The disclosure discloses an air-coupled ultrasonic detection method and device based on a defect probability reconstruction algorithm. The method includes the following steps: determining the excitation frequency of a transmitting air-coupled transducer according to a frequency dispersion curve of guided waves and the thickness of a to-be-detected piece; determining the group velocity of an antisymmetric mode according to the excitation frequency, and determining the inclination angle of the transmitting/receiving air-coupled transducer according to the Snell law; obtaining an initial waveform of a defect-free test piece as reference data by adopting a same-side penetration method, then rotating the transmitting/receiving transducer by 360 degrees by taking the Z direction as an axis at preset angle intervals by adopting a rotary scanning method, collecting N groups of signal data of the to-be-detected piece again, comparing the N groups of signal data with the reference data to determine whether the signal characteristics have great changes or not, calculating the defect distribution probability on the to-be-detected piece, and carrying out defect imaging on a rotating coverage area of the transmitting/receiving air-coupled transducer according to the defect distribution probability. According to the method, the precision of traditional air-coupled ultrasonic X and Y scanning detection is improved, and compared with a complex imaging technology, the air-coupled ultrasonic detection method consumes less time.

Waves from cement bond logging with a sonic logging-while-drilling tool (LWD-CBL) are often contaminated with tool waves and may yield biased CBL amplitudes. The disclosed LWD-CBL wave processing corrects the first echo amplitudes of LWD-CBL before calculating the BI. The LWD-CBL wave processing calculates a tool wave amplitude and a phase angle difference as the difference of the phases between the tool waves and casing waves. The tool waves are then used to correct the LWD-CBL casing wave amplitude and remove errors introduced from tool waves. In conjunction with the sets of operations described, the LWD-CBL wave processing also include array preprocessing operations. Array preprocessing may employ variation of bandpass filtering and frequency-wavenumber (F-K) filtering operations to suppress tool wave.

An electro-magnetic acoustic transducer (EMAT) system and method for controlling the EMAT system are provided. The system includes an electromagnet array with one or more electromagnets. Each electromagnet includes a magnetic core and a wound coil wrapped around the magnetic core. The electromagnet array generates bias magnetic fields having different patterns when the wound coils are energized differently.

A NEMS readout system includes a sensor array comprising a plurality of sensors. Each sensor of the plurality of sensors including a resonator with frequency characteristics different from the resonator of each other sensor of the plurality of sensors. A readout signal indicative of a plurality of output signals is collected from the sensor array. Each output signal of the plurality of output signals corresponding to one of the plurality of sensors. An analysis of the plurality of output signals is performed to identify a plurality of resonant frequencies and to detect a frequency shift associated with at least one of the plurality of resonant frequencies.

Embodiments herein provide a method and system for a non-invasive mechanism providing simultaneous determination of viscosity-temperature variation of a lubricant for predicting machine health using a Photo Acoustic (PA) sensing mechanism, Laser-enabled swept frequency acoustic interferometry (LE-SFAI), wherein the lubricant produces acoustic wave only if it absorbs the laser irradiation, thus overcomes the limitation of ultrasound based SFAI through optical absorption based contrast and proper selection of laser excitation wavelength. A PA signal received from the lubricant is processed by a Vector Network Analyzer (VNA), then converted to time domain to obtain normalized first peak that corresponds to the PA signal generated by the lubricant. A squared rise time of the first peak is indicative of viscosity of the liquid and shift in the first peak is indicative of variation of the viscosity as temperature of the lubricant varies.

Methods for processing data acquired using ultrasound elastography, in which shear waves are generated in a subject using continuous vibration of the ultrasound transducer, are described. The described methods can effectively separate shear wave signals from signals corresponding to residual motion artifacts associated with vibration of the ultrasound transducer. The systems and methods described here also provide for real-time visualization of shear waves propagating in the subject.

The present disclosure provides a system and method for real-time visualization of a material during ultrasonic non-destructive testing. The system includes a graphical user interface (GUI) capable of showing a three-dimensional (3-D) image of a composite laminate constructed of a series of two-dimensional (2-D) cross sections. The GUI is capable of displaying the 3-D image as each additional 2-D cross section is scanned by an ultrasonic testing apparatus in real time or near real time, including probable defect regions that contain a flaw such as a hole, crack, wrinkle, or foreign object within the composite. Furthermore, in one embodiment, the system includes an artificial intelligence capable of highlighting defect areas within the 3-D image in real time or near real time and providing data regarding each defect area, such as the depth, size, and/or type of each defect.

The present disclosure provides a system and method for real-time visualization of a material during ultrasonic non-destructive testing. The system includes a graphical user interface (GUI) capable of showing a three-dimensional (3-D) image of a composite laminate constructed of a series of two-dimensional (2-D) cross sections. The GUI is capable of displaying the 3-D image as each additional 2-D cross section is scanned by an ultrasonic testing apparatus in real time or near real time, including probable defect regions that contain a flaw such as a hole, crack, wrinkle, or foreign object within the composite. Furthermore, in one embodiment, the system includes an artificial intelligence capable of highlighting defect areas within the 3-D image in real time or near real time and providing data regarding each defect area, such as the depth, size, and/or type of each defect.

The present disclosure provides a system and method for real-time visualization of a material during ultrasonic non-destructive testing. The system includes a graphical user interface (GUI) capable of showing a three-dimensional (3-D) image of a composite laminate constructed of a series of two-dimensional (2-D) cross sections. The GUI is capable of displaying the 3-D image as each additional 2-D cross section is scanned by an ultrasonic testing apparatus in real time or near real time, including probable defect regions that contain a flaw such as a hole, crack, wrinkle, or foreign object within the composite. Furthermore, in one embodiment, the system includes an artificial intelligence capable of highlighting defect areas within the 3-D image in real time or near real time and providing data regarding each defect area, such as the depth, size, and/or type of each defect.

Relating to the technical field of batteries, and provided are a battery fault detection method, a battery fault detection system, a terminal, and a computer-readable storage medium. The method comprises: by means of a vibration generation device, sequentially applying a preset number of vibration signals of different frequencies to a battery to be tested (301); collecting response signals of the battery by means of a response collection device (302), the response signals comprising a preset number of vibration response amplitudes of the battery, wherein the preset number of vibration response amplitudes are separately generated by the battery under the action of vibration signals of different frequencies; and according to the response signals, determining whether the battery is faulty (303). By means of the described method, it is possible to quickly and non-destructively detect whether a battery is faulty.