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COMPUTER-IMPLEMENTED METHOD AND SYSTEM FOR AUTOMATICALLY MONITORING AND DETERMINING THE STATUS OF ENTIRE PROCESS SEGMENTS IN A PROCESS UNIT

  • US 20170082988A1
  • Filed: 12/05/2014
  • Published: 03/23/2017
  • Est. Priority Date: 12/05/2013
  • Status: Active Grant
First Claim
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1. A computer-implemented method for monitoring installation parts which are connected by process engineering and comprise one or more process units, having the following steps:

  • in step a), M process parameters to be monitored and their measurement range limits are input at a user interface and are forwarded to a module for defining the process unit,in step b), learning data phases consisting of potential learning vectors are imported to a database module,in step c), in the database module, N learning vectors from the learning phases from b) are alternatively automatically selected via the user interface using the measurement range limits from step a),in step d), the learning vectors from step c) are transmitted from the database module to a model module connected to the latter;

    in the model module, a model based on a neural network is generated by assigning each learning vector to a best matching unit defined by its M process parameters and adapting the best matching units to the learning vectors in a self-organizing neural map,in step e), the following features of the model are automatically calculated;

    for each of the N learning vectors, a deviation error as the distance between each process parameter value of a learning vector and the corresponding process parameter value of the best matching unit assigned to it,for each of the N learning vectors, a total deviation error as the sum of the deviation errors of its M process parameters,in step f), the total deviation error for each learning vector from step e) is transmitted to a module for analysing the deviation errors and a minimum and a maximum value of the calculated N total deviation errors are automatically determined there,in step g), in order to monitor the process units, the M process parameters monitored online are automatically transmitted, as the monitoring vector of the process unit over time, to the database module at a time stamp t followed by the transmission of the monitoring vector to the model module,in step h), each monitoring vector from step g) is automatically assigned to the best matching units of the neural map (SOM) from step c) in the model module by comparing the process parameter values of the monitoring vector with the process parameter values of each neuron in the neural map and making a selection on the basis of the shortest distance,in step i), the deviation errors and the total deviation errors of the monitoring vector are calculated,in step j), the total deviation error of the monitoring vectors is transmitted to the module for analysing the deviation errors, is assigned in comparison with the minimum and maximum values of the calculated N total deviation errors from f), and the assignment is displayed via the user interface.

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