The invention relates to a method (1) for monitoring a rotating machine (100) of an aircraft, wherein a measurement signal is acquired from the rotating machine. According to the invention, instantaneous frequencies (f.sub.K(t)) of sinusoidal components of the measurement signal are estimated, and, using a computing module (12), a plurality of successive iterations are carried out in each of which: complex envelopes of the components are updated (C1), parameters of a model of a noise of the signal are updated (C21) on the basis of the envelopes, whether the model has converged from the preceding iteration to the present iteration is tested (C4), with a view to: o if not, carrying out a new iteration, o if so, performing a computation (D) of the complex envelopes on the basis of the iterations that have been carried out.

The invention relates to a method (1) for monitoring a rotating machine (100) of an aircraft, wherein a measurement signal is acquired from the rotating machine. According to the invention, instantaneous frequencies (f.sub.K(t)) of sinusoidal components of the measurement signal are estimated, and, using a computing module (12), a plurality of successive iterations are carried out in each of which: complex envelopes of the components are updated (C1), parameters of a model of a noise of the signal are updated (C21) on the basis of the envelopes, whether the model has converged from the preceding iteration to the present iteration is tested (C4), with a view to: o if not, carrying out a new iteration, o if so, performing a computation (D) of the complex envelopes on the basis of the iterations that have been carried out.

A method for operating a plain bearing including: determining a first rotational speed at which a transition of a lubrication state takes place, or at which friction in the plain bearing is at a minimum; comparing the first rotational speed to a threshold value; and if the rotational speed has exceeded the threshold value, operating the bearing to produce a self-repairing effect.

To provide an abnormality monitoring device capable of reducing the size of a mounted device, enabling high-speed response, and achieving high accuracy in detecting abnormality. The abnormality monitoring device includes: at least one filter that extracts state information pertaining to drive of a mechanism of an industrial machine using a motor, as a signal of at least one frequency band; an integrator that integrates an output of the filter in each frequency band; and an abnormality detection unit that detects abnormality based on an integrated value integrated by the integrator. The state information may be control information of the controller that controls the motor or detection information from at least one detector attached to the mechanism.

To provide an abnormality monitoring device capable of reducing the size of a mounted device, enabling high-speed response, and achieving high accuracy in detecting abnormality. The abnormality monitoring device includes: at least one filter that extracts state information pertaining to drive of a mechanism of an industrial machine using a motor, as a signal of at least one frequency band; an integrator that integrates an output of the filter in each frequency band; and an abnormality detection unit that detects abnormality based on an integrated value integrated by the integrator. The state information may be control information of the controller that controls the motor or detection information from at least one detector attached to the mechanism.

For peaks having top ten peak values in a frequency spectrum obtained by frequency analysis, a central processing unit specifies a part based on information on a bearing subjected to measurement. For the peaks having the top ten peak values, a determination unit determines a vibration state based on the peak value and a criterion value. For the peaks having the top ten peak values, a display shows the peak value, the part, and a result of determination by the determination unit.

For peaks having top ten peak values in a frequency spectrum obtained by frequency analysis, a central processing unit specifies a part based on information on a bearing subjected to measurement. For the peaks having the top ten peak values, a determination unit determines a vibration state based on the peak value and a criterion value. For the peaks having the top ten peak values, a display shows the peak value, the part, and a result of determination by the determination unit.

Provided is a fractal structure for power-generation of bearing rotating vibration that is installed on an outer ring of a bearing to generate power using vibration generated from a micro whirling motion of the bearing, the fractal structure including a housing which is in contact with the outer ring of the bearing to receive the vibration generated from the micro whirling motion of the bearing, and has a receiving space therein, a flexible element which is disposed in the receiving space while being in contact with an inner circumference of the housing to convert the vibration into a radial direction, and a piezoelectric element which is installed between the housing and the flexible element and disposed near the receiving space, and deforms upon receiving the vibration converted in the radial direction from the flexible element, thereby producing electricity.

Provided is a fractal structure for power-generation of bearing rotating vibration that is installed on an outer ring of a bearing to generate power using vibration generated from a micro whirling motion of the bearing, the fractal structure including a housing which is in contact with the outer ring of the bearing to receive the vibration generated from the micro whirling motion of the bearing, and has a receiving space therein, a flexible element which is disposed in the receiving space while being in contact with an inner circumference of the housing to convert the vibration into a radial direction, and a piezoelectric element which is installed between the housing and the flexible element and disposed near the receiving space, and deforms upon receiving the vibration converted in the radial direction from the flexible element, thereby producing electricity.

A wind turbine generator fault detection method is described. The method includes obtaining a first signal from a generator of a wind turbine and a second signal from a vibration sensor coupled to the wind turbine, the first signal representing an output current of the generator, and the second signal being a time-sampled signal representing vibrations of a bearing in the wind turbine. Determining a shaft rotation frequency signal from the first signal, the shaft rotation frequency signal representing a time-varying rotational speed of a shaft of the wind turbine. Resampling an envelope of the second signal based on the shaft rotation frequency signal to provide a third signal, the third signal being an angular sampled signal. Detecting, by the at least one processor, a fault in the bearing of the wind turbine by identifying a characteristic signature of a bearing fault in the third signal.