Multidimensional analysis of monitoring and diagnostic information on the technological process

Abstract

The study divides the analysis of monitoring and diagnostic information, leaving for monitoring the parameters of the stationary process, and for diagnostics -various transient regimes in the technological process. This, in turn, divides the algorithms of information processing into control of the output from the given boundaries for stationary parameters and the classification and prediction for dynamically changing parameters in a multidimensional space. In view of the large number of monitoring and diagnostic information, as well as due to different algorithms for processing it in an appropriate information system, it is necessary to apply multi-dimensional analysis methods. As diagnostic influences, various jumplike changes of a "natural character" are used, and the state of the equipment allows judging the apparatus of the influence functions. The abrupt changes in the technological process are reflected in the change in its parameters. The reaction to them is weakened as they are removed in accordance with the influence functions. The values of the parameters at the moment of the reaction define a point in the multidimensional parameter space and allow one to relate the state to one or another standard, and to relate the corresponding management algorithm to the standard. The experimental model includes five links simulating the operations of the technological process, a pulsed signal source simulating a step change and five links of propagation delay simulating the duration of operations. The results confirmed theoretical conclusions about the influence functions.

Multi-criteria security assessment of control and diagnostic data on the technological processes

“…-the vector of values of the modified exciting noise that determines the values Q at the (l+1)-th step. The equation for observing the process w ∆ at the (l+1)-th step of the TP (in our case, this is the deviation state of some CDI security indicator) is described by expression (4).…”

“…Various production technologies, using many different tools and equipment, collect and analyze large amounts of information characterizing the results of control measurements and diagnostics [1][2][3][4]. The accuracy and reliability of this information certainly affects the effectiveness of TP management.…”