An LC Resonance-Based Sensor for Multicontaminant Detection in Oil Fluids

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Abstract
Most of the sensors currently used for wind turbine generator system oil detection can only perform measurements of a single physical quantity, and some sensors are capable of measuring multiple contaminants but require switching modes to achieve this, making it impossible to detect various oil contaminants simultaneously. These methods not only require the addition of numerous sensors and burden the wind turbine generator system piping, but also increase the time and cost of maintenance and inspection. In addition, it may be unable to respond quickly to specific emergencies. To address these limitations, this study proposes an LC-based passive dual solenoid coil multi-contaminant oil detection sensor. An analytical expression for the magnetic field strength of the dual solenoidal coil is derived, and a corresponding mathematical model is developed. The validity of the model is verified compared it with the finite element analysis results. An experimental verification was carried out. The experimental results show that the sensor can recognize multiple oil pollutants simultaneously according to different signal curves without switching modes. The sensor can detect iron particles with diameters larger than 38 μm, copper particles with diameters larger than 100 μm, liquid droplets with diameters larger than 100-110 μm, and air bubbles with diameters larger than 180-190 μm. By comparing with the existing sensors, the LC-based passive dual-coil multi-pollutant oil detection sensor proposed in this paper has a broad application prospect in real-time monitoring of wind turbine oil conditions.
Funding Information
  • Natural Science Foundation of China (52271303, 52301361)
  • Fundamental Research Funds for the Central Universities (3132023522)
  • China Postdoctoral Science Foundation (2023M730454)
  • Science and Technology Innovation Fund of Dalian (2022JJ11CG010)
  • Innovative Projects for the Application of Advance Research on Equipment (62602010210)

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