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Zeitschriftenartikel:

C. Haiden, T. Wopelka, M. Jech, F. Keplinger, M.J. Vellekoop:
"A Microfluidic Chip and Dark-Field Imaging System for Size Measurement of Metal Wear Particles in Oil";
IEEE Sensors Journal, 16 (2016), 5; 8 S.



Kurzfassung englisch:
We present a dark-field video microscopy setup and microfluidic sample cell to detect suspended particles and measure their size. The microfluidic chip was fabricated by etching of shallow chambers in silicon and bonding with glass, thus achieving robust devices with low background signal for dark-field microscopy. The system is suitable for measuring particles in liquid media, such as metallic wear particles originating from lubricated tribocontacts in oil. Here, sample wear particles were generated in the laboratory by sliding a piston ring section against a cylinder liner section with a reciprocating tribometer using base oil (PAO8) as lubricant. Individual microparticles and nanoparticles are visualized by means of their scattered light, and sizes are determined by tracking of the diffusive Brownian motion in liquid. By heating the oil sample, the viscosity is reduced, which increases the extent of Brownian motion and facilitates tracking-based size calculations. The height of the microfluidic chamber was matched with the focal depth of the optical system, so that particles stay in focus during the whole measurement time. The resulting particle size distributions were monomodal and displayed a peak diameter of 230 nm, as confirmed by reference measurements with dynamic light scattering. Our approach represents a straightforward way to determine the size of microparticles and nanoparticles and has the potential for a continuous online operation. Compared with the state-of-the-art particle counters used in condition monitoring of industrial machinery, it is possible to detect much smaller particles and, therefore, allow early detection of wear before severe failure events take place.


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/JSEN.2015.2501355


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.