Online Wear Particle Detection Sensors for Wear Monitoring of Mechanical Equipment?A Review
Large-scale equipment in the air transportation and military field requires real-time wear monitoring, especially monitoring of wear debris in the lubricating oil of the machinery and mechanical facilities. Online monitoring and analyzing feature parameters, like estimating the size and position of wear particles, are crucial to characterize the wear conditions.
Online monitoring systems are based on the principles of optical/imaging, electrical, ultrasonic, magnetostatic, electromagnetic, etc. Identifying the advantages and limitations of each of these principles is vital for optimizing the monitoring system.
The optical and imaging principle involves measuring the variation of light transmission by the lubricating oil in the presence of debris. In a direct imaging system approach, a CMOS camera identifies the shadow particles in lubricants to estimate the wear debris size. This technique can detect wear particles larger than 4 µm diameter. Measurement resolution can further be enhanced, and debris size of up to 2 µm can also be estimated through lensless optical microscopy involving a pinhole and a camera. Another method employs light-scattering, where a photodetector detects the scattered light. However, bubbles in lubricating oil could initiate false triggers, thus making the estimation of size unreliable.
Simple electrical wear monitoring involves capacitance change measurement. The permittivity of the lubricating oil changes in the presence of debris and leads to capacitance change. The method needs flow channels to realize the capacitor with lubricating oil as the dielectric and measure debris up to 25 µm diameter. Radio frequency-based monitoring is another electrical system where a part of the radio wave is absorbed, others get reflected, and the rest penetrates the lubricating oil in the presence of debris. The concentration of wear particles can be estimated based on the radio wave's transmission-reflection characteristics. However, the electrical system cannot distinguish ferromagnetic and non-ferromagnetic wear debris or identify the size of a single wear particle.
The ultrasonic principle of monitoring involves an ultrasound transmitter and receivers installed on the surface. The wear debris distorts the incident wave and generates a reflected wave. The strength of transmitted and reflected waves encodes the debris particle size information and can detect wear particles as small as 45 µm. However, it cannot differentiate between metallic and non-metallic particles.
A majority of mechanical components of machinery are made of steel. Magnetic sensors can be employed where a permanent magnet generates a static magnetic field. The flow channel is placed above the magnet, and a hall sensor detects the magnetic field strength on top of the channel. This method can only estimate the mass, not the particles' size. However, it can be resolved with a modified version with an inductive coupling coil, detecting particles as low as 81 µm in diameter. Static magnetic field-based techniques can only detect ferroelectric materials. It can be overcome by the alternating magnetic field-based approaches.
The detailed study identifies an in-situ integrated wear monitoring system with optical/imaging and magnetic principles as the most promising technology. Future research is moving towards an integrated wear monitoring system for multiple wear-information and intelligent wear particle detectors capable of wear monitoring, evaluation, and fault warning.