Performances evaluation and characterization of a novel design of capacitive sensors for in-flight oil-level monitoring aboard helicopters

Capacitive sensing is one of the most used sensing techniques for a large variety of applications. In particular, Capacitive Level Sensors (CLSs) are well suited for avionics, as they provide continuous measurements over the full range of the sensor, high reliability and low maintenance costs. However, industry standard CLSs used nowadays on helicopters show low sensitivity and poor dynamical characteristics. Hence, novel geometries were investigated and the simulation results (already presented in a previous manuscript) were encouraging. Therefore, three prototypes were built and tested. This manuscript is aimed at their experimental validation obtained using a mechatronic testbench with a high-precision positioning system purposely designed and built, able to move the probes in and out of an oil tank. The used oil had well-known electrical characteristics and many different tests were carried out. With the obtained data of capacity vs. oil level, an in-depth analysis of the probes' static (sensitivity, non-linearity, hysteresis) and dynamic (rise time, settling time, final error) behaviors were performed. From the analysis results it can be clearly seen that the novel design featuring a helicoidal slit along the external electrode of the cylindrical probe provides increased sensitivity, improved first-order response and negligible hysteresis phenomenon and non-linearity error.

Automated summary

Capacitive sensing is a widely used technique for a variety of applications, including avionics. However, current industry standard Capacitive Level Sensors (CLSs) used in helicopters perform poorly in terms of sensitivity and dynamic characteristics. In this study, novel geometries were explored and three prototypes were built and tested. Experimental validation showed that the new design featuring a helicoidal slit along the external electrode of the cylindrical probe improved sensitivity, response time, and linearity.