A novel on-line alumina concentration measurement system

The concentration of alumina in the electrolyte is of great significance during the production of aluminum; it may affect the stability of aluminum reduction cell and the current efficiency. However, the concentration of alumina is hard to be detected online because of the special circumstance in the aluminum reduction cell. At present, there is lack of fast and accurate soft sensing methods for alumina concentration and existing methods can not meet the needs for online measurement. In this paper, a novel soft sensing method based on the voltage between the anode and the cathode, the current of the anode rod and the modified extreme learning machine for online measurement of the alumina concentration is proposed. In order to achieve the soft sensing scheme, considering the problems on the work spot, such as anode effect, the paper mainly develops a system that can realize the online measurement of the voltage between the anode and the cathode. The hardware of the system is composed of three parts including protection circuit, filter circuit and data acquisition card. When the anode effect occurs, the protection circuit which is used to ensure the safe use of the acquisition device will switch off the connection between the voltage and the data collection card. When the voltage returns to normal level, it will switch on the connection. The modified ELM algorithm is based on the enhanced random search which is called incremental extreme learning machine in some references. It randomly chooses the input weights and analytically determines the output weights without manual intervention. The experimental results show that the approach can give accurate estimations of alumina concentration within 6 percent relative error.