Author: Yang, Xiongbin
Title: Breakthrough of ultrasonic imaging : from linear array to sparse network
Advisors: Su, Zhongqing (ME)
Degree: Ph.D.
Year: 2022
Subject: Ultrasonic imaging
Hong Kong Polytechnic University -- Dissertations
Department: Department of Mechanical Engineering
Pages: xxviii, 180 pages : color illustrations
Language: English
Abstract: Damage identification is somewhat like a detective task to catch the 'culprit' – defect or damage committed to materials and structures. Driven by the motivation to 'visualize' the 'culprit', diagnostic imaging using ultrasonic waves has been studied intensively and extensively over the past decades, to project identified defect or damage in an easily interpretable and intuitional quantitative image concerning the overall 'health' state of the structure under inspection. Nevertheless, prevailing diagnostic imaging approaches such as reverse time migration (RTM) and multiple signal classification (MUSIC), still show limitations when used in practice, particularly including (i) inferior imaging quality of the flaw: as a common problem of most imaging approaches, the image quality of lower flaw surfaces is usually inadequate, leading to possible deficiency in depicting full features of flaw; (ii) limited capability to detect flaw in specimens featuring irregular surfaces: prevailing imaging techniques often show proven effectiveness for a specimen with a flat surface that is either in parallel or oblique to the surface of the phased array, and it is a challenge to detect the specimens with non-planar surfaces; (iii) incomplete coverage of inspection region: prevailing MUSIC methods are largely bound up with the use of a linear array, leaving blind zones and failing to access the full planar area of an inspected sample; (iv) insufficient signal features: prevailing MUSIC algorithm, manipulated in the time domain, is applicable to monochromatic excitation only, ignoring signal features spanning a broad frequency band which also carry information of damage; and (v) lack of in-situ structural health monitoring (SHM) strategy: restricted by the use of bulky transducers, mobile manipulation, and computationally expensive imaging algorithms, it is a tough task to extend diagnostic imaging to real-time, continuous, in-situ SHM.
In recognition of the foregoing deficiencies in conventional ultrasonic imaging, a new ultrasonic imaging framework is developed in this PhD study.
First, an enhanced reverse time migration (ERTM) algorithm is developed, targeting superior imaging of full features of the embedded flaw in engineering material. On the basis of the multipath scattering analysis and Fermat's principle of the acoustic wave propagation, the algorithm establishes a new wavefield extrapolation model and presents a virtual phased array to reconstruct the lower surface of the embedded flaw. In conjunction with the flaw upper surface constructed by the actual phased array, the complete flaw features can be precisely delineated. The effectiveness of the ERTM approach is demonstrated by evaluating flaw with different geometric profiles in both simulation and experiment. Results show that, in comparison with the conventional RTM and TFM, the developed EMTR method can efficiently and accurately depict the full profiles of the flaw, providing a great alternative for characterizing flaw of complex shapes.
To extend the above imaging algorithm to an inspected specimen featuring an irregular top surface, an RTM-based multistep angular spectrum approach (ASA) imaging framework is developed. Central to the framework is a multistep ASA, via which the forward propagation wavefields of wave sources and backward propagation wavefields of the received wave signals are calculated. Upon applying a zero-lag cross-correlation imaging condition of RTM to the obtained forward and backward wavefields, the image of the specimen with an irregular surface can be reconstructed, in which hidden damage, if any and regardless of quantity, are visualized. The effectiveness and accuracy of the framework are examined using numerical simulation, followed with experiments, in which multiple side-drilled holes, at different locations in aluminum blocks with various irregular surfaces, are characterized. The validation affirms that the RTM-based multistep ASA shows an enhanced imaging resolution and contrast against conventional TFM.
An ameliorated multiple signal classification (Am-MUSIC) algorithm is proposed to remove the limitation of linear sensor array arrangement in conventional methods and to improve imaging resolution. The new method manipulates the signal representation matrix at each pixel using the excitation signal series, instead of the scattered signal series, which enables the use of a sparse sensor network with arbitrarily positioned transducers. By quantifying the orthogonal attributes between the signal subspace and noise subspace inherent in the signal representation matrix, a full spatial spectrum of the inspected sample can be generated, to visualize damage in the sample. Am-MUSIC is validated, in both simulation and experiment, by evaluating damage in plate-like waveguides with a sparse sensor network. Results verify that Am-MUSIC has full access to a sample, eliminating blind zones; and the amelioration expands conventional MUSIC from phased array-facilitated nondestructive evaluation to health monitoring using built-in sparse sensor networks.
Although Am-MUSIC algorithm expands conventional MUSIC algorithm from linear array-facilitated nondestructive evaluation to in-situ health monitoring with a sparse sensor network, a twofold issue still leaves to be improved: i) the signal representation equation is constructed at each pixel across the inspection region, incurring high computational cost; and ii) the algorithm is applicable to monochromatic excitation only, ignoring signal features scattered out of the excitation frequency band which also carry information on structural integrity. With this motivation, a multiple-damage-scattered wavefield model is developed, with which the signal representation equation is constructed in the frequency domain, avoiding computationally expensive pixel-based calculation – referred to as frequency-domain MUSIC (F-MUSIC). F-MUSIC quantifies the orthogonal attributes between the signal subspace and noise subspace inherent in the signal representation equation, and generates a full spatial spectrum of the inspected sample to visualize damage. Modeling in the frequency domain endows F-MUSIC with the capacity to fuse rich information scattered in a broad band and therefore enhance imaging precision. Both simulation and experiment are performed to validate F-MUSIC when used for imaging single and multiple sites of damage in a plate waveguide with a sparse sensor network. Results accentuate that the effectiveness of F-MUSIC is not limited by the quantity of damage and precision is not downgraded due to the use of a highly sparse sensor network – a challenging task for conventional MUSIC algorithm to fulfill.
Finally, an in-situ SHM diagnosis framework, from sensing to the presentation of diagnostic results, is established by integrating the all-printed nanocomposite sensor array (APNSA) and MUSIC diagnosis algorithm. The new breed of nanocomposite-based ultrasonic sensor – APNSA – is fabricated, in lieu of the conventional transducer array, featuring not only full integration with the inspected structure, but also high flexibility, ultralight weight, and broadband responsivity. Supported by the APNSA sensor and used in conjunction with the MUSIC algorithm, the continuous monitoring of damage can be implemented. The effectiveness of the diagnosis framework is validated experimentally by characterizing structural damage in the composite laminates, and results highlight its alluring application prospects for damage detection and health status perception in a real-time, in-situ manner.
In conclusion, enriched with fundamental theory development, dedicated modeling, innovative transducer fabrication, and intensive experimentation, a novel diagnosis imaging framework is developed in this study, to break through some critical bottlenecks of ultrasonic imaging, and cement a feasible way to meet diverse requirements in applications.
Rights: All rights reserved
Access: open access

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