tailieunhanh - Springer Verlag Soft Sensors for Monitoring P2

As regards the first block reported in Figure , a preliminary remark is needed. Generally, the first phase of any identification procedure should be the experiment design, with a careful choice of input signals used to force the process (Ljung, 1999). Here this aspect is not considered because the input signals are necessarily taken from the historical system database. | 28 Soft Sensors for Monitoring and Control of Industrial Processes fact past samples of the inferred variables could be available suggesting for using them in the model. At the same time high model prediction capabilities are mandatory. Figure . Block scheme of the identification procedure of a soft sensor As regards the first block reported in Figure a preliminary remark is needed. Generally the first phase of any identification procedure should be the experiment design with a careful choice of input signals used to force the process Ljung 1999 . Here this aspect is not considered because the input signals are necessarily taken from the historical system database. In fact due to questions of economy and or safety industries can seldom and sometimes simply cannot perform measurement surveys. Soft Sensor Design 29 This poses a number of challenging problems for the designer such as missing data collinearity noise poor representativeness of system dynamics an industrial system spends most of its time in steady state conditions and little information on system dynamics can be extracted from data etc. A partial solution to these problems is the careful investigation of very lengthy records even of several years in order to find relevant data trends. In this phase the importance of interviews with plant experts and or operators cannot be stressed enough. In fact they can give insight into relevant variables system order delays sampling time operating range nonlinearity and so forth. Without any expert help or physical insight a soft sensor design can become an unaffordable task and data can be only partially exploited. Moreover data collinearity and the presence of outliers need to be addressed by applying adequate techniques as will be shown in the following chapters of the book. Model structure is a set of candidate models among which the model should be searched for. The model structure selection step is strongly influenced by the purpose of the soft sensor .

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