LaserNet Fines®-C, Particle Shape Classifier and Particle Counter
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Application
- Machine Condition Based Monitoring
Description
The LaserNet Fines®C (LNF-C) is a bench-top analytical tool that combines the oil analysis techniques of particle size analysis and particle counting in one instrument. The LNF-C analyzes hydraulic and lubricating oil samples from various types of equipment and machinery that are part of a machine condition-monitoring program. The monitoring is based primarily on the morphological analysis and the particle size distribution of the abnormal wear particles that are created from the internal components of the machine. The operator is presented with an assessment of particles found in the fluid sample and a history of previous results for the same equipment. LNF-C can be used as a stand-alone analytical instrument, or in conjunction with a full service oil analysis program.
As a particle size analyzer, the LNF provides the user with shape recognition of all particles greater than 20 µm by using a neural network. An algorithm sorts particles into the following categories: cutting, fatigue, severe sliding, nonmetallic and fibers. The shape recognition software also does a test for circularity so that bubbles and droplets greater than 20 µm are eliminated from the particle counting results.
As a particle counter, the LNF processes and stores thousands of images to obtain good counting statistics. Particles are sized directly and results can be displayed by ISO 4406 Code (>4µm, >6µm, and >14µm), or several military codes. The direct imaging capability of this instrument eliminates the need for calibration with a test dust. Air bubbles greater than 20µm are ignored and the laser is powerful enough to process heavily sooted (black) oils.
Analytical Test
- Shape classification
- Particle counting
- Soot
Features and Benefits
- Particle count is an indication of a fluid’s cleanliness.
- Data outputs include particle type identification, image maps, size trends and ISO, NAS, and NAVAIR cleanliness codes.
- Algorithms to perform shape analysis, wear particle identification and machine condition assessment.
- Large particles are classed by a neural network as “cutting, fatigue, severe sliding, nonmetallic, free water droplets or fibers”.
- Provides image maps of all particles greater than 20 µm.
- Automatic adjustment for fluid darkness; sees through black diesel lubricating oils.
- Built-in data-base for machine condition trending.
- Magnification is set at factory. Recalibration is never required.
Product Information and Applications