A pulsed laser interferometer includes: a pulsed laser; a vibration controller that produces a vibration control signal that controls a vibrational frequency and vibrational amplitude of a structural member; an interferometer controller; a pathlength control stage that changes an optical pathlength for laser pulses; a pathlength reflector that moves in concert with the pathlength control stage to change the optical pathlength of propagation for the laser pulses; a light pulse detector that produces a light pulse detector signal; an interference light detector that produces an interference frequency signal; a signal mixer that produces a reference frequency signal; and a phase-sensitive detector that produces a vibrational amplitude signal and a vibrational phase signal from the interference frequency signal referenced to the reference frequency signal.

A device and method for evaluating long-term operation of a transformer oil pump. An inlet of an oil pump is connected to an outlet of an oil tank through an oil pipe, and an outlet of the oil pump is connected to an inlet of the oil tank through an oil pipe. A pressure gauge is provided on the oil pipe to the inlet and the outlet of the oil pump, respectively. An ultra-high-frequency (UHF) sensor is provided on an inner wall of an oil pipe close to the oil pump. A pressure difference between the oil pipes to the inlet and to the outlet of the oil pump is monitored. A three-phase unbalanced current of a stator winding is monitored. The vibration of the oil pump is monitored. The rotor-to-stator rub is monitored. Based on the above inspection, a long-term health status of the oil pump is determined.

An airborne sound transducer comprises an electromechanical transducer, an air impedance matching layer arranged on an acoustically active surface of the electromechanical transducer, and a cover arranged on the air impedance matching layer, an outer surface of the cover forming an exposed acoustic area of the airborne sound transducer. The outer surface is hydrophilic such that a contact angle of water on the outer surface is less than 60°.

A sensor or receiver array includes first and second pyroelectrically active electrodes formed of polyvinylidene difluoride and separated by a spacer layer that acts to electrically separate the pyroelectric layers while keeping them close enough such that they see effectively the same vibration or background acoustic excitation while maintaining sufficient separation to ensure that they generate significant differences in their pyroelectric responses. The structure provides two distinct signals (at separate timestamps), the difference between which provides a more accurate signal. An ultrasound detection system includes the tri-laminar sensor, disposed within a detection zone in which a test element can be positioned. The apparatus includes a processing unit, which comprises a detector unit coupled to the first and second pyroelectric elements and configured to derive a differential signal from the first and second pyroelectric elements. A processor is coupled to the detector unit and is configured to generate an electrical output waveform on the basis of the data extracted from first and second pyroelectric elements.

A measurement apparatus and method for in-situ quantitative texture measurement of a food snack. The apparatus includes an acoustic capturing device and a data processing unit. The physical interaction in the mouth with saliva, when a human being eats/drinks a food snack, sends pressure waves that propagate through the ear bone and produce an acoustic signal. The acoustic capturing device records and forwards the signal to a data processing unit. The data processing unit further comprises a digital signal processing module that smoothens, transforms and filters the received acoustic signal. A statistical processing module further filters the acoustic signal from the data processing unit and generates a quantitative acoustic model for texture attributes such as hardness and fracturability. The quantitative model is correlated with a qualitative texture measurement from a descriptive expert panel. Another method includes a food snack fingerprinting using an in-situ quantitative food property measurement.

Ultrasonic transducer (1) comprising a coupling element (3) and a piezo element (2), wherein a metal disk (4) is arranged between the coupling element (3) and the piezo element (2), wherein the metal disk (4) is connected with the piezo element (2) or with the coupling element (3) by means of an adhesive layer (5 or 6), characterized in that the adhesive layer (5 or 6) is producible, at least in certain regions, by means of a photochemically curable adhesive.

A photo acoustic non-destructive measurement apparatus and method for quantitatively measuring texture of a food snack is disclosed. The apparatus includes a laser generating tool, an acoustic capturing device, and a data processing unit. The laser generating tool directs a laser towards a food snack placed on a surface and creates pressure waves that propagate through the air and produce an acoustic signal. The acoustic capturing device records and forwards the signal to a data processing unit. The data processing unit further comprises a digital signal processing module that processes the received acoustic signal. A statistical processing module further filters the acoustic signal from the data processing unit and generates a quantitative acoustic model for texture attributes such as hardness and fracturability. The quantitative model is correlated with a qualitative texture measurement from a descriptive expert panel. Texture of food snacks are quantitatively measured with the quantitative acoustic model.

A portable facility failure diagnosis device using detection of radiation ultrasonic waves, comprising: an ultrasonic sensor array; a data acquisition board (DAQ board) in which an electronic circuit for acquiring ultrasonic signals at a sampling frequency of the ultrasonic signals sensed by the ultrasonic sensor array is mounted on a substrate of the data acquisition board (DAQ board); a main board in which an operation processing device that processes the ultrasonic signals received from the DAQ board is mounted on the substrate and the processed ultrasonic sound source information to a display device; a data storage medium storing data processed in the operation processing device of the main board; a display device visually displaying the data processed; and an optical camera picking up an image of a direction.

Laser ultrasonic testing includes a laser apparatus; a splitting unit that splits a pulsed laser from the laser apparatus into first and second lasers; a first pulse width conversion unit that converts a pulse width of the first laser; a first optical system that guides the first laser having the converted pulse width to a test object; a second pulse width conversion unit that converts a pulse width of the second laser; a pulse propagation time adjustment unit that adjusts a propagation time of the second laser having the converted pulse width; a second optical system that guides the second laser having the converted pulse width and adjusted propagation time to the test object; and a detection unit that detects a surface displacement change of the test object caused by an ultrasonic wave generated by the first laser when the second laser is reflected by the test object.

The present disclosure relates to an apparatus and a method for estimating a state of an object to be heated based on sound which is generated when the object to be heated is heated, and providing the estimated information to other devices in an Internet of Things (IoT) environment through a 5G communication network. The heating apparatus may include a housing having a receiving space therein, a heating member disposed within the housing, a power supplier for supplying power to the heating member, a top plate disposed on the top of the housing to support the object to be heated, a sound sensor disposed on the bottom of the top plate, and a controller for predicting the state of the object to be heated by using a deep neural network model that has been trained through machine learning based on a sound signal received from the sound sensor.