A method for measuring health of a motor includes: (a) measuring, by an electrocardiogram sensor, vibration of the motor to obtain at least two electrical signals with each of the at least two electrical signals representing a harmonic of the vibration of the motor; (b) comparing each of the at least two electrical signals with a corresponding baseline; (c) based on the comparison, determining whether any one of the at least two electrical signals includes one or more artifacts wherein an artifact in a respective one of the at least two electrical signals is a deviation from a respective one of the corresponding baseline; and (d) based on any one of the at least two electrical signals including the one or more artifacts, providing an estimated time to failure for the motor.

A processing apparatus acquires a first rise transition that is a rise transition of the temperature of a winding and a second rise transition that is a rise transition of the temperature detected by a temperature sensor in a state where voltage application for raising the temperature of the winding to a predetermined temperature is performed, determines a predetermined temperature characteristic model by calculating a predetermined parameter on the basis of the second rise transition, and further determines a winding temperature characteristic model by calculating a winding related parameter on the basis of the first rise transition.

The short-circuit detection device according to the present disclosure includes: a signal acquisition unit configured to acquire, from a magnetic flux detector configured to detect a magnetic flux generated in a gap between a rotor and a stator of a rotary electric machine, one detected signal based on the magnetic flux and set the one detected signal as a first detected signal and a second detected signal; a signal processing unit configured to perform frequency analysis on the first detected signal, and generate and decode a voltage signal simulating a voltage state assumed in a normal case; and a signal comparison unit configured to perform comparison between a decoded signal obtained through the decoding by the signal processing unit and the second detected signal transmitted from the signal acquisition unit, to detect a short-circuit in a field winding of the rotary electric machine.

An abnormality diagnosis system performs an abnormality diagnosis of a plurality of motor systems that include a motor for moving a moving body. The abnormality diagnosis system identifies a comparison target system that is the motor system, among the motor systems, that is a comparison target in relation to a diagnosis target system that is the motor system to be a target of the abnormality diagnosis. The abnormality diagnosis system acquires a state-related value that is a value related to an operation state of the motor from each of the diagnosis target system and the comparison target system. The abnormality diagnosis system performs a comparison of the state-related value that is acquired from the diagnosis target system and the state-related value that is acquired from the comparison target system, and diagnoses a presence or absence of an abnormality in the diagnosis target system using a result of the comparison.

An abnormality diagnosis system performs an abnormality diagnosis of a plurality of motor systems that include a motor for moving a moving body. The abnormality diagnosis system identifies a comparison target system that is the motor system, among the motor systems, that is a comparison target in relation to a diagnosis target system that is the motor system to be a target of the abnormality diagnosis. The abnormality diagnosis system acquires a state-related value that is a value related to an operation state of the motor from each of the diagnosis target system and the comparison target system. The abnormality diagnosis system performs a comparison of the state-related value that is acquired from the diagnosis target system and the state-related value that is acquired from the comparison target system, and diagnoses a presence or absence of an abnormality in the diagnosis target system using a result of the comparison.

A technique for performing condition monitoring of a plurality of components of a plurality of wind turbines is disclosed. The technique includes, for each of the plurality of wind turbines, measuring at least one time-series electrical output signal of the wind turbine generator, each time-series electrical output signal representing an aggregate of a plurality of subset signals. Such condition monitoring further includes mathematically extracting one or more such subset signals from the at least one time-series electrical output signal of the generator, and associating one or more such subset signals with one or more wind turbine components. A fault threshold value for each such one or more subset signals may be determined, and the one or more such subset signals are compared to such fault threshold value. Based on such association and comparison, the condition of such a wind turbine component of the plurality of wind turbines is determined.

A universal automatic test system for a digital plugboard based on imagine processing, including a digital plugboard test platform, an image acquisition and processing module, a test instrument module and a control and processing module.

A universal automatic test system for a digital plugboard based on imagine processing, including a digital plugboard test platform, an image acquisition and processing module, a test instrument module and a control and processing module.

An HVAC system includes a blower, a motor drive, and a controller. A benchmark rate of the flow of air provided by the blower and a corresponding benchmark power output of the motor drive associated with operation of the blower at a test condition are received. The controller determines a first motor drive frequency at which the motor drive is operating. Based on the benchmark rate and a comparison of the first motor drive frequency to the predefined motor drive frequency, a first rate of the flow of air provided by the blower is determined. At a later time, a current power output of the motor drive is determined during operation of the blower at the test condition. Based on a comparison of the current benchmark power output to the benchmark power output, an updated benchmark rate of the flow of air provided by the blower is determined.

There is provided a diagnostic apparatus including: a data acquisition unit configured to acquire target data relating to a current value between a power conversion apparatus and a motor; a detection unit configured to detect a peak value in a time series waveform of the target data; a counting operation unit configured to use a frequency counting method to calculate an amplitude of the peak value and a frequency of occurrence of the amplitude; and a diagnostic unit configured to diagnose an abnormality of the motor based on the amplitude and the frequency of occurrence. The diagnostic unit diagnoses that the motor is abnormal when a statistic which is calculated from the amplitude and the frequency of occurrence of the amplitude does not satisfy a predetermined reference.