This present disclosure describes an ultrasound image display method and apparatus, a storage medium, and an electronic device. The method includes acquiring, by a device, an input signal by performing detection on a to-be-detected object, the input signal comprising a three-dimensional (3D) radio-frequency (RF) signal. The device includes a memory storing instructions and a processor in communication with the memory. The method also includes performing, by the device, a modulus calculation on the 3D RF signal to obtain envelope information in a 3D ultrasound image, the modulus calculation being at least used for directly acquiring a 3D amplitude of the 3D RF signal; and displaying, by the device, the envelope information in the 3D ultrasound image, the envelope information being at least used for indicating the to-be-detected object.

Described herein are systems and methods based on acoustic emission (AE) technology to monitor a concrete structure for a short interval and, based on signals acquired, estimate Alkali-silica reaction (ASR) progression status in the structure remotely and efficiently without halting any serviceability and operational activities of the structure, knowing the ASR progression status of the structure helps determine rehabilitation and future structural safety and serviceability of the structure.

To provide an anomalous sound detection training technique by which a feature amount extraction function for detecting anomalous sound can be generated irrespective of whether training data for anomalous signals is available or not. An anomalous sound detection training apparatus includes: a first function updating unit 3 that updates a feature amount extraction function and an feature amount inverse transformation function, which are input, based on an optimization index of a variational autoencoder; an acoustic feature extraction unit 4 that extracts an acoustic feature of normal sound based on training data for normal sound; a normal sound model updating unit 5 that updates a normal sound model by using the acoustic feature that is extracted; a threshold updating unit 6 that obtains a threshold φ.sub.ρ corresponding to a false positive rate ρ, which has a predetermined value, by using the training data for normal sound and the feature amount extraction function that is input; and a second function updating unit 8 that updates the feature amount extraction function that is updated, based on a Neyman-Pearson-type optimization index defined by the threshold φ.sub.ρ that is obtained, and repeatedly performs processing of each of the above-mentioned units.

Method and apparatus for monitoring and diagnosing gun performance is derived that can determine proper gun operation and if not operating properly diagnose potential causes for abhorrent operation. The voltage produced by the gun is sampled in real time and the frequency spectrum produced analyzed using FFT and then reducing the FFT pattern down to a set of numerical values or a signature that can be compared to known signatures for both correct operation and abnormal operation. Using best fit techniques the cause of any abnormal behavior can then be identified. The method can also be used to predict the end of hardware life and aid in production scheduling and spare parts acquisition by providing advanced notice of wear and usage.

In accordance with a method for characterization of particles in a fluid-filled hollow structure, an ultrasound signal with a frequency spectrum, which exhibits a local maximum at a variable measurement frequency, is emitted in the direction of a part area of the hollow structure and reflected components are detected. The measurement frequency is tuned in a predetermined measurement interval, and depending on the detected reflected components, a spectral response curve is acquired as a function of the measurement frequency. Depending on the response curve, at least one characteristic property for a part of the particles located in the part area of the hollow structure is determined. The characteristic property includes a measure for an adhesion of the particles of the part of the particles located in the part area of the hollow structure.

A system for monitoring an acoustic scene outside a vehicle; the system including: a vehicle with wheels and a trunk, an acoustic sensor disposed in the trunk, a control unit operatively connected to the acoustic sensor, and at least one neural network operatively connected to the control unit, and trained in such a way to correlate the characteristics of an audio signal with types of road surfaces; the control unit is configured in such a way to receive an audio signal detected by the acoustic sensor while the vehicle is traveling, extract the characteristics of the audio signal and input said characteristics of the audio signal to the neural network in order to identify the type of road surface covered by the vehicle wheels.

The disclosure discloses a stress gradient high-efficiency non-destructive detection system based on frequency domain calculation of broadband swept frequency signals, and a detection method thereof. The detection method includes: step 1: calibrating an LCR wave velocity of an object to be measured; step 2: calculating a starting frequency and a cut-off frequency of broadband swept frequency signals based on the LCR wave velocity of the object to be measured in the step 1 and a stress gradient measuring range in a depth direction of the object to be measured; step 3: converting phase delay to time delay information based on the phase delay of the starting frequency and the cut-off frequency in the step 2; and step 4: determining stresses of depths corresponding to different frequency components based on the time delay information in the step 3 to finally realize layer-by-layer scanning of stresses at different depths of the measured object. The disclosure is used to solve the problem of low stress gradient measuring accuracy, and realize the high-efficiency characterization of the stress gradient in the depth direction.

An ultrasound transmitting and receiving device that can determine whether a contact state between a probe and a bolt is normal without relying on the skill of an operator is provided. The ultrasound transmitting and receiving device includes a probe control unit, an auxiliary storage device, and a contact state determination unit. The probe control unit causes a probe to transmit ultrasound to a bolt, and causes the probe to receive an echo of the transmitted ultrasound. The auxiliary storage device stores one or more pieces of comparison data to be compared with echo data indicating the echo received by the probe. The contact state determination unit compares the echo data with the comparison data, and determines a contact state between the probe and the bolt based on a comparison result.

An inspection device includes a first data storage unit configured to store a first data which is time series according to a state of an inspection object, a second data generation unit configured to generate second data, which is a spectrogram including a first frequency component, a time component, and an amplitude component by performing short-time Fourier transform on the first data, a third data generation unit configured to generate third data including the first frequency component, a second frequency component, and the amplitude component by performing Fourier transform on time-amplitude data for each first frequency component in the second data, respectively, and a determination unit configured to determine the state of the inspection object based on the third data.

An inspection device includes a first data storage unit configured to store a first data which is time series according to a state of an inspection object, a second data generation unit configured to generate second data, which is a spectrogram including a first frequency component, a time component, and an amplitude component by performing short-time Fourier transform on the first data, a third data generation unit configured to generate third data including the first frequency component, a second frequency component, and the amplitude component by performing Fourier transform on time-amplitude data for each first frequency component in the second data, respectively, and a determination unit configured to determine the state of the inspection object based on the third data.