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The FluidScan® 1000 series handheld Infrared oil analyzer provides direct quantitative measurement of a lubricant’s condition and plays an important role in Machine Condition Monitoring (MCM) for proactive and predictive maintenance in Reliability Management programs. It determines when oil needs to be serviced due to degradation of the oil chemistry or contamination by other fluids such as water or the wrong oil. It is compliant with ASTM D7889 “Standard Test Method for Field Determination of In-Service Fluid Properties Using IR Spectroscopy”.
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At the core of the FluidScan is a patented, mid-infrared spectrometer with grating optics and a linear detector array. The spectrometer collects the infrared light transmitted through the fluid in the flip top cell into a waveguide. The waveguide then carries the light to a prism-like diffraction grating that reflects the light into a high-performance array detector which registers the infrared spectrum of the fluid. It provides more than adequate spectral range, resolution and signal-to-noise ratio for the rapid analysis of in-service lubricants.
It also fulfils the National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion Engines (NESHAP RICE) requirements for extending oil change intervals in engines and back-up generators when used in conjunction with the Spectro MiniVisc 3050 Portable Viscometer.
One of the advantages of the FluidScan over laboratory FTIR is its ability to report absolute quantitative results for critical properties such as TAN and water contaminations for industrial lubricants or TBN, water, glycol, and soot for engine oils. Click here to view the different parameters provided by FluidScan depending on the oil type.
The FluidScan® classifies fluids into groups called families based on their chemical makeup, usage and spectral signature. The spectrum of all fluids in each family changes in a similar way with a given amount of degradation or contamination. Family-specific algorithms are assigned that accurately quantify these amounts. These algorithms yield quantitative results for the most critical properties of the most common oil types. Multivariate calibrations are applied so that quantitative readings can be obtained, even with complex, contaminated Samples
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