Abstract: A system configured for monitoring the operation status of an electric machine; a mobile phone therefor and server-based system using the same. The system includes a portable unit, adapted for free movement around the electric machine; an airborne acoustics sensor, adapted for measuring acoustic data produced by the electric machine at a first position in a path of the free movement; a magnetic field sensor, adapted for measuring magnetic field data produced by the electric machine at a second position in the path of the free movement; and a processing unit, adapted for calculating the operation status of the electric machine based on the acoustic data from the airborne acoustics sensor and the magnetic field data from the magnetic field sensor; wherein: the airborne acoustics sensor and the magnetic field sensor are integrated with the portable unit.

Abstract: A method for condition monitoring of distributed drive-trains using Bayesian data fusion approach for measured data includes measurement of physical signals obtained from sensors attached to the components being chosen from the drive-train which are delivered to the computer means for processing the measured data and performing data fusion processes, using a data from information database containing at least one information system. The method is characterized by comprising two stages for data fusion processes performed by using Bayesian Inference, the first one for local data fusion process and the second one for global data fusion process, and on the basis of the second stage the assessment process of the condition of the drive-train is performed by choosing the maximum value of the received data, which maximum value serves as an indicator for the most likely fault present in the drive-train.

Abstract: In aspects, the present invention discloses a method of detecting a rotor fault in an electric machine using a data analysis unit. The method comprises measuring magnetic field strength along a first axis and a second axis, determining operating slip frequency of the electric machine using the measured magnetic field strength along the first axis and the second axis, determining an amplitude of the determined operating slip frequency in a first frequency spectrum and an amplitude of operating slip frequency in a second frequency spectrum, and detecting the rotor fault by comparing the amplitude of the determined operating slip frequency in the first frequency spectrum and the amplitude of operating slip frequency in the second frequency spectrum against a predetermined threshold.

Abstract: In aspects, the present invention discloses a system for monitoring condition of a plurality of motors. The system includes a plurality of condition monitoring devices capable of measuring one or more parameters associated with the corresponding motors, a gateway device coupled to the one or more condition monitoring devices for configuring the one or more condition monitoring devices upon installation and for communicating measurement data from the one or more condition monitoring devices, a server configured to receive measurement data from the gateway device 140 and to detect a condition of at least one motor from the one or more motors, and at least one mobile device capable of configuring the one or more condition monitoring devices, and for displaying one or more alert messages associated with the detected condition of the at least one motor based on a message from the server.

Abstract: A method for identifying a fault condition in an electrical machine in which at least a stator or a rotor has parallel winding branches is disclosed. A measurement is carried out for obtaining a set of circulating current values between two parallel winding branches of which each winding branch includes a single coil. A frequency analysis is applied on the set of circulating current values to obtain at least one frequency component. A fault condition of the electrical machine is determined on the basis of the at least one frequency component.

Abstract: A condition monitoring device and monitoring system in one form includes an enclosure being shaped into a form of a portable tool for daily use, including a part for performing daily use functionality and being adapted to be carried by a user; and at least one sensor block being housed in the enclosure, being adapted for measuring data produced by a machine. The condition monitory device can be included in a system of multiple devices. The enclosure can take many forms including but not limited to a writing element, a memory unit (such as but not limited to a memory stick), and a screwdriver. The device can include a sensor block and a communication block. In some forms the device can be a mobile phone. The device can be included in a system that includes a server for processing signals, and/or a portable device that includes a processor.

Abstract: A system configured for monitoring the operation status of an electric machine; a mobile phone therefor and server-based system using the same. The system includes a portable unit, adapted for free movement around the electric machine; an airborne acoustics sensor, adapted for measuring acoustic data produced by the electric machine at a first position in a path of the free movement; a magnetic field sensor, adapted for measuring magnetic field data produced by the electric machine at a second position in the path of the free movement; and a processing unit, adapted for calculating the operation status of the electric machine based on the acoustic data from the airborne acoustics sensor and the magnetic field data from the magnetic field sensor; wherein: the airborne acoustics sensor and the magnetic field sensor are integrated with the portable unit.

Abstract: In aspects, the present invention discloses a method of detecting a rotor fault in an electric machine using a data analysis unit. The method comprises measuring magnetic field strength along a first axis and a second axis, determining operating slip frequency of the electric machine using the measured magnetic field strength along the first axis and the second axis, determining an amplitude of the determined operating slip frequency in a first frequency spectrum and an amplitude of operating slip frequency in a second frequency spectrum, and detecting the rotor fault by comparing the amplitude of the determined operating slip frequency in the first frequency spectrum and the amplitude of operating slip frequency in the second frequency spectrum against a predetermined threshold.

Abstract: A method for condition monitoring of distributed drive-trains using Bayesian data fusion approach for measured data includes measurement of physical signals obtained from sensors attached to the components being chosen from the drive-train which are delivered to the computer means for processing the measured data and performing data fusion processes, using a data from information database containing at least one information system. The method is characterized by comprising two stages for data fusion processes performed by using Bayesian Inference, the first one for local data fusion process and the second one for global data fusion process, and on the basis of the second stage the assessment process of the condition of the drive-train is performed by choosing the maximum value of the received data, which maximum value serves as an indicator for the most likely fault present in the drive-train.

Abstract: A method for identifying a fault condition in an electrical machine in which at least a stator or a rotor has parallel winding branches is disclosed. A measurement is carried out for obtaining a set of circulating current values between two parallel winding branches of which each winding branch includes a single coil. A frequency analysis is applied on the set of circulating current values to obtain at least one frequency component. A fault condition of the electrical machine is determined on the basis of the at least one frequency component.