In soft-sensing technique, much attention has paid to the evaluation and optimization of secondary variables. But little attention has been paid to the problem how to choose suitable secondary variables, which is still open and seems difficult. Based on extension methods, which study the laws for opening-up things and solving incompatible problems, the paper presents a new kind of inferential estimator called extension inferential estimator, which integrates the routine inferential estimator with an extension regulator. In the extension inferential estimator, five extension methods for choosing secondary variables are developed: (1) to consider the measurement object and its transformation; (2) to consider the characteristic and its transformation; (3) to consider the measure and its transformation; (4) to consider the measurement principle or method and its transformation; (5) to consider the measurement tool or component and its transformation.

Soft-sensing technique based on extension method

In this paper, the applications of artificial neural network(ANN) in wastewater treatment quality control are reviewed. The main applications include three fields: to predict the effluent quality, such as the concentration of COD, N and P; to soft sensing some parameters hard to measure on site, such as BOD; to measure some parameters more accurately, such as heavy metals. In combination with the developing trend of the researches, the future developing direction of ANN is analyzed.

The application of artificial neural network in wastewater treatment

Soft-sensing technique in process industry is introduced. General theory and methods about building a soft-sensing model are given. Problems related to soft-sensing technique in coal-fired power plant are discussed. Analysis of two implementation instances show that soft-sensing is an effective way to solve problems in sensing and control of complicated process variables.

Soft-sensing Technique and its Application Foreground in Coal-fired Power Plant

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Soft-sensing Technique and its Application Foreground in Coal-fired Power Plant