| 摘要 |
A diagnostic method for a process automation system composed of at least one field device, a control unit, and at least one fieldbus. The following method steps are included: in a learning phase raw data of measured variables, raw data of manipulated variables and/or raw data of state variables are stored. The field devices or the processes as input variables are registered and stored normalized. Moreover, in the learning phase at least one parameter, a measuring condition, at least one parameter of a process state and/or at least one parameter of a field device state as output variable predetermines, which corresponding output variables are the input variables associated with that which is stored, during the learning phase. A neural network formed by the input variables and the associated with output variables, in the learning phase are the causal relationships between the ascertained input variables and the corresponding, specified output variables by a transfer function of the neural network ascertained and stored, in an operating phase is by means of the transfer function from the current raw data the field devices as input variables at least one change of the current measuring condition, the current process state and/or the current field device state ascertained. |
