Abstract: A method for monitoring and identifying electrical discharge generated by electrical devices including collecting output indications of at least one physical parameter related to electrical discharge and sensed from a plurality of electrical devices operating at a voltage at which electrical discharge may occur, generating a unified model representative of behavior of the plurality of electrical devices based at least on the output indications of the at least one physical parameter sensed from the plurality of electrical devices, applying the model to output indications of the at least one physical parameter sensed from at least one given electrical device operating at a voltage at which electrical discharge may occur, identifying, at least by the applying of the model, at least one electrical-discharge related condition of the given electrical device, and automatically providing a human sensible output notification including an indication of the at least one identified condition.

Abstract: 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 machi

Abstract: A system for monitoring and identifying states of a semiconductor device, the system including at least one acoustic sensor for sensing acoustic emission emitted by at least one semiconductor device operating at a voltage of less than or equal to 220 V, the at least one acoustic sensor outputting at least one acoustic emission signal and a signal processing unit for receiving the at least one acoustic emission signal from the at least one acoustic sensor and for analyzing the at least one acoustic emission signal, the signal processing unit providing an output based on the analyzing, the output being indicative at least of whether the at least one semiconductor device is in an abnormal operating state with respect to a normal operating state of the semiconductor device.

Abstract: 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.

Abstract: A system for continuously monitoring at least one machine including at least one magnetic sensor sensing magnetic fields emitted by at least one machine, at least one vibration sensor synchronously sensing vibrations emitted by the at least one machine, a signal analyzer receiving at least a portion of the magnetic field emission signals and vibration signals and performing analysis thereof, the signal analyzer providing an output based on the analysis, the output including at least an indication of a condition of the at least one machine, and a control module initiating at least one of a repair event on the at least one machine, an adjustment to a maintenance schedule of the at least one machine and an adjustment to an operating parameter of the at least one machine based on the indication, whereby efficacy of the at least one machine is improved.

Abstract: 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 firs

Abstract: 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 machi

Abstract: A method for automatic diagnosis of a mechanical system of a group of mechanical systems sharing mechanical characteristics includes obtaining data relating to a vibration. The vibration-related data is acquired by a portable communications device configured to communicate with a remote processor. The processor automatically diagnoses the mechanical system by applying a relationship to the obtained vibration-related data. The relationship is based on sets of vibration-related data previously obtained from the mechanical systems. Each set of vibration-related data relates to vibrations of a mechanical system. The relationship is further based on sets of operation data previously obtained for mechanical systems of the group. Each set of operation data indicates a previous state of operation of a mechanical system. Each of the previous states of operation is associated with at least one of the previously obtained sets of vibration-related data.

Abstract: 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 machi

Abstract: A system for monitoring at least one machine including a plurality of magnetic sensors synchronously sensing magnetic fields emitted by at least one machine, along a corresponding plurality of channels and outputting magnetic field emission signals corresponding to the magnetic fields, a signal analyzer receiving at least a portion of the magnetic field emission signals, performing analysis thereof, and providing an output based on the analysis, the output including at least an indication of a condition of the at least one machine, and a control module receiving the indication of the condition and initiating at least one of a repair event on the at least one machine, an adjustment to a maintenance schedule of the at least one machine and an adjustment to an operating parameter of the at least one machine based on the indication, whereby efficacy of the at least one machine is improved.

Abstract: A system for monitoring and identifying states of a semiconductor device, the system including at least one acoustic sensor for sensing acoustic emission emitted by at least one semiconductor device operating at a voltage of less than or equal to 220 V, the at least one acoustic sensor outputting at least one acoustic emission signal and a signal processing unit for receiving the at least one acoustic emission signal from the at least one acoustic sensor and for analyzing the at least one acoustic emission signal, the signal processing unit providing an output based on the analyzing, the output being indicative at least of whether the at least one semiconductor device is in an abnormal operating state with respect to a normal operating state of the semiconductor device.

Abstract: 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 machi

Abstract: A method for automatic diagnosis of a mechanical system of a group of mechanical systems sharing mechanical characteristics includes obtaining data relating to a vibration. The vibration-related data is acquired by a portable communications device configured to communicate with a remote processor. The processor automatically diagnoses the mechanical system by applying a relationship to the obtained vibration-related data. The relationship is based on sets of vibration-related data previously obtained from the mechanical systems. Each set of vibration-related data relates to vibrations of a mechanical system. The relationship is further based on sets of operation data previously obtained for mechanical systems of the group. Each set of operation data indicates a previous state of operation of a mechanical system. Each of the previous states of operation is associated with at least one of the previously obtained sets of vibration-related data.

Abstract: A method for automatic diagnosis of a mechanical system of a group of mechanical systems sharing mechanical characteristics includes obtaining data relating to a vibration. The vibration-related data is acquired by a portable communications device configured to communicate with a remote processor. The processor automatically diagnoses the mechanical system by applying a relationship to the obtained vibration-related data. The relationship is based on sets of vibration-related data previously obtained from the mechanical systems. Each set of vibration-related data relates to vibrations of a mechanical system. The relationship is further based on sets of operation data previously obtained for mechanical systems of the group. Each set of operation data indicates a previous state of operation of a mechanical system. Each of the previous states of operation is associated with at least one of the previously obtained sets of vibration-related data.

Abstract: A method for automatic diagnosis of a mechanical system of a group of mechanical systems sharing mechanical characteristics includes obtaining data relating to a vibration. The vibration-related data is acquired by a portable communications device configured to communicate with a remote processor. The processor automatically diagnoses the mechanical system by applying a relationship to the obtained vibration-related data. The relationship is based on sets of vibration-related data previously obtained from the mechanical systems. Each set of vibration-related data relates to vibrations of a mechanical system. The relationship is further based on sets of operation data previously obtained for mechanical systems of the group. Each set of operation data indicates a previous state of operation of a mechanical system. Each of the previous states of operation is associated with at least one of the previously obtained sets of vibration-related data.

Abstract: A method for automatic diagnosis of a mechanical system of a group of mechanical systems sharing mechanical characteristics includes obtaining data relating to a vibration. The vibration-related data is acquired by a portable communications device configured to communicate with a remote processor. The processor automatically diagnoses the mechanical system by applying a relationship to the obtained vibration-related data. The relationship is based on sets of vibration-related data previously obtained from the mechanical systems. Each set of vibration-related data relates to vibrations of a mechanical system. The relationship is further based on sets of operation data previously obtained for mechanical systems of the group. Each set of operation data indicates a previous state of operation of a mechanical system. Each of the previous states of operation is associated with at least one of the previously obtained sets of vibration-related data.