Abstract: A method includes obtaining an utterance from a user including a user query directed toward a digital assistant. The method includes generating, using a language model, a first prediction string based on the utterance and determining whether the first prediction string includes an application programming interface (API) call to invoke a program via an API. When the first prediction string includes the API call to invoke the program, the method includes calling, using the API call, the program via the API to retrieve a program result; receiving, via the API, the program result; updating a conversational context with the program result that includes the utterance; and generating, using the language model, a second prediction string based on the updated conversational context. When the first prediction string does not include the API call, the method includes providing an utterance response to the utterance based on the first prediction string.

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: 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: 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.