Method for determining state information relating to a belt grinder by means of a machine learning system
AssigneeRobert Bosch GmbH
InventorsWolfgang Pleuger, Thorsten Klein, Thomas Kipfer, Johannes Fischer, Matthias Amann, Helena Kuppke
Life of this patent
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Abstract
A method determines state information relating to a belt grinder. The belt grinder has at least one abrasive belt for grinding a workpiece. The method includes providing measurement data relating to the belt grinder, and determining the state information from the measurement data using a machine learning system. The machine learning system is configured to determine the state information based on the provided measurement data.
Claims20
A method for determining state information relating to a belt grinder, the belt grinder having at least one abrasive belt for grinding a workpiece, the method comprising:
- generating measurement data relating to the belt grinder;
- and
- determining the state information from the generated measurement data using a trained machine learning system, wherein the trained machine learning system includes a plurality of steps and configured to determine the state information based on the generated measurement data, wherein the plurality of steps comprising:
- providing training data comprising training input data and training output data, wherein the training input data comprise measurement data relating to (i) a belt grinder for a plurality of pieces of state information, and (ii) at least two belt grinders of different types, at least two belt grinders of the same type with a different use, or two belt grinders of the same type with the same use, and wherein the training output data comprise in each case at least one assigned piece of the state information relating to the belt grinder;
- training the machine learning system, wherein parameters of the machine learning system are adapted such that the machine learning system determines respectively assigned training output data depending on the adapted parameters and depending on the provided training input data;
- and
- adding the trained machine learning system to a computer device of the belt grinder,
- wherein the trained machine learning system is configured to determine the plurality of pieces of state information by:
- receiving the measurement data;
- and
- determining the state information from the received measurement data, and
- wherein the belt grinder has at least one abrasive belt for grinding a workpiece.
A method for training a machine learning system, comprising:
- providing training data comprising training input data and training output data, wherein the training input data comprise measurement data relating to (i) a belt grinder for a plurality of pieces of state information, and (ii) at least two belt grinders of different types, at least two belt grinders of the same type with a different use, or two belt grinders of the same type with the same use, and wherein the training output data comprise in each case at least one assigned piece of the state information relating to the belt grinder;
- training the machine learning system, wherein parameters of the machine learning system are adapted such that the machine learning system determines respectively assigned training output data depending on the adapted parameters and depending on the provided training input data;
- and
- adding the trained machine learning system to a computer device of the belt grinder,
- wherein the trained machine learning system is configured to determine the plurality of pieces of state information by:
- receiving the measurement data;
- and
- determining the state information from the received measurement data, and wherein the belt grinder has at least one abrasive belt for grinding a workpiece.
Dependencies are inferred from the claim text.