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- 4Soft sensor
- 1Closed-loop identification
- 1Data quality assessment
- 1Ensemble Kalman filter
- 1Flat-topped Gaussian Distribution
The development of fast and efficient computer hardware technology has resulted in the rapid development of numerous computational software tools for making statistical inferences. The computational algorithms, which are the backbone of these tools, originate from distinct areas in science,...
Data Quality Assessment for Closed-Loop System Identification and Forecasting with Application to Soft SensorsDownload
In many chemical plants, data historians store thousands of variables at fast sampling rates. Much of this collected data is routine operating data that could easily be used for system identification and forecasting, especially in the design of soft sensors. Currently, there is no framework for...
In data-driven modelling, model accuracy relies heavily on the data set collected from target process. However, various types of measurement noise exist extensively in industrial processes and the data obtained are usually contaminated. If the influence of measurement noise is neglected, both the...
In many industrial processes, critical variables cannot be easily measured on-line: they are either obtained from hardware analyzers which are often expensive and difficult to maintain, or carried out off-line through laboratory analysis which cannot be used in real time control. These...