Performance experiment and numerical prediction of the copper based hair cell sensor for underwater sensing

Abstract

This paper demonstrates the performance experiment and numerical prediction of the copper based hair cell for underwater sensing. Generally, the hair cell consists of the single cantilever that attached perpendicular to the substrate and integrated with strain gage (Kyowa type: KFG-1N-120-C1-11). The hair cell sensor was simulated using different flow rates to study the pressure and the strain distribution acting on the sensor by using computational fluid dynamic and finite element analysis approach. High performance sensor can be achieved by increasing the length of the hair cell and also using low Young Modulus material. The hair cell has been fabricated for dimension of 8000 μm length, 2000 μm width and 100 μm thickness, where the copper was chosen due to its mechanical properties. The response time for a sensor to respond completely to a change in input is about 50 m/s and the sensitivity in terms of output voltage and input flow rate is 0.2 mV/ms-1. Also, the result obtained in the simulation is aligned with the experimental result. The experiment for moving object detection proved that this sensor is able to detect the moving object and it is necessary for underwater applications, especially for monitoring and surveillance.