US Patent Application 18190548. Method and Apparatus for Operating a System for Detecting an Anomaly of an Electrical Energy Store for a Device by Means of Machine Learning Methods simplified abstract
Method and Apparatus for Operating a System for Detecting an Anomaly of an Electrical Energy Store for a Device by Means of Machine Learning Methods
Organization Name
Inventor(s)
Christian Simonis of Leonberg (DE)
Tobias Huelsing of Stuttgart (DE)
Method and Apparatus for Operating a System for Detecting an Anomaly of an Electrical Energy Store for a Device by Means of Machine Learning Methods - A simplified explanation of the abstract
- This abstract for appeared for US patent application number 18190548 Titled 'Method and Apparatus for Operating a System for Detecting an Anomaly of an Electrical Energy Store for a Device by Means of Machine Learning Methods'
Simplified Explanation
The abstract describes a computer-based method for detecting abnormal behavior in an electrical energy store in a technical device. The method involves monitoring the operating variables of the energy store and extracting relevant features from the collected data. An anomaly detection model, specifically an autoencoder, is then used to analyze the input data and generate a reconstructed version of the input. Based on the difference between the reconstructed input and the original input, an error is determined and signaled if necessary.
Original Abstract Submitted
A computer-implemented method for determining an anomaly of a behavior of an electrical energy store in a technical device includes sensing an operating variable profile of at least one operating variable of the electrical energy store, and determining at least one feature from the sensed operating variable profile of the at least one operating variable of the electrical energy store. The method further includes evaluating an anomaly detection model using an autoencoder with a supplied input vector that includes or depends on the determined at least one feature, in order to determine a reconstructed input vector, and signaling an error based on a reconstruction error between the reconstructed input vector and the supplied input vector.
