Scientific Publications

Find all of Amiral Technologies' scientific publications

Comparison of anomaly detection models in an industrial context

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Application to non-cyclic datasets

Sensor fault detection using machine learning applied on acoustic test bench

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Amiral Technologies present its collaboration with Airbus Aircraft on the detection of failures and the use of a dictionary of failures to identify failures seen on a test bench.

Benchmark: comparison of failure prediction models

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The prediction of industrial equipment failures connected in blind mode is based on algorithms for detecting anomalies or new features on raw or transformed time series data.

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