ABSTRACT
Polymer-derived ceramic (PDC)-based high-temperature thin-film sensors (HTTFSs) exhibit promising applications in the condition monitoring of critical components in aerospace. However, fabricating PDC-based HTTFS integrated with high-efficiency, high-temperature anti-oxidation, and customized patterns remains challenging. In this work, we introduce a rapid and flexible selecting laser pyrolysis combined with a direct ink writing process to print double-layer high-temperature antioxidant PDC composite thin-film thermistors under ambient conditions. The sensitive layer (SL) was directly written on an insulating substrate with excellent conductivity by laser-induced graphitization. Then, the antioxidant layer (AOL) was written on the surface of the SL to realize the integrated manufacturing of double-functional layers. Through characterization analysis, it was shown that B2O3 and SiO2 glass phases generated by the PDC composite AOL could effectively prevent oxygen intrusion. Therefore, the fabricated PDC composite thermistors exhibited a negative temperature coefficient in the temperature range from 100 to 1100 °C and high repeatability below 800 °C. Meanwhile, it has excellent high-temperature stability at 800 °C with a resistance change of only 2.4% in 2 h. Furthermore, the high-temperature electrical behavior of the thermistor was analyzed. The temperature dependence of the conductivity for this thermistor has shown an agreement with the Mott's variable range hopping mechanism. Additionally, the thermistor was fabricated on the surface of an aero-engine blade to verify its feasibility below 800 °C, showing the great potential of this work for state sensing on the surface of high-temperature components, especially for customized requirements.
ABSTRACT
Remotely piloted unmanned combat aerial vehicle (UCAV) will be a prospective mode of air fight in the future, which can remove the physical restraint of the pilot, maximize the performance of the fighter and effectively reduce casualties. However, it has two difficulties in this mode: (1) There is greater time delay in the network of pilot-wireless sensor-UCAV, which can degrade the piloting performance. (2) Designing of a universal predictive method is very important to pilot different UCAVs remotely, even if the model of the control augmentation system of the UCAV is totally unknown. Considering these two issues, this paper proposes a novel universal modeling method, and establishes a universal nonlinear uncertain model which uses the pilot's remotely piloted command as input and the states of the UCAV with a control augmentation system as output. To deal with the nonlinear uncertainty of the model, a neural network observer is proposed to identify the nonlinear dynamics model online. Meanwhile, to guarantee the stability of the overall observer system, an adaptive law is designed to adjust the neural network weights. To solve the greater transmission time delay existing in the pilot-wireless sensor-UCAV closed-loop system, a time-varying delay state predictor is designed based on the identified nonlinear dynamics model to predict the time delay states. Moreover, the overall observer-predictor system is proved to be uniformly ultimately bounded (UUB). Finally, two simulations verify the effectiveness and universality of the proposed method. The results indicate that the proposed method has desirable performance of accurately compensating the time delay and has universality of remotely piloting two different UCAVs.
