Diagnosis Method and Diagnosis System for a Processing Engineering Plant and Training Method

A training method for a diagnosis system comprising a processor, memory, and a storage device having a plurality of models, and confidences to be allocated to classifications stored therein, the processor being configured to provide a course over time of plant data which at least partially characterizes a status of a process-engineering plant, classify the status of the process-engineering plant aided by the plurality of models based on the course over time of the plant data, the plurality of models differing with respect to a time window, from which the plant data are based, allocate, in each case, one confidence to the classifications which result from the at plurality of models, and output diagnosis information which is based on the classifications the status of the process-engineering plant and a confidence allocated thereto, the method comprising:

• determining the plurality of models via machine learning;
• wherein the plant data of a first quantity of a plurality of courses over time from at least two different time windows and information with respect to a plurality of process-engineering plant statuses corresponding to the plurality of courses over time form a basis for the machine learning.