Fouling detection/monitoring methods
Chen et al 2004 has a good review of these technologies. Summary:
Pressure Drop/Permeate Flux – current industry methods. Don’t work too well.
Direct Observation Through the Membrane (DOTM) – Li et al. 1998 – look at it with a microscope in real time. Enables you to estimate critical flux, size distribution of deposited particles. Cross-flow shear forces deter deposition of large particles. Critical flux increases with increasing cross flow velocity and particle size. Drawbacks – need to use a transparent membrane and position microscope under membrane.
Direct Visualisation Above the Membrane – Kang et al. (in press), Mores and Davis 2001 – provided valuable insights into the mechanisms of membrane cleaning.
Laser triangulometry – Altmann and Ripperger 1997 – a laser is bounced off the membrane, as the cake forms the angle of the laser will change. Cake thickness builds up to a maximum, but flux continues to decline. Additional factors such as cake structure could be affecting the flux.
Optical Laser Sensor – Hamachi and Mietton Peuchot 1999, 2001 – the cake will absorb light from a passing laser beam. Signal intesity of resulting beam is measured and used to calculate cake thickness. Cake thickness increased with increasing pressure, concentration and decreasing cross-flow velocity. Specific cake resistance is higher when filtering dilute suspensions, as they contain fewer large particles and hence form less permeable deposits. Resistance increases with pressure due to cake compaction. Porosity increases with thickness due to larger particle deposits (at odds with Altmann and Ripperger).
SilentAlarm™ – Saad 2004 – looks to be pretty crappy, based on industry standards compared with some unknown “correction factor”.
Ultrasonic Time Domain Reflectometry – Li et al 2002, 2006 – works well in comination with flux-decline monitoring. Good reaction to fouling removal. Early research aimed to measure thickness using time delay between incident and reflected signals, but this was not possible. Instead, the amplitude was used, but this is not quantitative. Li et al. fixed this but did not delve into quantitative studies.
Thermogravimetric – Tay et al 2003 – not much use for in situ monitoring, but shows that the fouling weight is proportional to resistance, and fouling rate is proportional to the concentration of the feed stock.
Impedance Spectroscopy – Coster et al. 1996, Chilcott et al. 2002 – “While the technique may be used to evaluate properties of fouled membranes, its application for in situ observation of the dynamics of fouling behavior is questionable.”
The last two methods focus on pore blockage rather than cake buildup. This is the irreversible stuff.
Small Angle Neutron Scattering (SANS) – Su et al. 1998, 1999, 2000 – changes in membrane pore structure can be monitored by detecting the changes in SANS intensity over time. The SANS intensity is unaffected by cake buildup, so it can be used in combination with another method to accurately identify the fouling mechanisms.
Characterisation of Cake Structure – Pignon et al. 2000, 2003 – Pignon et al. used static light scattering (SLS), SANS and local birefringence techniques to quantify the inner structure of the cake deposit.
The latest advancements in the fields of nanotechnology, microfluidics, optics, spectroscopy and sensors offer vast opportunities for development of robust in situ monitoring techniques in membrane filtration.
Thesis | stu | 
May 2, 2006 1:45 pm | 
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