Institute of Particle Process Engineering

AiF-Project "sensoric process monitoring of reverse osmosis systems" (21335 N)

November 01, 2020
Contact: Marc Weirich
Funding: Aif

The use of intelligent inline analysis and data processing methods enable to link information in order to accommodate options and guidance to ensure an optimal reverse osmosis process with regard to operational safety, (predictive) maintenance and cost reduction.

A major detoriation mechanism can be observed in membrane fouling. Organic, bio and colloidal fouling such as scaling are to be distinguished. Since colloidal foulants of 1 nm to 2 µm cause most irreversible degradation of the membrane, resulting in a decline system efficiency. Accordingly, the application of countermeasures in the form of pretreatment or demand-controlled backflushing promise enormous improvements. State-of-the-art measurement devices require the extrusion of samples and process know-how of a technican on-side. These offline methods cause a time delay and only detect particles above 450 nm hence are not compatible with a fully automated system control. Considering the lack of reliable inline particle metrology for these particle sizes, in the scope of this project the usability of the SE (statistical extinction)-Method will be examined in laboratory scale. The SE-Method describes a laser-based metrology adopting a laser beam through a particulate medium. The shading or extinction of the light beam provides a indication of the particle concentration and mean diameter. The extinction results from the transmission, which represents the ratio of light intensity entering and leaving the probe. Intelligent data analysis of the fluctuating transmission signal allows to monitor the characteristics of the particulate medium as small particles cause minor peaks than larger particles particles in the transmission signal. Previous investigations showed the influence of the wavelength of the light beam and the ratio between disperse and continious phase on the calculated particle size.

Further investigations will provide data for the availability of the dynamic extinction spectroscopy (DES) in nano scale. The DES is based on the dependency of the wavelength of the light beam and the measurable extinktion. Original studies showed particles below 1 µm extinct short-wave light significantly more than long-wave light. In order to measure the particle size, the ratio between two or more extinction rates of different wavelengths of the light beam has to be interpreted. From the collected data a modular inline sensor integrating SE-Method and DES will be designed and implemented in a pilot plant.

The methods and data from this project form the basis for future decision support tools or highly advanced process automation solutions.

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