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Computational Time-Reversal Imaging Method For Ultrasonic Nondestructive Evaluation
Source: Science Trends
To reliably access the integrity of a material or the structures made of it, we need to know the geometry and size of flaws buried potentially inside the material. When ultrasonic waves are used for a nondestructive evaluation (NDE) of materials, therefore, an important goal is to reconstruct the shape of flaws from a set of ultrasonic echo signals.

To achieve this goal, a variety of ultrasonic imaging methods have been studied over the years. The synthetic aperture focusing technique (SAFT) is one of them. SAFT was originally developed for radar imaging applications and known also as a synthetic aperture radar (SAR). Like ultrasonic medical diagnoses, imaging is becoming a common practice in the field of industrial NDE as array ultrasonic transducers having tens of hundreds of transmitter/receiver elements and personal computers with a greater computational capability become more affordable. The former is indispensable for efficient and accurate ultrasonic echo measurements, while the latter is for the implementation of computationally intensive imaging algorithms.

SAFT – basic idea and algorithm


To understand how SAFT works, it suffices to look at the way it samples and converts ultrasonic echo amplitudes to an image intensity (pixel value) at a selected pixel. To this end, suppose that we’re inspecting a material transmitting ultrasonic beam from multiple locations. Suppose also that ultrasonic echoes coming back from the material are measured as a time-varying signal at multiple observation points. With the set of measured ultrasonic signals, the SAFT imaging goes as follows. For every ultrasonic signal, SAFT evaluates an ultrasonic time-of-flight (TOF) supposing that an ideal point scatterer is placed at the pixel point of interest. The echo amplitude at the estimated TOF is then picked up from the ultrasonic RF signal and assign it to the pixel as a partial image intensity. To obtain a complete image intensity, the echo amplitude associated with the pixel are collected from all available signals and are summed. In taking the sum, the amplitudes are often weighed so as to normalize the signals considering such factors as transmitter/receiver directivity and wave attenuation. By repeating the above operations for each pixel, SAFT synthesizes an image over a predefined grid of pixels.

Read the full article at Science Trends.

Sensor Networks Inc.