Abstract: Systems and methods are disclosed for controlling and diagnosing the health of a motorized system. The systems may comprise a diagnostics system and a controller, wherein the diagnostics system employs a neural network, an expert system, and/or a data fusion component in order to assess the health of the motorized system according to one or more attributes associated therewith. The controller may operate the motorized system in accordance with a setpoint and/or a diagnostics signal from the diagnostics system. Also disclosed are methodologies for controlling and diagnosing the health of a motorized system, comprising operating a motor in the motorized system in a controlled fashion, and diagnosing the health of the motorized system according to a measured attribute associated with the motorized system, wherein the motor may be operated according to a setpoint and/or the diagnostics signal.

Abstract: A machine diagnostic system for on-line diagnosis of a machine including a package for a machine diagnostic module that collects data relating to operation of the machine. The package is mounted to an outer mounting surface of the machine and includes a container which contains the machine diagnostic module. The package further includes a heat dissipation device between the container and the outer mounting surface of the machine which dissipates heat generated by the machine into surrounding air thereby minimizing heat transfer to the container.

Abstract: A diagnostic system includes a vibration sensor mounted on a machine to measure vibrations. Vibration signals from the sensor are processed and analyzed by the system. From a known critical frequency of a vibration-generating component, the system measures the amplitude of the vibration signal at more than one harmonic frequency of the known critical frequency and compares the amplitudes to amplitudes at adjacent harmonic frequencies. When a relatively large amplitude is found at a harmonic frequency, that is a harmonic frequency near a resonant frequency of the physical path between the vibration sensor and the vibration-generating component, the system analyzes the shape and magnitude of the vibration signal around that harmonic frequency to evaluate the condition of the machine.

Abstract: A rotating flux vector is set up in a motor or generator's rotor by simultaneously energizing two phase windings while the rotor remains stationary, wherein each phase winding may be energized by the same or different excitation voltages. Respective tap voltages are then recorded at this first flux position. Thereafter, the two phase windings are simultaneously energized by another voltage excitation, wherein each phase is energized at the same or different voltages, causing a new flux position to occur. Once again, respective tap voltages are recorded. This process may be repeated for various rotations of the motor's flux. The measured tap voltages are evaluated to determine the location of the rotor, without actually moving it. The present invention is applicable to SR and non-SR machines having a plurality of phases and pole configurations.

Abstract: A diagnostic system includes a vibration sensor mounted on a machine which has vibration-generating components having different vibration characteristics with respect to a common sensor. The vibration sensor measures vibrations and sends vibration signals to a diagnostic module for evaluation of the signals. The diagnostic module has software for processing the vibration signals. From a known natural frequency of a vibration-generating component, the diagnostic module measures the amplitude of the vibration signal at more than one harmonic frequency of the known natural frequency and compares the amplitudes to amplitudes at adjacent harmonic frequencies.

Abstract: A machine diagnostic system is provided which includes a host computer for determining a health state of a machine. The host computer is operatively coupled to a network backbone. The system also includes a machine diagnostic module adapted to be integrally mounted to a machine, the machine diagnostic module being operatively coupled to the network backbone. The machine diagnostic module collects data relating to operation of the machine and preprocesses the data, and the host computer analyzes the preprocessed data in determining the health state of the machine. The machine diagnostic system includes a system architecture which facilitates the machine diagnosis. The system architecture includes several software layers which provide for collecting and preprocessing machine data, transmitting the collected and/or preprocessed data over a network and analyzing such for machine diagnosis and process diagnosis.

Abstract: A test procedure detects the onset of stator winding damage, identifies the failure mechanism, determines the winding's susceptibility to further damage, and predicts stator winding failure. This is accomplished by introducing a high frequency signal onto power lines which feed the stator and monitoring a change in the capacitance between the individual windings during introduction of the high frequency signal. In order to monitor the change in capacitance, a current sensor and voltage sensor are used to measure the current and voltage on the power lines during introduction of the high frequency signal. Changes in the capacitance between the individual stator windings are reflected as changes in the broadband impedance response of the stator windings which can be calculated by dividing the measured voltage by the measured current.