Sand filters waiting to be installed.

By J.W. Wouters, A. de Boer and J. van Pol

Moving bed biofiltration is a continuous operation. Biofilter media cleaning is continuously taking place while the filter is in operation. Moving bed biofilters (MBF) are used both in process and drinking water production and wastewater polishing. Thousands of plants have been equipped with various makes of MBF, functioning in a wide variety of applications.

One essential feature in moving bed biofiltration is the homogeneous sand circulation over the full filter area. Due to the continuous sand circulation, the filtration process is time-independent. With a constant feed water quality, filtrate quality will also be constant. Actual sand circulation rate affects the filtration efficiency for both solids removal and biological conversion processes in the filter bed. Monitoring and controlling the actual sand circulation rate is key to optimizing plant performance and reducing malfunctions and down-time.

RFID tagging

Methods to monitor and control moving bed biofiltration plants have been quite basic and required regular operator involvement.

A new method, called Sand-Cycle, uses RFID tags to monitor the movement of sand grains in a MBF. RFID tagging is an ID system that uses small radio frequency identification devices (RFID) for identification and tracking purposes. An RFID tagging system includes the tag itself (the transponder), a read device, and a host system application for data collection, logging, processing and transmission. A passive RFID tag is briefly activated by the radio frequency scan of the reader. The electrical current is small, generally just enough for transmission of an ID number.

The electronic identification system consists of two basic elements: the transponder and the reader. The transponder (ID tag) is mixed up with the sand grains in the filter bed. It contains no batteries and is hermetically sealed in a housing designed to survive harsh environmental conditions. It is completely maintenance free and has an unlimited life span.

The reader energizes the transponder by means of an electromagnetic field, which is emitted by the antenna. It then receives the code signal returned by the transponder and processes it. The reader excites the transponder inductively by means of a polarized low frequency electromagnetic field. Transponders can be read irrespective of their orientation and are detected while passing by a reader, which is integrated in the airlift structure. The codes, dates and times of the passing transponders are transmitted to a decoder, collecting the data from multiple readers. The decoder is connected to a data logger, equipped with a general packet radio service (GPRS) modem to transmit data to the back end of the online data server.

The Sand-Cycle data server converts the raw field data into relevant output data, by using dedicated algorithms. Output is available 24/7 for operators via the data server front office and is presented in various dashboards.

Sand-Cycle dashboard with health indicators provides 24/7 real-time monitoring.
Sand-Cycle dashboard with health indicators provides 24/7 real-time monitoring.

Real time monitoring of MBFs in water and wastewater treatment plants is an example of the potential of big data. It is a first step towards linking various datasets and finding relationships to make the process work better at varying operating conditions. The ultimate goal is to increase reliability (reducing plant failures) and optimize plant performance. It also initiates options for advanced filter control, resulting in higher performance.

Process optimization

At present, most continuous biofiltration plants are operated at more or less arbitrary sand circulation rates. As a consequence, the media circulation time is non-optimal.

The filter performance of a continuous biofilter is non-optimal at both low and high media turnover times. At low turnover times the sand is washed frequently and hence the filter is operated in “clean-mode”. A filter which is operated with pores partially filled with solids and/or biomass is capable of retaining more solids or biologically converting more organic matter.

At high turnover times, however, the filter bed resistance will increase and eventually breakthrough of solids will occur.

The filter should be operated between these two extremes. As the sand circulation can effectively be controlled by the amount of air supplied to the airlift, it is possible to operate the plant in the right range.

Economy behind RFID monitoring

Figure 1. Continuous sand filter savings from the use of Sand-Cycle
Figure 1. Continuous sand filter savings from the use of Sand-Cycle

In the last 20 years, numerous surveys have been executed on moving bed biofiltration plants in order to optimize plant performance and to initiate refurbishment. Based upon these surveys, an overall picture emerges of the consequences of plant malfunctioning. Essentially four parameters may be quantified in this respect:

  • Operator attendance for regular manual monitoring of sand circulation rates and washer assembly. Lack of regular attendance is most often the reason for malfunctioning. Real-time monitoring is assisting in the day-to-day inspections and will reduce the operator’s time to inspect the plant to a minimum.
  • Sand loss directly impacts plant performance and sand wash-out might block piping downstream of the plant. Identifying sand loss at an early stage will prevent this and help avoid regular sand top ups.
  • Energy (compressed air) for operating the airlift is continuously consumed. Due to wear and tear of the airlift, energy consumption is increased. Hence, timely detection of the status of the airlift helps to keep the energy input for the plant operations within limits. Long-term trends will indicate the actual airlift status and allow the operator to replace the airlift in time.

Field surveys have revealed downtime of moving bed biofiltration plants occurs due to any of the reasons indicated above. This results in temporarily reduced effluent quality and deterioration of the annual average performance of the plant.

Implementation of RFID monitoring tools shows a consistent reduction of costs associated with these parameters, resulting in returns of investment of typically one to two years. In Figure 1, the general savings are quantified in function of plant capacity (in litres per second). The colored bars indicate the particular savings on manpower (blue), energy (green), downtime (orange) and sand loss (purple). The blue line in the graph indicates the net savings over a 25-year filter plant lifetime.

Big data represents a huge opportunity to improve equipment reliability and reduce maintenance and refurbishment costs. The advantage of cheap wireless technologies means that sensor information can now be transferred wirelessly. Operation warnings and diagnostics can be shared quickly.

J.W. Wouters is with BW Products BV, The Netherlands. A. de Boer is with Brightwork BV, The Netherlands.
J. van Pol is with Ingu Solutions, Canada. This article appears in ES&E Magazine’s April 2017 issue.



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