Monitoring methods, computer program product, monitoring unit, gas analysis device, and use of artificial intelligence
AssigneeSiemens Aktiengesellschaft
InventorsJana Eder, Simon Weilandt, Ralf Bitter, Stephanie Holly, Tim Offermann, Daniel Schall, Piotr Strauch
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Abstract
A computer program product, a monitoring unit, gas analysis device equipped with the monitoring unit, use of artificial intelligence for monitoring the gas analysis device, and monitoring methods for a system having a plurality of devices which are configured to provide an associated measured value and/or a control command, wherein the monitoring methods are based on the use of a processing device or a neural network, with which measured values and/or control commands are evaluated.
Claims11
A monitoring method for a gas analyzer having a plurality of devices, which form nodes in a neural network, which maps an interaction of the devices in the gas analyzer, the method comprising:
- a) providing a trained neural network having a plurality of edges which each correspond to a zero correlation or an operating correlation, a correlation value being determined during training for zero correlations, and the correlation value having a value which is below an adjustable correlation threshold value;
- b) placing, by a controller, the gas analyzer into an active operating state and capturing, by the controller, at least one of measured values and control commands, each measured value and control command corresponding to least one of (i) at least one node and (ii) at least one edge of the neural network;
- c) determining, by the controller, a network deviation parameter which combines correlation values of a plurality of edges of the neural network, the correlation values being determined utilizing at least one of the measured values and control commands captured during step b);
- d) identifying, by the controller, an abnormal operating state of the system, if a value of the network deviation parameter exceeds an adjustable network threshold value, a warning being issued if the abnormal operating state is identified;
- and
- e) identifying an edge of the neural network which corresponds to the zero correlation in a normal operating state as a defective edge, if a value of the correlation value associated with the identified edge exceeds the associated correlation threshold value;
- and
- f) initiating a countermeasure during the active operating state of the gas analyzer to increase an efficiency of error detections within the gas analyzer based on a reduced computational load when the value of the correlation value associated with the identified edge exceeds the associated correlation threshold value such that the identified edge of the neural network which corresponds to the zero correlation in the normal operating state is identified as a defective edge.
A non-transitory computer readable medium encoded with a computer program which, when executed by processor of a monitoring unit for monitoring a gas analyzer which has a plurality of devices which interact to operate the gas analyzer, causes at least one of measured values and control commands to be captured and processed, the program comprising:
- a) program code for establishing a trained neural network having a plurality of edges which each correspond to a zero correlation or an operating correlation, a correlation value being determined during training for zero correlations, said correlation value have a value which is below an adjustable correlation threshold value;
- b) program code for placing, by a controller, the gas analyzer into an active operating state and capturing at least one of measured values and control commands, each measured value and control command corresponding to least one of (i) at least one node and (ii) at least one edge of the neural network;
- c) program code for determining, by the controller, a network deviation parameter which combines correlation values of a plurality of edges of the neural network, the correlation values being determined utilizing at least one of the measured values and control commands captured during step b);
- d) program code for identifying, by the controller, an abnormal operating state of the gas analyzer, if a value of the network deviation parameter exceeds an adjustable network threshold value, a warning being issued if the abnormal operating state is identified;
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- e) program code for identifying an edge of the neural network which corresponds to the zero correlation in a normal operating state as a defective edge, if a value of the correlation value associated with the identified edge exceeds the associated correlation threshold value;
- wherein a countermeasure is initiated during the active operating state of the gas analyzer increase an efficiency of error detections within the gas analyzer based on a reduced computational load when the value of the correlation value associated with the identified edge exceeds the associated correlation threshold value such that the identified edge of the neural network which corresponds to the zero correlation in the normal operating state is identified as a defective edge.
Dependencies are inferred from the claim text.