Coal mine roadways provide necessary underground space for personnel and equipment transportation, and mining operation, the reliability of which is critical for safe and efficient daily of operation of coal mine. Due to the impact of rock burst and coal mining movement, the deformation of roadway surrounding rock is more and more common in the process of coal mining, and has gradually become a high-risk factor that affects and restrains the development of high-quality coal mines. Given this, this work proposed an innovative regional measurement method of surface displacement of coal mine roadway based on D laser scanning technique. In the proposed method, point clouds of roadway from different phases are obtained in combination with the proposed approach of denoising and simplification, and the global deformation analysis of the point cloud is further carried out. Finally, the regional surface displacement distribution is acquired to realize the quantification of surrounding rock deformation. The proposed method has been applied in the actual environment of coal mine in northwest China, and reaches ideal measurement performance in different working conditions, including mining roadway, preparation roadway, and permeant roadway. Results show that the absolute errors of surface displacement measurement in three kinds of roadway environment are 0.2363 cm, 0.21 cm, and 0.4138 cm, respectively. The proposed measurement method also exhibits a resolution of better than 2 cm, which is sufficient for warning of roadway surrounding rock deformation.

The planetary gear transmissions driven by permanent magnet synchronous motor (PMSM) are prone to coupled dynamic failure mechanisms arising from frequency resonance and long-term tooth-surface wear. This paper presents an MRGP-based dynamic reliability framework for a permanent-magnet planetary gear transmission system (PMPGTS) that explicitly accounts for these mechanisms. A unified electromechanical model is first established by integrating PMSM electromagnetic torque and current control with a planetary gear dynamic model and a wear-dependent time-varying mesh stiffness (TVMS). On this basis, a multi-mode limit-state vector is constructed to describe resonance and wear failures across discrete wear stages. To overcome the prohibitive cost of Monte Carlo simulation (MCS) on the high-fidelity model, an active-learning multi-response Gaussian process (MRGP) surrogate is developed, which simultaneously approximates all limit-state components and is adaptively refined using a combined U-function and expected feasibility function (EFF). A benchmark example demonstrates that the proposed surrogate method attains a relative error of about 0.23% with only about 40.4 high-fidelity evaluations. Application to the PMPGTS over a [0-20] year service interval shows that early-life failure is dominated by resonance induced by high-order mesh harmonics, whereas late-life reliability is governed by tooth-surface wear, with the wear failure probability approaching 0.97 at 20 years. The proposed MRGP-based dynamic reliability framework provides an efficient tool for life-cycle dynamic reliability assessment and for guiding the design of geometry in PMPGTS.

Stray current corrosion is the main and most serious form of corrosion suffered by subway shield tunnels,1 which is induced only when the environmental Cl- concentration of reinforced concrete structure (RCS) reaches a threshold value. Hence, accurate monitoring of ambient Cl- concentration of RCS is crucial for early warning of stray current corrosion in shield tunnels. In view of this, an artificial intelligence-assisted predictive method was proposed to conduct the monitoring of Cl- concentration based on electrochemical noise (EN) measurement. The proposed model effectively constructs the regression relationship between Cl- concentration and EN signal characteristics by means of key features extraction. This work mainly highlights the practicality and interpretability of the XGBoost-based model in environmental Cl- concentration prediction. The implementation of the explainable AI technique also helps to reveal the EN signal features that have the most obvious impact on Cl- concentration. Results show that EN signal of RCS under stray current interference with different Cl- concentration show significant differences in both time domain and frequency domain. Key features, including mean value, skew, kurt, white noise level (WL), total energy of D4 ~ D6 layers (E2), and total energy of D7 ~ D9 layers (E3), were extracted as the input variables of the XGBoost-based model by means of training contribution rates. Compared with other concentration prediction algorithm, the proposed model exhibits superior performance advantages in terms of prediction accuracy and stability, and can reach an average prediction accuracy of 92.95 %, an RMSE evaluation index value of 0.046, and a prediction resolution of at least 0.1 mol/L, showing a potential application value for health monitoring and reliability assurance of RCS.

Stray currents pose a significant threat to the structural health and resilience of subway shield tunnels through the destructive effects of electrochemical corrosion, which is broadly recognized as one of the main obstacles to ensuring the sustainability of urban rail transit systems. Environmental humidity can lead to variations in the pore water saturation of concrete structures. In the coupled environment of stray currents and pore water saturation, this condition exacerbates the corrosion of reinforced concrete, shortening its service life and jeopardizing the normal operation of subway systems. Given this, a combined study is carried out to explore the effect of pore water saturation on stray current corrosion of reinforced concrete through FEM-based simulation and experiment tests. The effect of pore water saturation on stray current corrosion is studied by varying applied potential and porosity. The study validates the influence of concrete porosity and voltage on the control ranges of pore water saturation corresponding to the various stages of stray current corrosion in reinforced concrete. Based on the simulation and experimental results, it is concluded that, under the same voltage conditions, an increase in the porosity of the reinforced concrete correlates with a greater severity of corrosion as pore water saturation increases. As the applied voltage increased from 2 V to 10 V, the pore water saturation range for iron oxidation shrank from 0-0.6 to 0-0.4, while the hydrogen evolution range expanded from 0.7-1 to 0.5-1. Pore water saturation influences the control mechanisms of electrochemical corrosion at various stages in reinforced concrete. Moreover, under each control mechanism, the control ranges of pore water saturation corresponding to the corrosion stages demonstrate sequential trends of contraction, movement towards lower saturation regions, and expansion as the applied voltage increases. The findings of the study contribute to the understanding of the intrinsic mechanisms underlying the service life extension of buried foundation structures.

This study presents a novel electrochemical noise (EN)-based data mining approach for non-invasive measurement of environmental chloride ion (Cl−) concentration in reinforced concrete structures (RCS) exposed to stray current interference. A custom experimental system captures EN signals from mortar-embedded steel rebars under varying Cl− concentrations (0.05–0.9 mol/L) and stray current densities (0.05–0.1 A/cm²). Time-domain statistical features and frequency-domain wavelet-decomposed energy parameters are extracted from EN signals as regression inputs. To overcome the complexity of signal-environment relationships, an intelligent algorithm (WOA-XGBoost-Attention) is proposed, integrating Whale Optimization Algorithm (WOA) for hyperparameter training, XGBoost for regression, and an attention mechanism to weight critical features dynamically. Validation shows the model achieves 95.33% average accuracy and a 0.9929 correlation coefficient (R2) for Cl− prediction, significantly outperforming benchmark methods (XGBoost, Random Forest, etc.). The framework enables early warning of stray current corrosion by detecting critical Cl− thresholds, offering a robust solution for monitoring subway shield tunnel durability where traditional methods are impractical.

With the extension of urban rail transit systems, more and more buried gas pipelines will suffer from stray current interference due to contact with adjacent metro systems. Stray current interference will generate a hydrogen evolution reaction through cathodic current flow, which leads to severe hydrogen embrittlement hazards on pipeline steel. In this work, we used scanning electron microscopy to obtain the morphology of fracture surfaces, which is ascribed to hydrogen embrittlement for Q235 pipeline steel under stray current interference, considering varying defect area and environmental pH value. The fracture surfaces were then quantitatively characterized by multifractal methods, including multifractal spectrum and generalized fractal dimension. A novel method was proposed to accurately describe the surface morphology of hydrogen-induced fracture by combining spectral width A alpha and generalized dimension threshold width ADq . The results indicate that HE fracture surfaces of Q235 pipeline steels under stray current interference show obvious self-similar and multifractal characteristics. Moreover, multifractal spectrum f ( alpha)-alpha and generalized fractal dimension D ( q )-q exhibit high-accuracy performance in depicting the roughness and homogeneity of complex fracture surfaces, considering varying defect area and environmental pH value. Spectral width A alpha and generalized dimension threshold width ADq show a good negative correlation with hydrogen embrittlement susceptibility. The underlying mechanism was analyzed through the energy-absorbing effect during the transition process from ductile to brittle fracture. The findings of this research offer a new perspective that describes the fracture surface through probability distribution. The proposed approach provides a potential application for hydrogen embrittlement susceptibility evaluation through an on-site screening technique. (c) 2025 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.

The support bearing of permanent magnet synchronous motor (PMSM) is a key component of permanent magnet direct-drive system (PMDDS), and its reliability plays a critical role in the operational efficiency and safety of PMDDS. Existing PMSM bearing studies typically rely on static assumptions, neglecting time-varying reliability and degradation modeling. This study comprehensively considers the effects of electromechanical coupling and hybrid eccentricity of the PMSM rotor, investigates the evolution of bearing dynamic loads under varying system parameters and operating conditions, establishes a reliability assessment model for PMSM bearings, and proposes a dynamic reliability evaluation and sensitivity analysis method based on the active learning kriging (ALK) method. The results show that the proposed method greatly reduces calls to the actual performance function and provides highly accurate prediction results. Furthermore, the simulation results reveal the effects of various system parameters on the dynamic reliability of PMSM bearing. This study can provide a reference for the time-varying reliability prediction of PMSM bearings and the optimized design of PMDDS.

The low-speed, high-power permanent magnet semi-direct-drive sprocket system (PM-SDDS) exhibits electromechanical coupling characteristics, and its vibration analysis is complex due to internal and external excitations and varying operating conditions. This study integrates the effects of controller parameters, inverter and flux linkage nonlinearities, gear meshing nonlinearities, and the sprocket polygonal effect (SPE), establishing a state-space-based torsional dynamics model applicable to various operating conditions. The impact of controller parameters and load variation on system modal characteristics is analyzed, along with vibration responses under typical conditions. The results show that changes in the speed-loop proportional gain Kpw affect the first-order natural frequency fn,1 through the electromagnetic (EM) effect, while load variations impact fn,1 by altering the system's mechanical characteristics. The SPE introduces low-frequency excitations into the system, with its intensity varying under changes in lumped mass and motor speed. Transient free vibrations at fn,1 are observed both during heavy-load startup and upon sudden load changes. The second harmonic of the meshing frequency 2fm is the dominant frequency for exciting second- and third-order torsional resonance, with modulation sidebands |fe±2fm| appearing in the stator current. Under sudden load changes, sideband clusters modulated by fn,1 appear near the gear meshing harmonics, accompanied by |fe±fn,1| modulation sidebands in the current spectrum. This work provides a theoretical guidance for torsional resonance monitoring and dynamic characteristics analysis of the PM-SDDS.

Purpose Stray current generated from rail transit system poses great integrity threat on surrounding buried metal pipelines, especially for oil and gas pipelines. Apart from corrosion damage, hydrogen damage will also occur in widely distributed cathode area on the pipeline surface due to locomotive operating conditions and location. However, limited studies focus on the hydrogen permeability characteristics of Q235 pipeline steel under stray current interference. The purpose of this paper is to study hydrogen permeation behavior of Q235 steel under stray current interference from urban rail transit system. Design/methodology/approach Since hydrogen permeation is prerequisite for inducing hydrogen damage, this study deals with hydrogen permeation behavior of Q235 pipeline steel under direct stray current interference. Besides, the impact of surface defect and pH value on the hydrogen permeation behavior was also studied with electrochemical techniques. Nonlinear fitting was conducted with high accuracy to explore the quantitative relationship between hydrogen permeation process and influencing factors. Findings Experimental results show that stray current flowing into metal substrate could obviously promote hydrogen permeation process, and surface defect and decreasing pH value could also enhance hydrogen permeation effect. Hydrogen penetration kinetic parameters: hydrogen flux J and diffusion coefficient D were found to be positively correlated with increasing amplitude of stray current density and area of surface defect, and negatively correlated with the increasing environmental pH value. Originality/value This study clarifies main influencing factors of external environment on the hydrogen permeation under stray current interference. Experimental results of this study are of great significance for daily maintenance of buried gas pipelines adjacent to rail transit system and prevention of hydrogen-induced cracking from the perspective of influencing factors.

The harsh underground environment during coal mining operations leads to fluctuations in the internal parameters and external loads of the permanent magnet semi-direct drive (PMSD) scraper conveyor system, imposing greater demands on the speed control of the permanent magnet synchronous motor (PMSM). To this end, this paper proposes an improved sliding mode controller (ISMC) for PMSM speed control in the semi-direct drive scraper conveyor. First, an improved sliding mode reaching law (ISMRL) is proposed, which introduces the power term of the sliding mode surface and the variable speed adjustment function into the constant-speed switching term and the exponential approaching term of the exponential approaching law (ESMRL), respectively, and replaces the traditional switching function with the hyperbolic tangent function. It is verified through theoretical analyses and examples that this method allows the system state to reach the sliding surface faster and more smoothly from any initial state. Furthermore, for the uncertain disturbance in the speed control of the PMSD system, an adaptive sliding mode disturbance observer (ASMDO) that does not depend on the disturbance boundary information is proposed based on a double-layer adaptive algorithm. It can change the observer input and achieve fast and accurate disturbance estimation, which is then compensated to the ISMC. Then rigorous theoretical analyses demonstrate the stability of the ISMC and ISMC+ ASMDO closed-loop control system. Finally, the results show that the proposed method improves the robustness, response speed and steady state performance of the PMSD speed control system.

Corrosion is one of the most dangerous factors affecting the structural integrity of buried metal pipelines, which is mainly caused by the defects of external anti-corrosion layer. Therefore, it is significant to acquire the coating defects location in service in time to ensure the safety and reliability of buried metal pipelines. In view of this, an advanced method for accurate locating coating defects of long-distance transmission buried metal pipeline proposed by combining electrochemical impedance spectroscopy (EIS) and close interval potential survey (CIPS), and experimentally validated in this work. EIS measurement was to initially determine whether there exist coating defects in the target pipe segment, and CIPS test was further to achieve high precision location within the range of pipe segment where the location and number of coating defects have been initially determined. Experimental results show that the location and number of coating defects leads to the impedance to exhibit different characteristics compared that with intact coating, and conventional corrosion factors won't cause fundamental changes in impedance characteristics. The proposed method is proved to be effective in locating coating defects within the range of experimental pipe segment. The novelty of this work lines in the proposal an efficient positioning method for long-distance pipeline coating defect combining EIS and CIPS, and correlation model between characteristic parameters of EIS results and coating defect location information.

With the extension of urban rail transit systems, more and more buried gas pipelines will suffer from stray current interference due to inevitable interactions with transportation lines. Stray current interference from adjacent urban rail transit system poses an increasingly significant risk of hydrogen embrittlement on buried gas pipelines in addition to external electrochemical corrosion. This type of fracture failure caused by hydrogen embrittlement is hidden and sudden, and the safety risks it poses cannot be ignored. In view of this, an experimental study on hydrogen embrittlement of Q235 pipeline steel is conducted under stray current interference. In this work, typical influencing factors: local deformation on the steel surface and environment pH are both considered along with the synergistic effect of stray current interference. Slow strain rate tensile testing combined with scanning electron microscopy is carried out to explore the differences in hydrogen embrittlement sensitivity, risk level, and micromorphology under stray current interference due to deformation area and environmental pH. The results reveal that, under stray current interference, both increasing deformation area and decreasing pH value leads to higher hydrogen embrittlement sensitivity and risk level. Under low level of stray current interference, the influence of local deformation on the steel surface on hydrogen embrittlement sensitivity is greater than that of environmental pH value. Besides, under synergistic effect of stray current interference, the hydrogen embrittlement fracture morphology shows obvious morphological changing pattern and fractal characteristics.

The hazard of stray current attracts more and more attention due to the potential infrastructure failure caused by the electrochemical corrosion. In view of the poor insulation performance and lack of stray current collection system in the metro depot, stray current leakage becomes particularly evident in this area. In order to evaluate the corrosion risk of buried metal pipeline surrounding metro depot, an assessment model for interference scope induced by stray current is proposed in this paper. The distribution of stray current is calculated based on the resistive network by considering different boundary conditions in different areas of metro depot, and the interference scope is assessed by surface potential gradient for corrosion risk of corroded pipeline. Moreover, the characteristics of surface potential gradient distribution in different areas of metro depot and the influence of electrical parameters are analyzed. Finally, the proposed model is verified through simulation and experimental results.

Rail-to-earth transition resistance characterizes the amplitude of stray current leakage in urban rail transit system using electric traction, which is critical for evaluating failure risk of metal infrastructures caused by electrochemical corrosion. However, detection method commonly used in the field exhibit measurement errors resulting from the limitation of measuring principle and measuring distance, which will seriously affect the accuracy of electrical insulation performance evaluation of the whole system. In view of this, this paper proposes a data-driven method for accurately measuring rail-to-earth transition resistance in urban rail transit system based on CDEGS-based simulation and SSA-optimized algorithm. CDEGS model was built to construct database for machine learning of SSA-RF network structure. SSA algorithm was used in the measurement model to optimize the topology of the random forest (RF) structure. Proposed ensemble in this paper was proved to conduct transition resistance regression with a mean relative accuracy rate of 98.85 %. Results of sensitivity analysis indicate that proposed measurement method shows acceptable robustness, which allows the algorithm parameters to fluctuate within a certain range when applied in the field. Besides, in the case of uniform and non-uniform insulation degradation, the proposed method shows good performance in assessing insulation performance. This provides a feasible foundation for future applications of the proposed method in failure risk evaluation of buried infrastructures.

As the gradual emergence of alternating current (AC) electrified rail transit system in urban areas, buried gas pipeline adjacent to the system will be seriously corroded by induced alternating stray current. These buried gas pipelines are at serious risk of electrochemical corrosion, which leads to safety and environmental threaten. In order to study the distribution of alternating stray current corrosion on pipeline surface on a larger spatial scale, this paper conducted numerical simulation and experimental validation of alternating stray current corrosion of buried gas pipeline. In the numerical simulation model, coupling between different physical fields are realized through the relationship between current density of pipe-to-soil interface, electrolyte, and electrodes. Proposed numerical method based on coupled multi-physics in this paper are in good agreement with experimental results under different influencing factors. A novel evaluation index was proposed to assess the corrosion risk within different zones on the pipeline surface. Results show that corrosion distribution is greatly influenced by spatial interaction between buried pipeline and rail transit system including crossing angle and parallel distance. Besides, alternating stray current corrosion on buried gas pipeline are proved to be both affected by dynamic characteristics due to AC fluctuation and operation mode of locomotive.

Electrochemical corrosion induced by leakage current from the running rail in DC subway system, the stray current corrosion, is a threat that can't be ignored to the transportation pipeline near the metro line system. In view of the corrosion problem caused by stray current in the subway, this paper discusses the evaluation of simulated direct stray current interference on Q235A metal in two types of electrolytes (solution or soil environments), which is often employed as the pipeline steel. Instrumental methods employed in this study to conduct the electrochemical analysis includes Tafel polarization, electrochemical impedance spectroscopy, SEM scanning and EDS scanning to analyze the main electrochemical parameters for the assessment of corrosion resistance during the stray current corrosion process, which is carried out in electrolyte solution and soil environment, respectively. The EIS of electrolyte solution and soil environment (10 min-30 min) exhibits the same equivalent electronic circuit. The electrochemical results were also compared with two different experimental environments to exhibit a degree of similarity. Results also show that the charge transfer resistance Rct decreases and corrosion current density icorr increases in both electrolyte solution and soil environment, which indicates a reduction of corrosion resistance during the experimental period of this study.

Dynamic stray current leads to severe electrochemical corrosion on rock bolt in large cross-section subway tunnel. It's important to evaluate the corrosion risk of corroded rock bolt based on monitoring signal. In this paper, an experiment for half-cell potential measurement of rock bolt under dynamic stray current interference was carried out. Tested non-stationary half-cell potential signal was analyzed the dynamic characteristics of half cell potential in time and frequency domain. Herein, two parameters: potential shift & UDelta;E and time ratio rt, were put forward to capture the characteristics of half-cell potential signal. A probabilistic-based analysis method was therefore proposed to quantify the corrosion risk of non-stationary half-cell potential, in which PDF of potential shift signal was fitted by generalized extreme value (GEV) function and kernel density estimation (KDE) technique. It is found that location parameter mu in GEV and the sum of the absolute values of the PDF derivative S(d )could effectively represent potential shift and time ratio in half-cell potential signal respectively.

The cutting transmission system is always subjected to multi-frequency load excitation due to the complicated working conditions of shearer. Under this condition, the multi-frequency load excitation not only affects the torsional vibration response of the transmission system, but also induces various resonance cases. Thus, the oversimplification of excitation may lead to large errors in the dynamic response of the transmission system and further result in the inaccuracy of the torsional vibration analysis. According to the Lagrange principle, a simplified two-inertia electromechanical coupling torsional vibration model for the rotor system is established considering the electromagnetic excitation as well as the multi-frequency load excitation. Then, the resonance response of the rotor system is solved by the multiple scales method, and a parametric study is conducted to reveal the effects of electromagnetic excitation and load excitation on the amplitude–frequency response, respectively. In addition, other possible resonance cases (combination resonance and combination subharmonic resonance) are also discussed in this research. Finally, by utilizing the Runge–Kutta method, the numerical simulation is carried out to verify the validity of the analytical solutions and the reliability of the proposed dynamic model. The results indicate that the presence of the multi-frequency load excitation introduces the interaction between various harmonic excitations, which significantly change the vibration behaviors of shearer semi-direct drive cutting transmission system.

To reveal the features of the gear wear and failure correlation on the system reliability, comprehensive consideration of PMSM characteristics, gear internal structure and load torque, the permanent magnet gear transmission system dynamic model is established based on the motor theory and Maxwell equation. The gear variable amplitude fatigue load spectrum is statistically analyzed by rain flow counting method and Goodman theory. On this basis of nonlinear damage theory and modified P-S-N curve, the dynamic reliability of gear single failure mode considering the number of random loads and strength degradation is predicted. Finally, based on the Copula function, the change regularities of the system dynamic reliability are analyzed by using the relationship between the correlation function and reliability.

Stray current corrosion poses threaten to gas pipelines, and corresponding test method provides effective preventions to limit the damage. Three-electrode system has limitations in terms of convenience and economy in the practical application. Thus, this work aims to develop a novel non-destructive testing method of corrosion current density in the presence of stray current, in which a network-based model is proposed to realize highaccuracy measurement. An interdisciplinary approach is presented by combining electrochemical laboratory measurements with data-driven technology to predict corrosion current density. An innovative algorithm combining neural network with Levy Flight Weighted Quantum Particle Swarm Optimization is proposed to predict corrosion current density through non-destructive input factors. Results demonstrate that proposed approach improves algorithm performance significantly, including mean accuracy rate (AR) and stability. The best mean AR of corrosion current density is 94.11 %, enhancing the performance by 7.35 % to 18.16 % in comparison to other network-based algorithm.