Multi sensor data fusion with flange mounted acoustic emission sensors in the monitoring of fluidised beds

Acoustic emission (AE) sensors screwed onto flanges of pipelines transporting particulate materials have been used in monitoring particle velocity. The sensor signals have been analysed in a data fusion scenario to give alarms in cases of particulate clotting, which often hinders the smooth transport of bulk materials in closed conduits. Furthermore the sensor signals were used in a correlation algorithm to estimate particulate velocity. The airflow is an established means of sustaining fluidised bed behaviour in bulk material transport. The sensors were integrated in a network using profibus technology. Independent airflow measurements and Computational Fluid Dynamic (CFD) simulations verified the particulate flow velocity. The sensor-networking scenario can be observed in a telematic set-up, which will be demonstrated during the presentation of this paper, if Internet access is available in the presentation room. This paper presents results from signal processing, sensor data fusion and some aspects of system integration. This is a collaboration between SIEMENS, Telemark, Te-Tek, Porsgrunn and Telemark University College. Part of the project was conducted within the context of a thematic network of the European Union, THEIERE. The Royal Norwegian Research Council supports Urmila Datta in this R&D effort.