Inductive-Capacitive Dual-Mode Oil Detection Sensor Based on Magnetic Nanoparticle Material
Chenzhao Bai, Hongpeng Zhang, Wenqi Wang, Xupeng Zhao, Haiquan Chen, Naibin Zeng
Abstract
A new type of oil contaminant detection sensor based on a microfluidic chip is designed, which is mainly applied to the online detection and analysis of contaminants in oil system. The main innovation of this sensor includes the integration of inductance and capacitance detections. At the same time, magnetic nanoparticles are added inside the solenoid coil, to enhance the sensor detection sensitivity. Compared with traditional single-solenoid sensors, the double-solenoid sensor not only improves the detection accuracy, but also realizes multi-pollutant detection. We theoretically analyze the working principle of the sensor and build an experimental system for verification while the Scanning Electron Microscope (SEM) confirms the optimal concentration. The experimental results show that the sensor detection sensitivity with magnetic nanoparticles for inductance detection is improved by 19-24%, while the sensor can detect $20~\mu \text{m}$ iron particles and $80~\mu \text{m}$ copper particles. For capacitance detection, the detection accuracy is improved by 12-15%. The sensor can detect water droplets and air bubbles sized at 100_110 $\mu \text{m}$ and 150-160 $\mu \text{m}$ , respectively. The sensor design provides a new method for the rapid online detection of oil contaminants, which is significant for the life diagnosis and health monitoring of the oil systems.