A data processing device includes a peak detector that detects a peak from a frequency spectrum and a map generator that generates an abnormality map for the frequency spectrum. The abnormality map includes as abnormal components, a frequency of a detected peak of interest and a frequency of a peak that appears together with the peak of interest when the peak of interest is assumed as the peak originating from abnormality. The data processing device includes an abnormal peak extractor that extracts as an abnormal peak, a peak at a frequency that matches with any of the abnormal components included in the abnormality map and a first criterion value calculator that calculates a first criterion value representing occurrence of abnormality corresponding to the abnormality map based on a spectral density of the abnormal peak.

The present disclosure relates to a stringed instrument resonance analysis device which uses a scientific detection method to evaluate the resonance effect of stringed instrument, wherein the stringed instrument resonance analysis device has a cabinet, a holder, a resonant sounder, a sonic generator, at least one sonic collector and a spectrum analyzer. The cabinet forms an accommodating space therein. The holder a holder is disposed in the accommodating space and used to fix and hold the stringed instrument. The resonant sounder is disposed in the accommodating space and fixed and clamped to a bridge on a loudspeaker box of the stringed instrument. The sonic generator is connected to the resonant sounder. The sonic collector is disposed in the accommodating space and adjacent to the loudspeaker box of the stringed instrument. The spectrum analyzer is connected to the at least one sonic collector.

An abnormality detection device 1 includes: a vibration acquisition unit 11 configured to acquire an acoustic signal generated during passage of a vehicle on a road; a frequency domain conversion unit 12 configured to convert the acquired acoustic signal into a frequency domain signal; an unexpectedness determination unit 13 configured to determine whether there is unexpectedness at each predetermined frequency using the frequency domain signal; and an abnormality determination unit 14 configured to determine whether there is an abnormality in the road based on the number of frequencies at which it is determined that there is the unexpectedness.

A method for monitoring machine operation for various machine speed and loads includes measuring vibration information at a sensor associated with a machine and an associated machine speed. The machine is a rotating machine. The method includes performing an operational frequency analysis of the vibration information and comparing results from the operational frequency analysis with a vibration signature for the machine. The vibration signature is for a machine speed that matches the machine speed of the measured vibration information. The vibration signature is one of several vibration signatures for the machine where each is for a different machine speed. The method includes identifying a potential failure mode based on a frequency range where the frequency analysis of the measured vibration information exceeds, by a threshold amount, the vibration signature of the plurality of vibration signatures that matches the machine speed, and transmitting an alert comprising the identified potential failure mode.

Systems and methods for identifying potential bullying are disclosed. In various aspects, a system for identifying potential bullying includes a sound detector configured to provide samples of sounds over time, a processor, and a memory storing instructions. The instructions, when executed by the processor, cause the system to determine that a noise event has occurred by processing the samples to determine that the sounds exceed a sound level threshold over a time period that exceeds a time period threshold, process the samples to provide frequency spectrum information of the noise event, determine whether the noise event is a potential bullying occurrence based on comparing the frequency spectrum information of the noise event and at least one frequency spectrum profile, and initiate a bullying notification in a case of determining that the noise event is a potential bullying occurrence.

An adaptive noise filtering system and method detect sounds using a sensor onboard a vehicle system. A value of a signal associated with operation of the vehicle system is determined. One or more sounds detected by the sensor are filtered out based on the value of the signal that is determined. Operation of the vehicle system may be controlled using the remaining sound(s).

A sound recognition apparatus (100) includes at least two microphones (1) that detect a surrounding sound, an attitude detection unit (4) that detects attitudes of the microphones (1), a self-position estimation unit (52) that estimates positions of the microphones (1) based on the attitudes of the microphones (1) and a signal of the sound detected by the microphone (1), a sound source estimation unit (53) that estimates a direction of the sound source (200) of the sound based on the attitudes of the microphones (1) and the signal of the sound detected by the microphone (1), and a sound environment mapping unit (54) that creates a sound environment map based on the positions of the microphones (1) and the direction of the sound source (200), the sound environment map displaying at least a position of the sound source (200).

Systems and methods for identifying potential bullying are disclosed. In various aspects, a system for identifying potential bullying includes a sound detector configured to provide samples of sounds over time, a processor, and a memory storing instructions. The instructions, when executed by the processor, cause the system to determine that a noise event has occurred by processing the samples to determine that the sounds exceed a sound level threshold over a time period that exceeds a time period threshold, process the samples to provide frequency spectrum information of the noise event, determine whether the noise event is a potential bullying occurrence based on comparing the frequency spectrum information of the noise event and at least one frequency spectrum profile, and initiate a bullying notification in a case of determining that the noise event is a potential bullying occurrence.

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.

An abnormality cause identifying system for a device including a rotating member includes: acceleration sensors, a pickup sensor, and a temperature sensor, which observe a state of a rotating member and acquire a measurement data piece; a measurement data piece converting portion configured to convert the measurement data piece into two or more new-format conversion data pieces that are different from each other; and an abnormality cause identifying portion configured to identify an abnormality cause of the device by analyzing the conversion data pieces created by the measurement data piece converting portion.