An AE-signal detecting device for an abrasive wheel includes: an AE sensor which outputs an AE signal upon receipt of an elastic wave generated in an annular abrasive wheel sandwiched between a fixed flange fixed to a rotating shaft and a movable flange provided capable of getting closer to/separating from the fixed flange; a transmission circuit portion which wirelessly transmits the AE signal output from the AE sensor; and a reception circuit portion which receives the AE signal transmitted wirelessly, wherein the AE sensor is disposed on the movable flange or the fixed flange, detects the elastic wave transmitted from the abrasive wheel, and outputs the AE signal.

An AE-signal detecting device for an abrasive wheel includes: an AE sensor which outputs an AE signal upon receipt of an elastic wave generated in an annular abrasive wheel sandwiched between a fixed flange fixed to a rotating shaft and a movable flange provided capable of getting closer to/separating from the fixed flange; a transmission circuit portion which wirelessly transmits the AE signal output from the AE sensor; and a reception circuit portion which receives the AE signal transmitted wirelessly, wherein the AE sensor is disposed on the movable flange or the fixed flange, detects the elastic wave transmitted from the abrasive wheel, and outputs the AE signal.

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.

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.

A rotating machine abnormality detection device of an embodiment includes a non-contact acoustic emission sensor, an analyzer, and a diagnoser. The non-contact acoustic emission sensor, arranged at a position spaced away by a predetermined distance from a measurement target acting as a rotating member or a measurement target rotatably supporting the rotating member, is configured to detect acoustic emission that occurs during rotation of the measurement target or the rotating member supported by the measurement target and propagates in an atmosphere. The analyzer is configured to perform time-frequency analysis on a detection signal of the non-contact acoustic emission sensor. The diagnoser is configured to detect occurrence of a rotation abnormality when a frequency component equal to or larger than a predetermined threshold value is present in a predetermined frequency band, based on an analysis result of the analyzer.

A rotating machine abnormality detection device of an embodiment includes a non-contact acoustic emission sensor, an analyzer, and a diagnoser. The non-contact acoustic emission sensor, arranged at a position spaced away by a predetermined distance from a measurement target acting as a rotating member or a measurement target rotatably supporting the rotating member, is configured to detect acoustic emission that occurs during rotation of the measurement target or the rotating member supported by the measurement target and propagates in an atmosphere. The analyzer is configured to perform time-frequency analysis on a detection signal of the non-contact acoustic emission sensor. The diagnoser is configured to detect occurrence of a rotation abnormality when a frequency component equal to or larger than a predetermined threshold value is present in a predetermined frequency band, based on an analysis result of the analyzer.

Method for monitoring the operation of a pair of turboprop engines of an aircraft comprising the steps of: detecting the sound pressure generated by the first or second turboprop engine generating a respective first or second signal x(t); iteratively calculating by means of a function Rx/Ry the similarity between the first/second signal x(t)/y(t) at a time T1 and at a time T2 subsequent to time T1; and storing the degrees of similarity calculated in successive iterations in order to detect situations of normal operation of the engines when the degrees of similarity fall in successive iterations within the interval of a first value and to detect a potential fault situation in the engines when the degrees of similarity depart from this interval.

A method of determining wear/degradation levels of a consumable assembly of a welding/plasma torch may utilize a controlled sound signal in order to determine an acoustic profile or full spectral audio analysis dataset of the consumable assembly that facilitate the identification of patterns that correlate to certain wear/degradation levels of the consumable assembly. The full spectral audio analysis dataset may be obtained by subjecting a given consumable assembly to a controlled sound signal between operations and as the consumable assembly degrades over time. The full spectral audio analysis may serve as a wear/degradation profile over the life of the given consumable assembly. With a full dataset known for a particular consumable assembly model, an acoustic profile of another consumable assembly of the same model may be obtained and compared to the full dataset in order to identify the wear/degradation level of the tested consumable assembly.

A method of determining wear/degradation levels of a consumable assembly of a welding/plasma torch may utilize a controlled sound signal in order to determine an acoustic profile or full spectral audio analysis dataset of the consumable assembly that facilitate the identification of patterns that correlate to certain wear/degradation levels of the consumable assembly. The full spectral audio analysis dataset may be obtained by subjecting a given consumable assembly to a controlled sound signal between operations and as the consumable assembly degrades over time. The full spectral audio analysis may serve as a wear/degradation profile over the life of the given consumable assembly. With a full dataset known for a particular consumable assembly model, an acoustic profile of another consumable assembly of the same model may be obtained and compared to the full dataset in order to identify the wear/degradation level of the tested consumable assembly.

In some examples, a distributed acoustic detector system may include a frame structure and multiple acoustic detectors. The frame structure may be configured to be retained in a laser-based ophthalmo-logical surgical system aligned to an eye of a patient during therapeutic treatment of the eye of the patient with the laser-based ophthalmological surgical system. The acoustic detectors may be coupled to the frame structure and may be spaced apart from each other and electrically separated from each other.