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Coal Preparation

Sensor Development for On-Line Dynamic Simulation of Dense Medium Cyclones

Coal Preparation » Gravity Separation

Published: July 07Project Number: C15054

Get ReportAuthor: Peter Holtham | Julius Kruttschnitt Mineral Research Centre, University of Qld

C12001On-Line Simulation of a DMC Circuit
This project has shown that it is possible to make useful predictions of dense medium cyclone performance with a dynamic model of the DMC running side-by-side with the real plant. Two different DMC models were evaluated, the Wood coal washing model, and the Dunglison general purpose model. As might be expected both gave similar results, the Dunglison model is more complex and is also able to provide predictions of medium classification behaviour.

The models read operating data from the plant (medium density, feed pressure, feed tonnes) and predict cut point and Ep on a size-by-size basis at 10 second intervals. Other data such as underflow and overflow medium densities, and medium to coal ratio are also predicted. If reliable washability data is available, the models can estimate the cyclone yield and product and reject ash.

The project field work was carried out at Anglo Coal's Moranbah North CPP. The DMC models were linked to the one metre cyclones in both modules. An OPC client/server network link was used to read the data from the Moranbah North DCS. After an initial site visit to prove the concept, a second site visit was timed to coincide with a routine sampling audit undertaken by SGS. The models were run reading data and making predictions while the same cyclone was being audited.

The predicted results which were available immediately showed the cyclone tested had an overall cut point (12.5 x 0.71mm) of 1.742 and Ep of 0.033. The predicted yield was 92% and the ash 8.0% using two month old washability data. When contemporary washability data was used, the yield was 91% and the clean coal ash 7.8%. The audit results which were available two months later showed the cyclone had an overall cut point of 1.730, and an Ep of 0.031. Within experimental error these results are the same. Audited yield was 91.2% and ash 8.6%.

At present the model assumes the medium density and pressure signals are absolutely correct and that the cyclone is well maintained. Further development of this approach by making additional plant data available will improve the 'believability' of the model predictions, and allow for changes in operation that occur due to cyclone wear.

C13061 Sensor Development for On-Line Dynamic Simulation of Dense Medium Cyclones
 The objective of this project was to develop and test instrumentation to monitor dense medium cyclone (DMC) underflow or overflow medium density, as well as feed flow rate, as a check on predictions made by an on-line DMC model.  The project was a continuation of C12001, which demonstrated that two of the JKMRC’s DMC models could be linked to the DCS of an operating coal preparation plant to make continuous high quality predictions of DMC performance on-line.

The site test work was carried out at Anglo Coal’s Moranbah North plant.

Inputs to the models from the plant DCS were feed medium density, cyclone feed pressure and estimated DMC feed tonnage. The models and the plant ran side by side, with the model predicting actual cut point and Ep (on a size-by-size basis), medium to coal ratio, and medium underflow and overflow densities at 10 second intervals.

C15054 Sensor Development for On-Line Dynamic Simulation of Dense Medium Cyclones
This project  is the culmination of a series of projects with the overall aim of providing on-line process information from operating dense medium cyclones. In the projects a widely used and accepted DMC model was interfaced to the plant to read feed pressure, feed medium density and feed tonnes per hour. The model provides (at 10 second intervals) the following information: overall cutpoint and Ep, size-by-size cutpoint and Ep, overflow and underflow
medium densities, medium to coal ratios in the feed and products. If feed washability is reliably known, an estimate can be made of yield and product ash.

PC-based models are only as good as the input data. This project developed and tested in an extended plant trial, a Hall effect based sensor to estimate overflow medium density. The sensor value can be compared with the model prediction, which is normally very reliable.

The three-month plant trial showed that the sensor did indeed respond to changes in overflow density in a sensible manner, and provided a useful check on the model predictions. The trial only ended when the HDPE overflow pipe the sensor head was mounted on wore out. The model software and the electronics were still performing correctly.

It is recommended that ACARP consider further development of the sensor in order to reduce its size to the point where it can be incorporated under the ceramic lining of plant pipe work. ACARP might also consider a trial of all ACARP funded DMC sensor technology at a single site to assess whether the combined results provide information of value to operators and metallurgists.

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