In order to accurately analyze the motion characteristics of nanofluid
particles in the flow state, a method for micro-motion analysis of nanofluid
particles based on machine vision was proposed. The influence of temperature
on the micro-motion of nanoparticles was studied by establishing a
water-based near-wall flow simulation model of nanofluids, and the
Lennard-Jones potential parameters of nanofluids were obtained. Machine
vision imaging technology is used to establish a reference system for
nanofluid particles micro-motion image acquisition. Based on this system,
the micro-motion images of nanofluid particles are collected, and the
micro-motion characteristics of nanofluid particles are accurately
detected. An experimental measuring platform composed of optical system and
electronic system is established. The rotational and translational motions
of nanoparticles and the velocity and temperature distributions of
nanofluids are obtained. It was found that the velocity gradient of the
nanofluid near the wall was higher than that of the base liquid, and the
temperature of the nanofluid near the wall was significantly higher than
that of the single-phase base liquid. The experimental results show that
the velocity and temperature distributions of nanofluids at different
temperatures can be obtained by using this method.
Analysis of micro-motion of nanofluid particles based on machine vision
