A computer implemented method processes time waveform machine vibration data that are indicative of operational characteristics of a machine. The data, which were measured on the machine over a period of time having a begin time and an end time, are accessed from a memory or storage device. An integer number M of waveform samples are determined from the data to be averaged, and an asymptotically decaying DC bias component in the data is derived using a moving average of the M number of waveform samples. The DC bias component is extrapolated from the begin time of the waveform back to an earlier time and from the end time of the waveform forward to a later time. The DC bias component is then subtracted from the time waveform data, and a Fast Fourier Transform is performed on the data to generate a spectrum.

A photoacoustic measurement setup having an infrared radiator that is suitable for radiating broadband light with periodically modulated energy/intensity. The infrared radiator is configured to change an excitation spectra of a radiated broadband light, and a gas volume is heated by the radiated broadband light to generate an acoustic wave within the gas volume. The photoacoustic measurement setup also includes an acoustic sensor, which is suitable for measuring the acoustic wave generated in the gas volume.

A method of distinguishing a first physical phenomenon captured in a sensory measurement time waveform from a second physical phenomenon captured in the waveform includes: receiving the waveform on a processor from a sensor in sensory contact with an object undergoing first and second physical phenomena, wherein the first phenomenon is a comparatively fast event; deriving a first rate of change data stream from the time waveform with a processor operable on a processor, wherein each value of the first rate of change data stream is based on a difference in extreme amplitudes of the waveform during a first interval of waveform samples; and analyzing with the processor the derived first rate of change data stream to distinguish the comparatively fast first physical phenomena from the second physical phenomenon captured in the waveform.

The disclosure includes a system for photoacoustic inspection of an object. The system includes a broadband emission source configured to generate an emission beam, a direction apparatus including at least one spectrum splitter configured to split the emission beam into at least a first and a second component, the direction apparatus being configured to sequentially direct the respective components to N respective locations on the object at N times to generate N respective acoustic waves within the object. The N respective locations and N times are such that the respective N acoustic waves at least semi-constructively interfere to generate a respective propagating acoustic wave within the object. The system also includes a vibration sensing system configured to detect said respective propagating acoustic waves at a respective detection location on the object.

The disclosure includes a system for photoacoustic inspection of an object. The system includes a broadband emission source configured to generate an emission beam, a direction apparatus including at least one spectrum splitter configured to split the emission beam into at least a first and a second component, the direction apparatus being configured to sequentially direct the respective components to N respective locations on the object at N times to generate N respective acoustic waves within the object. The N respective locations and N times are such that the respective N acoustic waves at least semi-constructively interfere to generate a respective propagating acoustic wave within the object. The system also includes a vibration sensing system configured to detect said respective propagating acoustic waves at a respective detection location on the object.

This wedge looseness inspector for a rotary electric machine includes: an inspector including a wedge striker having a tap hammer for striking a wedge, and a wedge vibration detector for detecting vibration of the wedge; and attraction portions connected to the inspector via connection members and being attractable to an outer circumferential surface of a stepped-down portion, wherein the attraction portions have, on an inner side in the axial direction, first attachments that allow adjustment of the attached position in the axial direction of the attraction portions or replacement thereof.

A sensor system includes one or more sensors that sense vibrations of a vehicle and one or more processors that can determine a speed of the vehicle and determine whether the vibrations occurring at one or more frequencies of interest (that are based on the speed of the vehicle) indicate damage to a propulsion system of the vehicle. The one or more processors optionally may determine a hunting frequency of a wheel and axle set and/or a lateral acceleration of the wheel and axle set from the vibrations. The one or more processors can determine a conicity of a wheel in the wheel and axle set based on the hunting frequency and/or the lateral acceleration that is determined.

A sensor system includes one or more sensors that sense vibrations of a vehicle and one or more processors that can determine a speed of the vehicle and determine whether the vibrations occurring at one or more frequencies of interest (that are based on the speed of the vehicle) indicate damage to a propulsion system of the vehicle. The one or more processors optionally may determine a hunting frequency of a wheel and axle set and/or a lateral acceleration of the wheel and axle set from the vibrations. The one or more processors can determine a conicity of a wheel in the wheel and axle set based on the hunting frequency and/or the lateral acceleration that is determined.

The technology disclosed relates to systems, methods, and devices for non-destructive evaluation (NDE) of a wooden specimen. A computer-implemented method for non-destructive evaluation of a wooden specimen comprises receiving acoustic wave signal data from NDE of the wooden specimen; processing the acoustic wave signal data to determine signal characteristics, such as an arrival velocity and amplitude attenuation of an AW2 mode; determining, based in part on a characteristic of the AW2 wave, an estimated strength metric of the wooden specimen; and displaying, on a graphical user interface associated with the computing device, an indication of the estimated strength metric of the wooden specimen.

The technology disclosed relates to systems, methods, and devices for non-destructive evaluation (NDE) of a wooden specimen. A computer-implemented method for non-destructive evaluation of a wooden specimen comprises receiving acoustic wave signal data from NDE of the wooden specimen; processing the acoustic wave signal data to determine signal characteristics, such as an arrival velocity and amplitude attenuation of an AW2 mode; determining, based in part on a characteristic of the AW2 wave, an estimated strength metric of the wooden specimen; and displaying, on a graphical user interface associated with the computing device, an indication of the estimated strength metric of the wooden specimen.