The paper discusses the development of a soft sensor (SS) for an MTBE plant in the cases when the training sample either is small or does not comprise the whole of quality range because of process plant non-stationarity as well as the difficulty and high cost of retrieving more information. In order to build a soft sensor that provides higher accuracy in estimating the quality of the output product, an algorithm for extending the initial training sample using a rigorous model of the distillation column of the methyl-tert-butyl ether production under condition of exactly unknown values of the Murphree trays efficiency has been proposed. The resulting SS enables 40% improvement of product quality prediction.

本文讨论了在MTBE工厂的软传感器（SS）的开发中，如果培训样本由于过程工厂的不平稳性以及困难和高成本而导致培训样本很小或不包括整个质量范围的情况检索更多信息。为了构建一种软传感器，以在估算输出产品的质量方面提供更高的精度，该算法用于在完全未知的条件下使用严格的甲基叔丁基醚生产蒸馏塔模型来扩展初始训练样本已经提出了Murphree塔板效率的值。所得的SS可使产品质量预测提高40％。