A method and apparatus for inspecting a fusion joint is provided. The apparatus includes a processor, an ultrasound (“US”) probe in communication with the processor, and a database comprising classification rules. The processor is configured to generate an initial set of US scanning positions about the fusion joint based on information of at least one of the US probe and the fusion joint; measure, via the US probe, a US pulse-echo spectrum from at least two of the initial US scanning positions; compare each measured US pulse-echo spectrum with one or more known US pulse-echo spectrums; classify each measured US pulse-echo spectrum according to the classification rules; and evaluate an aggregate of measured US pulse-echo spectrums to determine if the fusion joint is defective.

A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process includes acquiring first sound data collected by a first microphone and second sound data collected by a second microphone during traveling of a vehicle in which the first microphone is provided in vicinity of a front wheel and the second microphone is provided in vicinity of a rear wheel; and detecting a cavity under a road surface where the vehicle has traveled based on a difference between the acquired first sound data and the acquired second sound data.

A system for monitoring and identifying states of a semiconductor device, the system including at least one acoustic sensor for sensing acoustic emission emitted by at least one semiconductor device operating at a voltage of less than or equal to 220 V, the at least one acoustic sensor outputting at least one acoustic emission signal and a signal processing unit for receiving the at least one acoustic emission signal from the at least one acoustic sensor and for analyzing the at least one acoustic emission signal, the signal processing unit providing an output based on the analyzing, the output being indicative at least of whether the at least one semiconductor device is in an abnormal operating state with respect to a normal operating state of the semiconductor device.

Embodiments provide systems and methods for utilizing acoustic sensors to detect defects via online or in situ monitoring of additive manufacturing (AM) processes. Sensors may capture acoustic waves associated with AM manufacturing operations. The acoustic emissions in combination with other sensing data, such as cameras or thermometers, may be used to characterize the state of the AM process, such as to detect a defect has occurred or confirm a defect has not occurred. When defects are detected, the AM process may be stopped to prevent further processing of a defective part. When defects are predicted as likely to occur, operational parameters of the AM device or process may be adjusted to mitigate the occurrence of a defect. The techniques disclosed herein enable detection of defects that occur underneath the surface of the part being manufactured, as well as correct issues with the AM device or process before a defect occurs.

A device and a method for measuring and/or monitoring at least one process variable of a medium is provided. The device comprises a sensor unit with a mechanically vibrating unit, at least one reflection unit, a piezoelectric element which is attached to the membrane, and an electronic. The device is designed to excite the mechanically vibrating unit to mechanical vibrations using an excitation signal, to receive the mechanical vibrations of the vibrating unit and convert them into a first reception signal, to emit a transmission signal, and to receive a second reception signal. The electronic unit is designed to determine the at least one process variable of the medium based on the first and/or second reception signal.

An apparatus may include one or more optical fibers, one or more optical waveguides, and multiple resonator nodes arranged in an array of sensing locations. Each resonator node may include an optical coupling between an optical waveguide and an optical fiber having a set of resonant frequencies at a respective sensing location. Each resonator node may be further configured to communicate a set of signals corresponding to at least one shift in the set of resonant frequencies in the optical fiber at the respective sensing location.

A method and system for identifying a cavity position of a structure based on global search includes: step 1: using a structure requiring cavity position identification as a target area, arranging acoustic emission sensors at key positions of the target area, and acquiring actual travel time of signals between the acoustic emission sensors on site; step 2: constructing cavity models for the target area; and for each cavity model, tracking shortest paths of signal propagation between the acoustic emission sensors when each cavity model exists in the target area, to obtain theoretical travel time of the signals; and step 3: respectively calculating deviations between the theoretical travel time and the actual travel time of the signals between the acoustic emission sensors corresponding to each cavity model, and using a position of a cavity model corresponding to a minimum deviation as an identified cavity position in the target area.

Embodiments provide systems and methods for utilizing acoustic sensors to detect defects via online or in situ monitoring of additive manufacturing (AM) processes. Sensors may capture acoustic waves associated with AM manufacturing operations. The acoustic emissions in combination with other sensing data, such as cameras or thermometers, may be used to characterize the state of the AM process, such as to detect a defect has occurred or confirm a defect has not occurred. When defects are detected, the AM process may be stopped to prevent further processing of a defective part. When defects are predicted as likely to occur, operational parameters of the AM device or process may be adjusted to mitigate the occurrence of a defect. The techniques disclosed herein enable detection of defects that occur underneath the surface of the part being manufactured, as well as correct issues with the AM device or process before a defect occurs.

Various embodiments include a method for determining the mixing ratio R of a fluid comprising a mixture of at least two different fluids for a technical process in a device comprising: irradiating an ultrasonic signal with a transmission level along a measuring distance running inside a measuring section; measuring a receiving level of the ultrasonic signal at one end of the measuring distance; determining an ultrasonic attenuation of the ultrasonic signal attenuated by the fluid based at least on the transmission and receiving levels of the ultrasonic signal; measuring a temperature of the fluid flowing through the measuring section; and determining a mixing ratio of the at least two different fluids from the determined ultrasonic attenuation and from the measured fluid temperature.

An acoustic garbage classification method using a one-dimensional convolutional neural network (1D-CNN) is provided. The method includes: acquiring sound signals generated by falling garbage; preprocessing the sound signals; acquiring and preprocessing the sound signals of different types of garbage, building a sound database for garbage classification, and establishing and training a 1D-CNN model; acquiring a sound signal of garbage to be classified, and inputting the sound signal into the trained 1D-CNN for garbage classification to obtain a classification result. The present disclosure is helpful to assist people in accurate garbage classification, improves the accuracy of garbage classification and recycling, and has high practical and popularization value.