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US20220050023 - SYSTEM FOR PREDICTING ANOMALIES OF MACHINING
Abstract
(EN)
A system (1) for predicting anomalies of machining, in particular the anomalies generating a defect on a part machined by a machine tool, comprising:
- a. a signal-processing unit (10) configured to acquire raw data, in particular sensor data and machining parameters from a machine tool (2) and to process the raw data to neuromorphic-circuit input data including features extracted by the signal-processing unit;
- b. a neuromorphic circuit (20) connected to the signal-processing unit configured to build a neural network on an integrated circuit, wherein the neural network is trained by training data and the trained neural network enables to determine anomaly data describing anomalies of the machining in response to the neuromorphic-circuit input data, in particular to the features; and
- c. a controller configured to receive the determined anomaly data from the signal-processing unit and to determine at least one action, which can be taken to overcome the determined anomalies.
Interestingly, it appears this patent specifies learning on the edge:
If additional information, such as new anomalies are obtained during the quality control, the additional information can be used to build new training data to improve the learning of the neuromorphic circuit. By this way, the detection precision can be further improved as shown in step 5 S 5
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Product unrelated but it's an example from their range. Obviously looking to implement neuromorphic circuitry to detect defects during production.