A vibration detection device includes an A/D conversion unit for receiving a sine wave signal of an AE wave corresponding to vibration generated in a target machine from an AE sensor that detects the AE wave and converting the received sine wave signal into digital data, an extraction unit for extracting, from the digital data, a data point of a local maximum value for each cycle of the sine wave signal, and an output processing unit for outputting the data point extracted by the extraction unit and cycle data including data points with the number of points which can be recognized as a sine wave and including the data point of a local maximum value so that an output unit visibly outputs the data point and the cycle data.

A vibration management device for managing the vibrations of a motor vehicle, the device including an electronic controller> The electronic controller is able to be fixed to a vibrating wall receiving vibrations from a component or set of components of the vehicle, by a fixing device including a vibration sensor, generating a vibration signal. The electronic controller includes a signal processor for processing the signal originating from the sensor, and the electronic controller is connected to a device for managing the vibrations.

A contact sensor for the repeatable detection of small, high frequency mechanical vibrations in external systems is presented herein. The sensor includes a metal housing with an attachment device at one end and an output at the other end. Inside the metal housing is a core assembly that includes a piezo transducer assembly suspended or isolated between an actuator and a biasing device. The actuator may be in the form of a ceramic sphere that sits at least partially within a recess on the inside of the housing and is in physical contact with the piezo transducer assembly. The biasing device may be in the form of a spring that causes the piezo transducer assembly to be pressed against the actuator at a contestant and known amount of tension.

A computer-implemented method for training a model for recommending threshold values of at least one spatial vibration component of an electric rotary machine. A computer-implemented method for monitoring a status of an electric rotary machine using the trained model. A computer program product with commands for carrying out the methods, a machine-readable storage medium with a computer program product, and a data transmission signal which carries the commands. A sensor and computing facility for monitoring a status of an electric rotary machine which is designed to detect data relating to the operation of the electric rotary machine on the electric rotary machine. The sensor and computing facility has commands which, when executed by the sensor and computing facility, cause the sensor and computing facility to carry out the training method and/or the status monitoring method.

A condition monitoring device for monitoring machinery includes a combination of on-board sensors and a condition monitoring module. The on-board sensors include modules for non-contact temperature, magnetic flux and 3-axis vibration sensing of the machinery. The condition monitoring module provides a condition monitoring signal containing information about an operating condition of the machinery, based upon a data synthesis condition monitoring technique that synthesizes non-contact temperature, magnetic flux and 3-axis vibration sensed data received from the combination of on-board sensors, determines a current operating condition of the machinery, and compares the current operating condition and the baseline operating condition of the machinery.

An early sign detection device includes a plurality of sensors, a data acquisition unit configured to acquire time series variation data of a physical amount from each of the plurality of sensors, a computation unit configured to compute an occurrence probability of a vibration mode involved in a sudden variant vibration of a detection subject from an amplitude or a phase of the time series variation data of the physical amount at each of the plurality of positions, and a detection unit configured to detect an early sign of the sudden variant vibration on the basis of the occurrence probability of the vibration mode. The plurality of sensors are respectively disposed at a plurality of positions of the detection subject and are each configured to measure the physical amount at a corresponding position of the plurality of positions.

In a method for monitoring an operating behavior of a tool holder, a resultant measurement axis signal is calculated using at least two measurement axis signals of at least two radially oriented measurement axes of a sensor provided in the tool holder. The monitoring is performed using the resultant measurement axis signal or the resultant.

Disclosed herein is a vibration monitoring and diagnosing system for monitoring conditions of a wind power generator and diagnosing a defective portion thereof using vibration characteristics obtained from acceleration sensors mounted to the wind power generator. A vibration-based defect detecting method may include: collecting vibration data of the wind power generator using the plurality of sensors; extracting a first characteristic value of a time domain based on the vibration data; extracting characteristic values in one or more frequency bands for a location of each sensor in a frequency domain or an envelope frequency domain if the first characteristic value is greater than a preset alarm setting value; and determining that a defect is present when at least one characteristic value of the characteristic values is greater than a preset normal value.

A rail-guided cart system includes a traveling rail and a traveling cart to travel along the traveling rail. The rail-guided cart system includes a measurement sensor and a diagnosis processor. The measurement sensor is fixed with respect to the traveling rail to measure vibration or sound. The diagnosis processor diagnoses a condition of the traveling cart that passed through a measurement point on the traveling rail corresponding to a location of the measurement sensor. based on measurement data measured by the measurement sensor.

A method for automatic diagnosis of a mechanical system of a group of mechanical systems sharing mechanical characteristics includes obtaining data relating to a vibration. The vibration-related data is acquired by a portable communications device configured to communicate with a remote processor. The processor automatically diagnoses the mechanical system by applying a relationship to the obtained vibration-related data. The relationship is based on sets of vibration-related data previously obtained from the mechanical systems. Each set of vibration-related data relates to vibrations of a mechanical system. The relationship is further based on sets of operation data previously obtained for mechanical systems of the group. Each set of operation data indicates a previous state of operation of a mechanical system. Each of the previous states of operation is associated with at least one of the previously obtained sets of vibration-related data.