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.
Milling chatters caused by the regenerative effect is one of the major limitations in increasing the machining efficiency and accuracy of milling operations. This paper studies robust active chatter control for milling processes with variable pitch cutters whose dynamics are governed by multidelay nonlinear differential equations. We propose a state feedback controller based on linear matrix inequality (LMI) approach that can enlarge multiple stability domains in the stability lobe diagram (SLD) while the controller gain is minimized. Numerical simulations of active magnetic bearing systems demonstrate the effectiveness of the proposed method.
Three-dimensional (3D) reconstruction of human body has wide applications, for example, for customized design of clothes and digital avatar production. Existing vision-based systems for 3D body reconstruction require users to wear minimal or extreme-tight clothes in front of cameras, and thus suffer from privacy problems. In this work, we explore a novel solution based on a sparse number of soft sensors on a standard garment, and use it for capturing 3D upper body shape. We utilize the maximal stretching range by modeling the nonlinear performance profile for individual sensors. The body shape can be dynamically reconstructed by analyzing the relationship between mesh deformation and sensor reading, with a learning-based approach. The wearability and flexibility of our prototype allow its use in indoor/outdoor environments and for long-term breath monitoring. Our prototype has been extensively evaluated by multiple users with different body sizes and the same user for multiple days. The results show that our garment prototype is comfortable to wear, and achieves the state-of-the-art reconstruction performance with the advantages in privacy projection and application scenarios.
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