There are various health issues associated with the different stages of long-distance pipeline transportation. These issues pose potential risks to environmental pollution, resource waste, and the safety of human life and property. It is essential to have real-time knowledge of the overall health status of pipelines throughout their entire lifecycle. This article investigates various health-monitoring technologies for long-distance pipelines, providing references for addressing potential safety issues that may arise during long-term transportation. This review summarizes the factors and characteristics that affect pipeline health from the perspective of pipeline structure health. It introduces the principles of major pipeline health-monitoring technologies and their respective advantages and disadvantages. The review also focuses on the application of Distributed Acoustic Sensing (DAS) technology, specifically time and space continuous monitoring technology, in the field of pipeline structure health monitoring. This paper discusses the process of commercialization development of DAS technology, the main research progress in the experimental field, and the open research issues. DAS technology has broad application prospects in the field of long-distance transportation pipeline health monitoring.

Slurry filling technology has been increasingly adopted in coal mines in the northwest region. However, due to the complexity of slurry transport pipelines, blockages remain a frequent issue. These blockages can reduce operational efficiency, with different blockage types causing varying levels of damage. Despite the significance of this issue, there is limited in-depth analysis in the literature, especially regarding the role of pressure in pipeline blockages. This study utilizes FLUENT 2020R2 (the fluid simulation software) for computational fluid dynamics simulations of slurry pipeline blockages, focusing on the impact of blockage morphology, location, and extent on slurry transport pressure distribution. The results indicate that the greater the blockage extent, the more pronounced the pressure loss along the pipeline. Furthermore, blockage morphology also has a varying effect on pressure drop. At lower blockage levels, the pressure drop variation across the three blockage types is relatively minor. However, when the blockage exceeds 50%, sedimentation-type blockages (B-blockage) cause the most significant harm. The study identifies the underlying causes of this and provides recommendations to mitigate sedimentation-type blockages. Within 1 m downstream of the blockage, the flow velocity rapidly decreases to near zero, creating a stagnant zone that accelerates the deposition of gangue particles, thereby worsening the blockage. After a sudden blockage, the location of the blockage has minimal impact on pressure drop. The influence on slurry pressure is ranked as follows: sedimentation-type blockage (B-blockage) > composite blockage (C-blockage) > attachment-type blockage (A-blockage).

Long-distance coal gangue slurry transportation pipelines are critical components of underground coal mine green backfilling systems, yet blockage failures severely threaten their safe and efficient operation. Existing distributed acoustic sensing (DAS)-based monitoring methods for such pipelines suffer from three key limitations: insufficient fixed-point quantitative accuracy, lack of verified blockage-specific characteristic indicators, and limited quantitative severity assessment capability. To address these gaps, this paper proposes a novel feature-level fusion monitoring method integrating DAS, fiber Bragg grating (FBG), and piezoelectric accelerometers for accurate blockage identification and quantitative evaluation in coal gangue slurry pipelines. A slurry pipeline circulation test platform with gradient blockage simulation (0% to 76.42%) and a synchronous multi-sensor monitoring system were developed. Through multi-domain signal analysis, three blockage-correlated characteristic frequencies were identified and cross-validated by synchronous multi-sensor data: 1.5 Hz (system background vibration), 26 Hz (blockage-induced fluid–structure resonance, verified by the Euler–Bernoulli beam theory with a theoretical value of 25.7 Hz), and 174 Hz (transient flow impact). The DAS phase change rate exhibited a unimodal nonlinear response to blockage degree, with the peak occurring at 40.94% blockage. On this basis, a sine-fitting quantitative inversion model was developed, achieving a high goodness of fit (R² = 0.985), and leave-one-out cross-validation confirmed its excellent robustness with a mean relative prediction error of 3.77%. Finally, a collaborative monitoring framework was built to fully leverage the complementary advantages of each sensor, realizing full-process blockage monitoring covering global blockage localization, precise quantitative severity calibration, and high-frequency transient risk early warning. The proposed method provides a robust experimental and technical foundation for real-time early warning, precise localization, and quantitative diagnosis of long-distance slurry pipeline blockages and holds important engineering application value for the safe and efficient operation of underground coal mine green backfilling systems.

Ground subsidence and shaft lining deformation caused by compressed dewatered bottom aquifers in deep unconsolidated strata mining areas are critical engineering challenges, making the study of the seepage–soil deformation coupling mechanism during groundwater injection remediation vital. This study built a visual cylindrical model (1025 mm × 150 mm); formulated well-graded analogous materials based on the D₂₀ principle to simulate sandy gravel layers; embedded FBG sensors at 200/400/600 mm depths, combined with a dial indicator on the model top; and conducted two water injection–dewatering cycles. Results indicate: water injection generates excess pore water pressure, placing the entire model in a tensile stress state with top rebound; post-injection vertical stress redistributes (tension above the injection point, compression below, and an interlaced transitional band), validating the necessity of full-section injection; during the second injection–dewatering cycle, tensile strain at the upper monitoring point reaches 597.77 με, while compressive strain at lower depths reaches −253.90 με, internal deformation stabilizes within 6.5–10.0 days, injection improves the in situ stress state by reducing effective stress, and the deformation of the field strata remains in a stabilization period, with the stabilization time decreasing as the depth of the strata increases. This study clarifies the temporal evolution and representative spatial variation in internal strain at monitored depths during injection, providing theoretical and design references for optimizing water injection schemes to mitigate coal mine shaft damage.

Slurry filling technology has gradually been adopted in coal mines in the northwest region. However, due to the complexity of slurry transport pipelines, blockages remain a frequent issue. Pipeline blockages can adversely impact production, reducing operational efficiency, with different blockage types causing varying degrees of harm. Despite the significance of this issue, there is limited in-depth analysis in the literature, especially regarding the role of pressure in pipeline blockages. This study utilizes FLUENT software for computational fluid dynamics (CFD) simulations of slurry pipeline blockages, focusing on the impact of blockage morphology, location, and extent on slurry transport pressure distribution. The results indicate that the greater the blockage extent, the more pronounced the pressure loss along the pipeline. Furthermore, blockage morphology also has a varying effect on pressure drop. At lower blockage levels, the pressure drop variation across the three blockage types is relatively minor. However, when the blockage exceeds 50%, sedimentation-type blockages cause the most significant harm. The study analyzes the reasons behind this and offers recommendations to mitigate sedimentation-type blockages. Within 1 meter downstream of the blockage, the flow velocity rapidly decreases to near zero, creating a stagnant zone that accelerates the deposition of gangue particles, thereby worsening the blockage. After an instantaneous blockage occurs, the location of the blockage has little effect on the pipeline's pressure drop. Among the three blockage types, the impact on slurry pressure in the pipeline is ranked as follows: sedimentation-type blockage > composite blockage > attachment-type blockage.

Distributed Acoustic Sensing (DAS) technology holds great potential for structural dynamic monitoring; however, its quantitative capability for complex dynamic strain fields and the reliability of spatial resolution require systematic verification. This study employed a systematic “theoretical modeling–simulation analysis–experimental verification” approach, using an equal-strength beam under sinusoidal excitation to investigate the dynamic response characteristics of DAS. A complete dynamic strain transfer model from external excitation to DAS phase-change signals was established, defining the phase sensitivity coefficient as a key parameter for quantitative analysis. Finite element simulations revealed that while the beam's strain is approximately uniform at low frequencies (< 5 Hz), it exhibits a gradient distribution—large near the fixed end and small near the free end—near the natural frequency, departing from the static “equal-strain” characteristic. Experimental results under 5 Hz excitation, utilizing synchronized measurements from accelerometers, FBG sensors, and DAS, demonstrated that DAS accurately captures the dominant vibration frequency. The measured phase sensitivity coefficient showed only a 4.82% error relative to theory, the response amplitude maintained high linearity with excitation and reference signals (R² ≥ 0.99), and the phase delay was negligible (0.02 rad). Furthermore, by comparing DAS channel response ratios across spatial positions with theoretical strain ratios, the study confirmed DAS’s ability to quantitatively resolve spatial differences in dynamic strain distribution. This work systematically validates the quantitative accuracy and reliability of DAS as a distributed dynamic strain sensing tool, and the revealed dynamic-static strain distribution differences, together with the established validation methodology, provide solid theoretical and experimental support for refined DAS-based monitoring in engineering structure dynamic monitoring scenarios.