Jul 2026· International Journal of Reliability, Quality and Safety Engineering (IJRQSE)· 0 citations
Abstract
Gear wear and fatigue often coexist under complex operating conditions. Their coex istence may bias reliability assessment and greatly increase the computational cost of time-varying reliability analysis. To address these issues, this paper proposes a dynamic multi-failure reliability analysis method for tooth surface wear, tooth surface contact fa tigue, and tooth root bending fatigue. First, the dynamic pressure angle is incorporated into the tooth surface wear model. A wear evolution model and a threshold limit-state function are then established by combining Archards wear law with Hertzian contact theory. Second, a Gamma stochastic process is used to describe the random strength degradation associated with contact fatigue and bending fatigue, and the degradation parameters are identified from the material probability-stress-life (P-S-N) curve. Third, Pearson correlation coefficients (PCCs) are introduced to describe the correlations among the basic random variables. Based on the moment information of the performance func tion obtained by second-order expansion, skewness and kurtosis are further used to construct an improved optimal squared approximation (OSA) probability density func tion for time-varying reliability computation. A high-speed stage gear of a belt-conveyor reducer is used as an example. The results show that the proposed method captures the reliability evolution of different failure modes and agrees well with Monte Carlo simulation (MCS) while reducing the computational cost.
This study presents an individualized inverse Gaussian process-based reliability modeling and optimal degradation test design for rubber V-belts, addressing the high cost, long duration, and data scarcity of traditional reliability demonstration testing (RDT). Degradation experiments on five B-type V-belts monitored slip ratio, tension force, and primer crack depth every 12 h, yielding lifetimes between 190 and 209 h (mean: 197 h). A stochastic degradation model incorporating individual heterogeneity was developed, with parameters estimated via Bayesian inference using Markov Chain Monte Carlo. By minimizing the asymptotic variance of the 0.1-quantile lifetime under cost constraints, an optimal RDT scheme was derived. Results show that when the asymptotic variance is below 0.0035, the relative error between estimated and actual lifetimes remained below 1.52%. The optimal plan—four samples, 18 measurements, and a 10-h interval—achieves high evaluation accuracy at a total cost of 7696 CNY. This work advances existing methods by explicitly modeling individual variability, justifying the inverse Gaussian process choice through empirical validation, and offering a practical, cost-efficient RDT framework extensible to other degradation-prone products.
Unknown authors· Proceedings of the Instituti...· 0 citations
Gear wear is a tribological surface damage process caused by contact loading and relative motion between meshing tooth flanks. It involves progressive material removal or transfer, changes tooth-flank topography, and consequently affects contact conditions, mesh stiffness, transmission error, and dynamic response. This paper reviews recent advances in gear wear research, including typical tooth-surface damage, wear prediction under various lubrication conditions, tribodynamic behavior, dynamic effects of wear, and the influence of assembly errors, parameter uncertainties, and gear modification on meshing characteristics. Existing studies have progressed from isolated descriptions of wear to integrated analyses involving lubrication, surface condition, and dynamics. Nevertheless, the long-term bidirectional coupling between wear evolution and tribodynamics remains insufficiently understood, while the effects of assembly errors and multi-source uncertainties have received limited attention. Gear modification studies have also focused mainly on initial transmission performance rather than its sustained role during wear degradation. Future research should therefore establish coupled wear–friction dynamic models and develop wear analysis methods that account for actual assembly conditions and parameter uncertainties.
The aging trend of the global civil aviation fleet has become increasingly significant, with a large number of in-service aircraft operating beyond their initial design service goals. Current deterministic damage tolerance analysis methods struggle to quantify the combined effects of multi-source uncertainties, including load randomness, environmental corrosion, and material dispersion, on structural safety. This study focuses on the fatigue performance evolution law and reliability assessment methodology of wing structures under coupled complex loads and environmental conditions. Through corrosion-fatigue coupling interrupted tests, damage constitutive modeling, time-dependent reliability algorithm development, and system reliability optimization design, this research aims to reveal the cross-scale cumulative mechanism of fatigue damage, develop efficient time-dependent reliability calculation methods for small failure probabilities, and construct a system reliability optimization theoretical framework considering failure path correlation. The findings will provide theoretical support for anti-fatigue lightweight collaborative design of next-generation civil aircraft, offer scientific evidence for aging aircraft life extension certification, and promote the transformation of aviation maintenance from scheduled inspection to condition-based maintenance.
Xun-Yi Wen· Frontiers in Science and Eng...· 0 citations
Fatigue failure is considered to be one of the most critical forms of failure in mechanically loaded associated components that are characterized by cyclic loading. It takes almost 80-90 percent of the failures of engineering structures and machine elements. Fatigue life estimation is a tricky and tough task due to the unpredictability of the fatigue crack initiation and propagation. In this paper, a detailed exploration of fatigue failure prediction of mechanical components has been developed in terms of experimental, analytical and computational as well. A review and a comparison of traditional stress-life (S ⁸ N), strain-life (ε N), as well as fracture mechanisms-based methods, are discussed, and contrasted with the recent data-driven and machine learning-based methods. The paper focuses on combination of finite element analysis (FEA), material characterization and probabilistic modeling in terms of better fatigue life prediction. It suggests a methodology based on a systematic approach to the problem with the analysis of stress, the model of damage accumulation, and verification with experimental results. To prove the efficiency of the proposed method, simulated case studies of common mechanical elements like shaft, gears, and welded contacts are provided. Findings show that cross-validation models that incorporate physics-based and data-driven methods are less inaccurate and reliable. The paper will be used as a framework of reference by the researcher and practicing engineers involved in fatigue study and structural durability evaluation.
Chen Wei· International Journal of Mod...· 0 citations
To support the surface wear evaluation of protective coatings on paper dryer, this study aims to characterize the long-term wear behavior of WC coatings and to quantify the wear depth by integrating stage-dependent tribological transitions into an efficient regression model.
A twin-roller rolling-sliding wear test was first conducted to investigate the wear evolution of the coating and to determine key tribological parameters, including the stage-dependent friction coefficient and wear rate. Subsequently, a three-dimensional dynamic finite element model was developed based on the experimentally determined parameters and the Archard wear theory to analyze the influence of operating variables on wear behavior. Finally, experimental and numerical results were integrated to establish a multivariate nonlinear regression model for quantitative wear prediction.
The results show that the WC coating exhibits a transition from severe mechanical wear to stable mild oxidative wear, and wear depth follows a power-law relationship with increasing service cycles under a constant normal load. The fitted model indicates a negligible sensitivity to sliding velocity.
This study develops a method for quantifying wear depth by incorporating stage-dependent wear parameters. The proposed approach provides methodological support for the wear assessment of protective coatings on paper dryer, facilitating timely surface maintenance.
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2026-0178/
Xiao-Kai Sun, Xuecheng Ping, Shuangge Yang et al.· Industrial Lubrication and T...· 0 citations
The fatigue performance of gears is very important to the safe operation of the transmission system. For gears fabricated using novel materials and advanced manufacturing processes, fatigue limit testing entails significant costs and prolonged timeframes, thereby constraining the rate of design iteration. In this paper, a rapid prediction method for the bending fatigue limit of gears is proposed. This method starts with the S-N curve of the material. Based on the rapid test theory and the principle of small sample statistics, combined with the step-down loading method, the safety fatigue limit of the gear under certain reliability is estimated. Compared with the up-and-down method, the error of this method is within 7.8%, verifying the feasibility of this data processing. At the same time, in this paper, the bending fatigue test of corrosion-resistant nitrided steel gears is carried out, and the bending fatigue limit of corrosion-resistant nitrided steel gears under 99% reliability is quickly obtained. This method holds significant engineering significance in saving test costs, reducing the number of tests, and shortening the development cycle. However, it is currently only applicable to standard spur gears and does not yet consider factors such as the geometric characteristics of helical gears and the corrosion resistance of materials.
