway supports.

Measurement while drilling technology (MWD) has emerged as a pivotal approach for geological exploration. However, the accuracy of existing geological recognition models remains limited, primarily due to data fluctuations that result in high overlap rates and reduced reliability of drilling parameters. This study takes torque data as an example and analyzes the frequency distribution laws of torque responses across rock with varying strengths. A quantitative model of the frequency distribution characteristic interval is established, and a rock information prediction approach based on frequency distribution characteristics is proposed. The results indicate that torque frequency distributions for homogeneous rock exhibit a unimodal pattern, whereas those for composite rocks display multimodal characteristics. The boundaries of the frequency distribution characteristic intervals are mathematically defined as CIS = T_p|_{(dF/dT) = 0} ± σ and CIM = x_li ± 0.5∆x_i. The strength prediction model constructed using torque within the characteristic interval achieves an average accuracy of 85.3%. Furthermore, the frequency of torque within the characteristic interval enables the estimation of rock stratum thickness. This research contributes to enhancing the accuracy of rock information identification.

The pre-tightening force loss (PTFL) of bolts is an important but underestimated cause of roadway instability. In mine anchorage systems, the actual pre-tightening force of bolts is only 50% to 80% of the design value. Through a case study at Xiahuo Coal Mine, it was found that the essential causes of PTFL are the increasing friction coefficient between supporting units controlled by factors such as pre-tightening torque levels, pre-tightening cycles, and surrounding rock roughness. This study investigates the behavioral characteristics of PTFL and its influence on surrounding rock failure in roadways. This research reveals a linear correlation between pre-tightening force and torque, with an average torque conversion coefficient of approximately 0.19. However, the PTFL increases with higher levels of pre-tightening torque, increasing pre-tightening cycles, and rougher surrounding rock conditions. For every 30 N·m increase in pre-tightening torque, the PTFL increases by approximately 1.67 kN. Reducing the PTFL can expedite the stress redistribution process and shorten the self-stabilizing period of the roadway by approximately 10 days, thereby enhancing the active supporting potential of bolts.