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Browse AllIn response of the stringent requirements of high-resolution optical remote sensing satellites for attitude control stability and micro-vibration environment, this study focuses on the friction dynamics modeling and simulation analysis of large-angular-momentum flywheels across a wide speed range. To quantify the impact of flywheel friction disturbances on satellite attitude pointing accuracy, friction torque characteristic data were first acquired through ground testing over the full speed range, and a high-fidelity static fitting mathematical model was constructed using the least squares method. To further elucidate the nonlinear friction mechanisms in the low-speed regime—particularly during speed zero-crossings—the LuGre dynamic friction model was introduced, and its core parameters were identified and optimized. Comparative results demonstrate that the model exhibits high-precision characterization capabilities, with a deviation of less than 0.0015 Nm from measured data within the critical low-speed range of ±50 rpm. Subsequently, the established friction model was integrated into a satellite attitude control closed-loop system for digital simulation to quantitatively evaluate the disturbance of friction torque on system steady-state accuracy. The results indicate that under the closed-loop control compensation mechanism, the impact of flywheel friction on satellite attitude pointing accuracy is effectively suppressed, with the attitude angle deviation maintained within 0.002°, thereby meeting the engineering requirements for high-precision remote sensing imaging. This research provides a theoretical basis and data support for the optimization design of flywheel systems and the refined design of satellite attitude controllers.
Real-time monitoring of metal wear debris in lubricating oil is crucial for accurately assessing aerospace equipment health and preventing catastrophic mechanical failures. Although three-coil differential inductive sensors are widely used due to their high sensitivity and robust structure, their detection performance inevitably degrades under the influence of multi-physics coupling effects inherent in complex industrial environments. Existing analytical models were primarily limited to single electromagnetic field simulations, failing to capture the intricate electromagnetic-thermal-mechanical interactions, which reduced analytical accuracy and hindered the optimization of sensor designs for extreme conditions. To overcome these challenges, this study established a comprehensive parametric simulation model to conduct a rigorous electromagnetic-thermal-mechanical coupled analysis of the differential sensor. Specifically, the research analyzed the underlying mechanisms by which wide temperature variations from -55 °C to 200 °C and specific debris kinematics exert varying degrees of influence on the induced voltage. Quantitative results indicated that both the isolated thermal and mechanical fields altered the voltage by a maximum of 0.649%, demonstrating that the sensor maintains a relatively stable response across extreme thermal gradients. Furthermore, the analysis revealed that increased debris velocity decreased the induced voltage amplitude due to the intensified motion-induced eddy current effects. Notably, in complex multiple debris scenarios, the strong dominant signals generated by ferromagnetic wear debris severely masked the weaker responses from non-ferromagnetic ones, indicating a substantial missed detection risk under mixed contamination conditions. Ultimately, this research successfully filled the critical simulation gap for evaluating these sensors under multi-physics coupling, providing robust theoretical guidance for their reliable deployment in complex industrial applications.