This application relates to an apparatus and method for detecting a microcrack using orthogonality analysis of a mode shape vector and a principal plane in a resonance point. The apparatus may include a measurement unit comprising multiple sensors and configured to measure whether a crack exists at a measurement target, and an analysis unit configured to determine whether a crack exists, on the basis of measurement values of the respective sensors. The measurement unit includes a fixing jig configured to fix the measurement target, an excitation means configured to apply a predetermined impact to the measurement target, and multiple acceleration sensors attached at predetermined locations on the measurement target. The analysis unit may further calculate frequency responses of the measurement target to the impact applied by the excitation means, and determine whether a crack exists by analyzing the number of resonance points and independence of the resonance points.

A system can control a transmission of a pressure signal subsea into a flowline comprising a fluid. The system can receive sensor data indicating one or more properties of a first reflection signal corresponding to the pressure signal in the flowline. The system can adjust a model based on the one or more properties of the first reflection signal. The model can be configured for determining a presence of a material deposition in the flowline. The system can determine, based on a second reflection signal and the adjusted model, a presence of the material deposition in the flowline. The system can output a command configured to initiate a remediation operation to reduce the material deposition in the flowline.

A non-linear dynamic process such as multiphase flow is characterized to determine a condition of the process. A sensor may obtain information about strain, vibration, flow rate, etc. during the process. That sensor data may be plotted, and at least one perceptual hash can be generated from the plot. The perceptual hash can be compared against a database storing plots or hashes for non-linear dynamic responses for different sensor types or processes. A best fit hash may be identified and used to determine what conditions are occurring in the field, or multiple near fits can define an envelope of experimental/reference conditions with similar non-linear dynamics to the field system. Multiple hash comparisons may be used to refine the envelope, determine a best fit, or determine what measurement would help discriminate the flow conditions.

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.

A method for quantitatively evaluating the expected ultrasonic inspectability of a designed part using ray tracing. First, a model of a part imported. Materials having different indices of refraction are selected for the part and an acoustic coupling medium. Then the following structures and positional relationships are defined: an ultrasonic transducer array comprising a plurality of elements, a position of the acoustic coupling medium between the transducer array and the part, and a plurality of positions of a transmit aperture relative to the part. For each defined position of the transmit aperture, a path of a respective ray is traced from a center of the transmit aperture through the part and then to a respective receive location on the transducer array. Also, a respective value of an inspectability margin is calculated based at least in part on a respective distance between a center of the receive aperture and the respective receive location. Each value of the inspectability margin is compared to a threshold value.

A method and system are described for processing tissues according to particular processing protocols that are established based on time-of-flight measurements as a processing fluid is diffused into a tissue sample. In one embodiment, measurement of the time it takes about 70% ethanol to diffuse into a tissue sample is used to predict the time it will take to diffuse other processing fluids into the same or similar tissue samples. Advantageously, the disclosed method and system can reduce overall processing times and help ensure that only samples that require similar processing conditions are batched together.

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.

Methods, systems, devices, and products for evaluating a downhole fluid in a borehole intersecting an earth formation. Methods include using ultrasonic irradiation to produce sonoluminescence from cavitation in a volume of the fluid; obtaining spectral information from measurement of the sonoluminescence with a light-responsive device; and estimating a parameter of interest of the fluid from the spectral information. The parameter may be a composition of the fluid or concentration of: i) at least one chemical element in the volume; i) at least one molecular element in the volume. Methods include deconvolving a response spectrum by using one or more separately determined standard spectra, or estimating the parameter of interest using spectral lines represented by the spectral information. Methods may include using an optically transparent ultrasonic transducer to produce the cavitation at the interface of the transducer, with optically transparent ultrasonic transducer between the interface and the light-responsive device.

A method for denoising magnetostrictive guided wave detection signals to improve detection accuracy. The method includes forming a matrix A by using the signals; performing a singular value decomposition on the matrix A to obtain a singular matrix B including a plurality of eigenvalues; setting eigenvalues in the singular matrix B that are smaller than the median to zero to obtain a matrix C; performing an inverse transformation of the singular value decomposition on the matrix C to obtain a matrix D; and determining the denoised signals according to the matrix D.