Methods, systems, and computer storage media for providing an indication of an integrity of an object based on a non-invasive assessment of the integrity of the object using acoustic signature management engine in object integrity sensing system. In operation, an aggregate object-intermediate-medium sound of an object in an intermediate medium is detected (e.g., via sensors). An acoustic signature of the aggregate object-intermediate-medium sound is generated as a processed acoustic channel associated with statistical measurements. A reference acoustic signature of the object and intermediate medium is accessed. The reference acoustic signature is associated with an acoustic signature computation model, that generates reference acoustic signatures based on a mean and standard deviation measurements of input signals transmitted through the object and intermediate medium. A determination whether the object has impaired integrity is determined based on a quantified difference between the acoustic signature of the aggregate object-intermediate-medium sound and the reference acoustic signature.

Method and apparatus estimate the length of a fatigue crack in sheet metal structures from individual acoustic emission (AE) signals without recourse to the AE signal history or AE signal amplitude. AE energy generated at one crack tip travels to the other tip and establishes a standing wave pattern that has a characteristic dominant frequency which depends on the crack length. Therefore, crack length information can be recovered from the analysis of the standing wave frequency present in the high-frequency AE signals. We found that the AE signals predicted through numerical simulation have embedded in the high-frequency information that can be related directly to crack size. This information is manifested as peaks in the frequency spectrum that shift as crack length changes. The predictive AE models were tuned against experimentally observed AE signals and a methodology for predicting crack length from AE signals was established. This methodology was utilized to develop machine learning algorithms for predicting crack length directly from individual AE signals. Specific artificial intelligence methodology presently disclosed can estimate in real-time the crack length information from the high-frequency AE waveforms during fatigue crack growth.

An acoustic scatterometer has an acoustic source operable to project acoustic radiation onto a periodic structure and formed on a substrate. An acoustic detector is operable to detect the −1st acoustic diffraction order diffracted by the periodic structure and while discriminating from specular reflection (0th order). Another acoustic detector is operable to detect the +1st acoustic diffraction order diffracted by the periodic structure, again while discriminating from the specular reflection (0th order). The acoustic source and acoustic detector may be piezo transducers. The angle of incidence of the projected acoustic radiation and location of the detectors and are arranged with respect to the periodic structure and such that the detection of the −1st and +1st acoustic diffraction orders and discriminates from the 0th order specular reflection.

A system for estimating both thickness and wear state of refractory material (1) of a metallurgical furnace (12), including at least on processor including a database of simulated frequency domain data named simulated spectra representing simulated shock waves reflected in simulated refractory materials of known state and thickness, each simulated spectrum being correlated with both known state and thickness data of the considered simulated refractory material, wherein the at least one processor is configured to record a reflected shock wave as a time domain signal, and to convert it into frequency domain data named experimental spectrum, and are further configured to compare the experimental spectrum with at least a plurality of simulated spectra from the database, to determine the best fitting simulated spectrum with the experimental spectrum and to estimate thickness and state of the refractory material (1) of the furnace (12) using known state and thickness data correlated with the best fitting simulated spectrum.

A system comprising a computer readable storage device readable by the system, tangibly embodying a program having a set of instructions executable by the system to perform the following steps for indication confirmation for detecting a sub-surface defect, the set of instructions comprising: an instruction to initialize a transducer starting location and a transducer orientation responsive to a prior determination of a potential flaw location; an instruction to optimize an observation point of the transducer responsive to the transducer starting location and the transducer orientation responsive to a flaw response model; an instruction to move the transducer to the observation point location and orientation; an instruction to collect the scan data at the observation point location and orientation; and an instruction to analyze the scan data to extract a measure of the flaw response model; and an instruction to update the flaw response model.

A system for detecting a sub-surface defect comprising a transducer fluidly coupled to a part located in a tank containing a liquid configured to transmit ultrasonic energy, the transducer configured to scan the part to create scan data of the scanned part; a pulser/receiver coupled to the transducer configured to receive and transmit the scan data; a processor coupled to the pulser/receiver, the processor configured to communicate with the pulser/receiver and collect the scan data; and the processor configured to detect the sub-surface defect and the processor configured to have a sub-surface defect confidence assessment and a prioritization for further human evaluation.

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.

Pressure-inducing devices and pressure transducers can be used to detect and quantify liquid pools in hydrocarbon fluid pipelines. Pressure fluctuations can be detected by a pressure transducer, where the pressure fluctuations are the response of a pressure-inducing device outputting a pressure signal in a pipe carrying hydrocarbons. Variation in a pipe diameter caused by pooling or deposition can be estimated using an inverse model. The pooling or depositions can be classified by applying a machine-learning model to the pressure fluctuations. The variation in pipe diameter can be converted to an equivalent liquid volume for pooling locations. A pooling or deposition location and volume can be output and used for determining an action on the pipe to remove the pooling or deposition.

A sound source device and a signal receiver are disposed at first and second ports of a target object, respectively. A sound of a specific frequency of the sound source device is introduced into the target object to generate a resonant sound wave. A computer simulates a signal generated when the resonant sound wave is received by the signal receiver and regarding the signal as reference information. The reference information comprises first data having characteristics of the resonant sound wave, and data having features of an imaginary defect formed on the target object. The features of the imaginary defect correspond to the characteristics of the resonant sound wave. When the target object has a real defect, the sound of the specific frequency of the sound source device is introduced into the target object. Features of the real defect are derived by comparing the first data with the second data.

A measuring system is disclosed. The measuring system includes a surface acoustic wave (SAW) device including a piezoelectric substrate and a first and second electrode disposed on a surface of the piezoelectric substrate, and a measuring device communicatively coupled to the first electrode via a first probe and the second electrode via a second probe and configured to apply an electrical signal to the first and second electrode to generate an incident bulk acoustic wave within the piezoelectric substrate, detect at least a first reflected bulk acoustic wave and a second reflected bulk acoustic wave at the first and second electrode, and calculate a thickness between a first interface corresponding to the first reflected bulk acoustic wave and a second interface corresponding to the second reflected bulk acoustic wave based on a time elapsed between detecting the first and second reflected bulk acoustic waves.