Rare-earth-doped strontium titanate ceramics yielding the formula Re 0.02 Sr 0.97 TiO 3 (Re-ST, Re = La, Sm, Gd, Er) were prepared by solid-state reaction route. All Re-ST ceramics had single cubic perovskite structure similar to pure SrTiO 3 (ST). The grain size of Re-ST ceramics dramatically decreased to 1-10 lm, depending on different rare-earth elements, as compared to~30 lm of pure ST. The relative dielectric constant of Re-ST ceramics (e r = 2750-4530 at 1 kHz) showed about 10-15 times higher than that of pure ST (e r = 300 at 1 kHz), whereas the dielectric loss of Re-ST ceramics still remained lower than 0.03 (at 1 kHz) at room temperature. Under 0-1.63 3 10 6 V/m bias electric field testing conditions, the e r of Re-ST ceramics at room temperature changed within 14%. The P-E results indicated that the Re-ST ceramics were linear dielectrics. Together with their relatively high breakdown strength (E b > 1.4 3 10 7 V/m), the Re-ST ceramics could be very promising for high-voltage capacitor applications. Meanwhile, the temperature stability of the e r of Re-ST ceramics was evaluated in a temperature range of À60°C-200°C.

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Residual useful lifetime (RUL) prediction plays a key role of failure prediction and health management (PHM) in equipment. Aiming at the problems of residual life prediction without comprehensively considering multistage and individual differences in equipment performance degradation at present, we explore a prediction model that can fit the multistage random performance degradation. Degradation modeling is based on the random Wiener process. Moreover, according to the degradation monitoring data of the same batch of equipment, we apply the expectation maximization (EM) algorithm to estimate the prior distribution of the model. The real-time remaining life distribution of the equipment is acquired by merging prior information of real-time degradation data and historical degradation monitoring data. The accuracy of the proposed model is demonstrated by analyzing a practical case of metalized film capacitors, and the result shows that a better RUL estimation accuracy can be provided by our model compared with existing models.