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.

An acoustic inspection system can be used to generate a surface profile of a component under inspection, and then can be used to perform the inspection on the component. The acoustic inspection system can obtain acoustic imaging data, e.g., FMC data, of the component. Then, the acoustic inspection system can apply a previously trained machine learning model to an encoded acoustic image, such as a TFM image, to generate a representation of the profile of one or more surfaces of the component. In this manner, no additional equipment is needed, which is more convenient and efficient than implementations that utilize additional components that are external to the acoustic inspection system.

Provided are a non-destructive inspection system and a non-destructive inspection method both based on an artificial intelligence (AI) model. The non-destructive inspection system based on an AI model for determining a defect of an inspection object includes an image input unit configured to receive inspection signal image data of the inspection object, a first AI model unit configured to extract one or more feature portions for determining a defect of the inspection object from the inspection signal image data, and a second AI model unit configured to generate node relationship information by converting each of the feature portions into a node and learn based on the node relationship information to determine a defect in the inspection object.

Provided are a structure inspection method and a structure inspection system capable of efficiently inspecting structure and predicting deterioration with high accuracy. The structure inspection method includes: acquiring information on a location having internal damage within an inspection target region; and imaging the inspection target region with a visible light camera a plurality of times while shifting an imaging location, wherein a location except for the location having the internal damage is imaged with first pixel resolution and the location having internal damage is imaged with second pixel resolution higher than the first pixel resolution. Damage appearing on a surface of the structure is detected on the basis of a visible light image captured by the visible light camera. Information on the location having internal damage within the inspection target region is acquired by capturing an image that visualizes an internal state of the inspection target region.

An acoustic inspection device and an associated method for inspecting a component are provided. The acoustic inspection device is portable and includes an acoustic transmitter and receiver that may be placed on opposite sides of an inspection region on the surface of the component. The acoustic transmitter has an array of acoustic transducers for generating an acoustic wave that travels along a surface of the component and the acoustic receiver has an array of acoustic transducers for receiving that acoustic wave. A controller determines at least one surface characteristic of the component from the measured acoustic wave, such as its crystalline structure or grain size.

A phase-based approach can be used for one or more of acquisition, storage, or subsequent analysis, e.g., A-scan reconstruction or Total Focusing Method imaging, in support of acoustic inspection. For example, binarization or other quantization technique can be used to compress a data volume associated with time-series signal acquisition. A representation of phase information from the time-series signal can be generated, such as by processing the binarized or otherwise quantized time-series signal. Using the representation of the phase information, a phase summation technique can be used to perform one or more of A-scan reconstruction, such as for pulse-echo A-scan inspection, or a TFM imaging technique can be used, as illustrative examples. In such a phase summation approach, time-series representations of phase data can be summed, such as where each time-series can be delayed (or phase rotated) by an appropriate delay value and then aggregated.

Systems and techniques for measuring process characteristics including electrolyte distribution in a battery cell. A non-destructive method for analyzing a battery cell includes determining acoustic features at two or more locations of the battery cell, the acoustic features based on one or more of acoustic signals travelling through at least one or more portions of the battery cell during one or more points in time or responses to the acoustic signals obtained during one or more points in time, wherein the one or more points in time correspond to one or more stages of electrolyte distribution in the battery cell. One or more characteristics of the battery cell are determined based on the acoustic features at the two or more locations of the battery cell.

Systems and methods for tracking the location of a non-destructive inspection (NDI) scanner using images of a target object acquired by the NDI scanner. The system includes a frame, an NDI scanner supported by the frame, a system configured to enable motorized movement of the frame, and a computer system communicatively coupled to receive sensor data from the NDI scanner and track the location of the NDI scanner. The NDI scanner includes a two-dimensional (2-D) array of sensors. Subsurface depth sensor data is repeatedly (recurrently, continually) acquired by and output from the 2-D sensor array while at different locations on a surface of the target object. The resulting 2-D scan image sequence is fed into an image processing and feature point comparison module that is configured to track the location of the scanner relative to the target object using virtual features visible in the acquired scan images.

An ultrasonic inspection apparatus includes: an acquisition unit acquiring a signal indicating a fundamental wave and a second harmonic of an ultrasonic wave, which are obtained by the ultrasonic wave being scanned over an inspection object through a medium, at each scanning position; a calculation unit calculating a value obtained by dividing a second harmonic amplitude by a square of a fundamental wave amplitude, at each scanning position; and an output unit outputting information on a defect of the inspection object, based on the value obtained by dividing the second harmonic amplitude by the square of the fundamental wave amplitude.

An acoustic technique can be used for performing non-destructive testing. For example, a method for acoustic evaluation of a target can include generating respective acoustic transmission events via selected transmitting ones of a plurality of electroacoustic transducers, and in response to the respective acoustic transmission events, receiving respective acoustic echo signals using other receiving ones of the plurality of electroacoustic transducers, and coherently summing representations of the respective received acoustic echo signals to generate a pixel or voxel value corresponding to a specified spatial location of the target. Such summation can include weighting contributions from the respective representations to suppress contributions from acoustic propagation paths outside a specified angular range with respect to a surface on or within the target, such as to provide an acoustic path-filtered total focusing method (PF-TFM).