Automatic Wear Particle Classifier - SpectroLNF Q200
Application
- Machine Condition Based Monitoring
Description 
Wear particles that contaminate lubricating oil can carry important information that can be used to understand the condition of a machine. Because of this, it is important to monitor and analyze these particles along with their generation rate. Machine condition information can be obtained through an analysis of wear particle size, shape, and concentration. Traditionally, a Ferrogram Maker is used to isolate particles in an oil sample to then be classified based on size, shape, and composition. Preparing a ferrogram slide can be a time consuming process and the analysis requires much knowledge about wear particle characteristics to accurately classify them. Using the SpectroLNF, classification is done quickly and automatically using an advanced technology that classifies particles based on size and shape characteristics. The SpectroLNF Q200 is easy to use and requires no extensive instrument knowledge needed to obtain an automatic accurate wear particle analysis.
The SpectroLNF Q200 operates using a technique known as direct imaging. This technology is similar to taking a photo with a digital camera. A laser is used to illuminate the sample in flow cell. As the sample is illuminated, a CCD (charge coupled device) captures the images.
These images are then sent to an artificial neural network for processing to determine the size and the shape of the particle to be used for the total particle count as well as the final classification of the particle. Also, the SpectroLNF Q200 is able to distinguish between non-metallic and metallic particles. Particle counts are completed on all particles between 4µm to greater than 100µm in size. A wear particle classification is provided for particles that are 20µm or greater. Particles are classified in one of four wear categories: cutting wear, sliding wear, fatigue wear, nonmetallic wear. 
The SpectroLNF Q200 is also capable of classifying whether a particle is a fiber (such as a piece of the filter), a water droplet, or an air bubble which can interfere with the overall particle count. Because air bubbles are classified, any bubble greater than 20µm will be automatically eliminated from the total count to provide a more accurate particle count.
Benefits
- A fast and automatic way to pre screen samples
- Classification helps to define wear modes and wear severity leading to early detection of machine failures
- Water contamination is detected through a classification of water droplets
- An expert in Ferrography is not needed to perform sample analysis
- Establish alarm limits through an automatic calculation of the dynamic equilibrium
Product Information and Applications