Performance Degradation Prediction and Reliability Evaluation of Rubber Aging in Natural Environment Under Alternating Cyclic Thermal Load

Abstract

With a focus on predicting the degradation of rubber performance in the natural environment and evaluating its reliability, the distribution law of accelerated aging life is analyzed through the accelerated aging test of hot oxygen. A Weibull distribution model is then established to verify the consistency of the accelerated aging mechanism. Through the constant stress accelerated aging test data, the aging characteristics of the rubber under alternating thermal stress load in the natural environment are inferred. The concept of thermal stress amplitude coefficient is proposed, and its numerical value is calculated by the combination of numerical simulation and single-peak curve fitting. Under the principle of time-temperature equivalence, the segmentation time equivalent method and the overall temperature equivalent method are employed to calculate the rubber performance degradation curve under natural environment aging conditions. Finally, according to the Weibull distribution, the aging reliability of the rubber over time is simulated. This research can provide a reference for the aging reliability evaluation of products under alternating stress.INDEX TERMS Rubber, natural aging, alternating stress, thermal stress amplitude coefficient, Weibull distribution, reliability.

Modeling and Analysis of Performance Degradation Data for Reliability Assessment: A Review

“…Dating back to the 1880s, the Swedish scientist Arrhenius first proposed the Arrhenius relationship when he found that chemical reaction rates were approximately proportional to the applied temperature after conducting massive experiments. Since then, this physics-based acceleration model has received wide applications for incorporating the temperature stress in accelerated degradation modeling, and a large number of products are designed to damage by thermal stress, e.g., rubber [9], batteries [42], carbon film resistors [58], light-emitting diodes (LED) [59], and electrical connectors [35], [60]. In these cases, the Arrhenius relationship or its logarithmic-linear forms are the best choice for acceleration modeling [56], [61].…”

“…In the laboratory, the constant current is usually used to accelerate the degradation process of LED [2], [98], and film capacitors [3]. More applications of constant-stress loading can be seen in degradation analysis of sealing rubber rings [9], electronic connectors [61], and crack growth [99]. However, the variability of degradation models (e.g., the regression-based approach [100]- [102] and stochastic process [37], [103]) makes ADT planning complicated, especially when environmental stress factors, individual differences, and measurement errors, are considered.…”

“…For this reason, the selection of a suitable distribution model is quite essential. Among existing studies, the Weibull [9], [251], exponential [252], normal [151], [171], log-normal [253], skew-normal [151], [249], extreme-value [254], and Gamma distribution [255] have been widely used in the statistical analysis of performance degradation data. Moreover, some of these models can be transformed from others through pow law transformations.…”

“…In reliability engineering, the change of failure thresholds will directly impact the reliability assessment of a product (see (7), (9), and (12)). Therefore, it is regarded as a vital indicator of the concerned product in degradation modeling.…”

“…At the same time, the emergence of highly reliable products has also promoted the fast development of accelerated reliability tests for reliability assessment. For instance, AT methods have evolved from constant-stress [2], [3] to step-up-stress [4], step-down-stress [5], [6], progressive-stress [7], [8], and cyclic-stress approaches [9], [10]. Being exposed to higher stress levels, modern engineering systems will generate more unknown failure mechanisms, random uncertainties, and interactions, especially in multi-component systems [11].…”