Computer-implemented method for processing machine-related data of a component of a device
AssigneeQlar Europe GmbH
InventorViktor RAIS
Life of this patent
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Abstract
A computer-implemented method for processing machine-related data in order to obtain at least one trained machine-learning model and to a computer-implemented method for detecting the operating state of a component of a device. Provided is also a device for processing data, and designed to carry out a respective method of the computer-implemented methods or both computer-implemented methods, and to a data structure.
Claims24
A computer-implemented method for detecting an operating state in a particular component of a device, the computer-implemented method comprising:
- receiving data that represent and/or makes it possible to determine information on one or more state variables assigned or assignable to the particular component;
- and
- calculating a trained machine-learning model at least partially with the received data as input data, the trained ML model being obtained as a training method during a computer-implemented method preceding the detection for processing machine-related data in order to obtain at least one trained ML model, the training method comprising:
- selecting components of at least two devices as specific components and are each assigned to at least one of at least one definitional component group and/or (ii) for each device of at least two devices, at least one component of the respective device is selected as a specific component and is assigned to at least one and/or exactly one component group of at least one definitional component group in such a way that after the assignment of all specific components of all devices (a) the specific components assigned to one and the same component group are all similar or identical and/or (b) the specific components which are all similar or identical among all specific components of all devices are each assigned to the same component group;
- receiving data, which, in relation to each of the specific components, represent and/or make it possible to determine information on (i) one or more of the state variables assigned or assignable to the respective specific component and (ii) one or more events relating to the respective specific component;
- and
- training, for each of the at least one component groups, a separate ML model on a separate database, each of which is at least partially created on the basis of at least parts of the received data.
A computer-implemented method for processing machine-related data, which represent information on state variables and events associated with or assignable to device components or used to determine the same in order to obtain at least one trained machine-learning model, the computer-implemented method comprising:
- selecting components of at least two devices as specific components and are each assigned to at least one of at least one definitional component group and/or (ii) for each device of at least two devices, at least one component of the respective device is selected as a specific component and is assigned to at least one and/or exactly one component group of at least one definitional component group in such a way that after the assignment of all specific components of all devices (a) the specific components assigned to one and the same component group are all similar or identical and/or (b) the specific components which are all similar or identical among all specific components of all devices are each assigned to the same component group;
- receiving data, which, in relation to each of the specific components, represent and/or make it possible to determine information on (i) one or more of the state variables assigned or assignable to the respective specific component and (ii) one or more events relating to the respective specific component;
- and
- training, for each of the at least one component groups, a separate ML model on a separate database, each of which is at least partially created on the basis of at least parts of the received data.
A computer-implemented method for processing machine-related data in order to obtain at least one trained machine-learning model, the computer-implemented method comprising:
- selecting components of at least two devices as specific components and are each assigned to at least one of at least one definitional component group;
- receiving data, which, in relation to each of the specific components, represent and/or make it possible to determine information on (i) one or more of the state variables assigned or assignable to the respective specific component and (ii) one or more events relating to the respective specific component;
- and
- training, for each of the at least one component groups, a separate ML model on a separate database, each of which is at least partially created on the basis of at least parts of the received data.
A computer-implemented method for detecting an operating state, in particular an error state, in a particular component of a device, the computer-implemented method comprising:
- receiving data representing and/or making it possible to determine information on one or more state variables assigned or assignable to the particular component;
- and
- calculating a trained ML model with the received data as input data, such that the output data of the trained ML model represents the operating state of the device.
A data structure in which component objects and assignments are stored, wherein the component objects are placed in relation to one another and displayed in the form of a tree structure via the assignments, wherein the component objects describe device components and a tree structure of the associated component objects are displayed for the components of at least two devices, wherein at least two of the at least two tree structures have at least one component object identically.
Dependencies are inferred from the claim text.