Ultrasonic Fluid Sound Speed Calibration for Tubular Defect Imaging
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Solution Overview
Problem
Existing ultrasonic inspection systems face inaccuracies in determining the speed of sound in fluids within tubular structures, leading to geometrical distortions and mischaracterization of structural flaws due to incorrect assumptions about fluid composition and varying sound speeds, which affects the quality of imaging and inspection results.
Innovation Solution
A method and system that iteratively transmits ultrasonic pulses in multiple directions, receives reflections, and computes a deviation metric to optimize the speed of sound by creating and analyzing images from different trial values, extracting geometric parameters, and selecting an optimal value that minimizes deviation, thereby improving image alignment and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If an estimated speed of sound is used in ultrasonic imaging, then the inspection process can proceed, but geometrical distortions and mischaracterization of structural flaws occur
Solution Approach 1:
The system uses geometric parameters extracted from ultrasonic images as feedback to iteratively optimize the speed of sound value. By computing a deviation metric among geometric parameters from multiple images and adjusting the speed of sound to minimize this deviation, the system automatically refines the speed of sound estimate without manual intervention, resolving the contradiction between maintaining productivity and improving measurement precision.
Solution Approach 2:
The speed of sound is treated as a dynamic parameter that can be adjusted and optimized during the inspection process. Instead of using a fixed estimated value, the system dynamically refines the speed of sound by iterating through multiple values and selecting the one that produces the most consistent geometric parameters across multiple ultrasonic images, thereby improving measurement precision while maintaining inspection efficiency.
2Measurement precision
If the speed of sound is determined iteratively by creating multiple images and computing deviation metrics, then measurement precision improves, but device complexity and processing time increase
Solution Approach 1:
The system performs self-calibration by automatically using its own ultrasonic images to determine the correct speed of sound. The geometric parameters extracted from the images serve as the basis for computing the deviation metric and optimizing the speed of sound value without requiring external reference materials or complex calibration equipment, thus improving measurement precision while limiting the increase in device complexity.
3Measurement precision
If multiple trial values for speed of sound are tested to optimize imaging accuracy, then measurement precision improves, but loss of time occurs during the iterative process
Solution Approach 1:
The system performs preliminary actions by acquiring multiple ultrasonic images with different transmit directions simultaneously or in rapid sequence before the optimization process begins. This preliminary data collection enables the subsequent iterative optimization to proceed more efficiently, as all necessary image data is already available for computing geometric parameters and deviation metrics, thereby reducing the overall time loss while maintaining measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of ultrasonic imaging by determining the correct speed of sound, reducing geometrical distortions and improving the characterization of tubular structures, ensuring accurate detection and characterization of defects.
Implementation Method 1
transmitting a plurality of ultrasonic pulses in a plurality of directions from an ultrasonic transducer array
Implementation Method 2
receiving a plurality of reflections from a target, wherein a respective reflection in the plurality of reflections corresponds to at least one respective pulse in the plurality of pulses
Data Source
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AI summary
A non-destructive testing device with an ultrasonic transducer array inspects objects carrying a fluid. Ultrasound reflections are stored in the device and processed to create images of the object. A processor estimates the speed of sound of the fluid by trying values for the sound speed and for each value: makes images from the reflections, calculate geometric parameters for the object from the images, and calculate a metric for how much the parameters vary. The estimated speed of sound is associate with the optimized metric.