Structural Optimization Design Of Composite Sensor For Lubricating Oil Wear Particles

Oil monitoring technology is an important method to monitor the health of aeroengine. The majority of aeroengine failure was caused by abnormal wear parts with large grains generated, so monitoring the big wear particles in the lubricating oil can achieve fault diagnosis and early warning. The sensor output signals determine the type and location of wear, and then come to the health of the engine. During the narrow measurement range of current sensors, this paper puts forward the new composite sensor, whose measurement category is wider, based on the research of inductance and capacitance sensors.Firstly, three-coil inductive sensor and tricyclic electrode differential capacitance sensor are modeled respectively by finite element analysis software ANSYS. Secondly, the characteristic relationships are analyzed between the sensor output and particles parameters of different size, location, material etc. and structural parameters such as width, thickness, spacing, etc. And then the parameters are optimized of the sensor structure. Finally, put forward the new composite sensor, and achieve the optimal solution by the comparation of three composite schems.Simulation results show that the composite sensor output voltage and capacitance can reach the level of mV and pF respectively. Composite sensor can distinguish the conductive and non-conductive type, ferromagnetic and non-ferromagnetic particles, so it not only expands the monitor scope, providing a reliable basis for fault diagnosis and evaluation, but also indicates the possibility for information fusion. All the above experimental results demonstrate the feasibility and scientific value.