Augury Systems Ltd.

Daniel Barsky

Gal Shaul

Ori Negri

Gal Ben-Haim

Saar Yoskovitz

Christopher Bethel

A method for machine monitoring including causing a first sensor to acquire at least a first non-stationary signal from at least one machine operating in a non-stationary manner during at least one operational time frame, causing a second sensor to acquire at least a second non-stationary signal from the at least one machine during the operational time frame, fusing a first non-stationary output provided by the first sensor with a second non-stationary output provided by the second sensor, extracting at least one feature from the fused output, analyzing the at least one feature to ascertain a state of health of the at least one machine and performing at least one operation on the at least one machine based on the state of health as found by the analyzing.

Automated analysis of non-stationary machine performance

A method for identifying a fault of at least one mechanical machine, including causing a first plurality of sensors coupled to a corresponding first plurality of mechanical machines to acquire a first plurality of sets of signals emanating from the first plurality of mechanical machines, the first plurality of mechanical machines sharing at least one characteristic, supplying at least the first plurality of sets of signals of the first plurality of mechanical machines to a pre-existing fault classifier previously trained to automatically identify faults of a second plurality of mechanical machines based on signals emanating therefrom and previously acquired by a second plurality of sensors, the second plurality of sensors being of a different type than the first plurality of sensors, the second plurality of mechanical machines sharing the at least one characteristic, modifying the pre-existing fault classifier by employing transfer learning, based at least on the first plurality of sets of signals of the first plurality of mechanical machines, thereby providing a modified fault classifier, applying the modified fault classifier to at least one additional set of signals acquired by at least one sensor of the first plurality of sensors and emanating from at least one given mechanical machine sharing the at least one characteristic, the modified fault classifier being configured to automatically identify at least one fault of the at least one given mechanical machine based on the at least one additional set of signals, and providing a human sensible output, by an output device, including at least identification of the fault of the at least one given mechanical machine, at least one of a repair or maintenance operation being performed based on the human sensible output.

Sensor-agnostic mechanical machine fault identification

A method for monitoring at least one machine including causing at least a first sensor to acquire at least a first non-stationary signal from at least one machine operating in a non-stationary manner during at least one operational time frame, the at least first sensor providing at least a first non-stationary output, causing at least a second sensor to acquire at least a second non-stationary signal from the at least one machine during the operational time frame, the at least second sensor providing at least a second non-stationary output, fusing the at least first non-stationary output with the at least second non-stationary output to produce a fused output, extracting at least one feature of at least one of the first and second non-stationary signals based on the fused output, analyzing the at least one feature to ascertain a state of health of the at least one machine and performing at least one of a repair operation, maintenance operation and modification of operating parameters of the at least one machine based on the state of health as found by the analyzing.

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Haifa, Israel

Daniel Barsky