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Nondestructive Sensing and Imaging in Ultrasound—Second Edition

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 20 July 2026 | Viewed by 2137

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Special Issue Editors

Dr. Miguel Ángel García Izquierdo

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Guest Editor

Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
Interests: NDE; ultrasound; ultrasonic tomographic; digital communication receivers; development of wireless monitoring systems; signal processing; machine learning
Special Issues, Collections and Topics in MDPI journals

Dr. Margarita Hernández

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CSIC—Instituto de Tecnologías Físicas y de la Información Leonardo Torres Quevedo (ITEFI), 28006 Madrid, Spain
Interests: characterization and inspection of materials; digital signal processing and ultrasonic methods of non-destructive testing; cementititious materials
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the previous Special Issue "Nondestructive Sensing and Imaging in Ultrasound" (https://www.mdpi.com/journal/sensors/special_issues/nsiu_sensors), we are pleased to announce the next in the series, entitled "Nondestructive Sensing and Imaging in Ultrasound—Second Edition".

Nondestructive evaluation via ultrasound is a method used in a wide range of industrial sectors, from automobiles and aeronautics to medicine, transport, and civil infrastructure, among others. Ultrasonic imaging is used extensively to establish the properties and quality of materials and infrastructures. The development of new methodologies, sensors, and instrumentation in NDE has to follow the trends being seen in the informatization, digitization, and networking of industrial production. The development of nondestructive sensors has led to the creation of an interdisciplinary method with multiple applications in different areas. New production techniques, such as 3D printing, will allow for the efficient and timely production of small numbers of unique parts customized for the needs of NDE.

This Special Issue aims to highlight advances in nondestructive sensing and imaging via ultrasound within different thematic areas to create a multidisciplinary viewpoint of this topic.

Dr. Miguel Ángel García Izquierdo
Dr. Margarita Hernández
Guest Editors

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Keywords

nondestructive sensing and imaging
ultrasound
NDE

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Nondestructive Sensing and Imaging in Ultrasound in Sensors (9 articles)

Published Papers (2 papers)

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Research

26 pages, 6942 KB

Open AccessArticle

Application of the Akaike Information Criterion to Ultrasonic Measurement of Liquid Volume in a Cylindrical Tank

by Krzysztof J. Opieliński and Tomasz Świetlik

Sensors 2025, 25(23), 7191; https://doi.org/10.3390/s25237191 - 25 Nov 2025

Viewed by 337

Abstract

The ultrasonic sensor method is the most significant and widely accepted technique for measuring liquid levels in tanks. Ultrasonic waves are particularly advantageous in the case of explosive, flammable, or aggressive liquids because of the possibility of introducing ultrasonic pulses through the tank wall safely. Often, the measurement of these liquids should be performed automatically using electronic devices to ensure that the tank remains sealed. In the case of ultrasound, measurements are made using the echo method, with a transmitting-receiving (transceiver) ultrasonic transducer that sends vibration pulses into the tank. The measured delay between the transmitted pulse and the pulse reflected from the liquid surface is proportional to the liquid level in the tank. The volume of liquid can be calculated on the basis of the dimensions of the tank. In this method, it is very important to accurately determine the delay by detecting the beginning of the reflected pulse, which determines the accuracy of the measurement of the level of the liquid and its quantity in the tank. To improve this accuracy, this paper proposes the use of the Akaike Information Criterion (AIC) used in statistics for model selection. As part of the research, ultrasonic test measurements were performed for a tank filled with water and extraction gasoline. This allowed a favorable comparison of the AIC method with the most commonly used threshold method and for determining the accuracy of liquid volume measurements in the tank using both methods in relation to the parameters of several selected ultrasonic sensors. The accuracy obtained using the AIC method was found to be better than that of the fixed-fractional amplitude threshold method. Furthermore, the AIC method is more versatile because it is less sensitive to interference and is capable of detecting the onset of a pulse regardless of its shape and frequency, even in noise. It is suitable for real-time embedded systems for liquid level measurement as well. Full article

(This article belongs to the Special Issue Nondestructive Sensing and Imaging in Ultrasound—Second Edition)

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26 pages, 12809 KB

Open AccessArticle

Coating Thickness Estimation Using a CNN-Enhanced Ultrasound Echo-Based Deconvolution

by Marina Perez-Diego, Upeksha Chathurani Thibbotuwa, Ainhoa Cortés and Andoni Irizar

Sensors 2025, 25(19), 6234; https://doi.org/10.3390/s25196234 - 8 Oct 2025

Viewed by 800

Abstract

Coating degradation monitoring is increasingly important in offshore industries, where protective layers ensure corrosion prevention and structural integrity. In this context, coating thickness estimation provides critical information. The ultrasound pulse-echo technique is widely used for non-destructive testing (NDT), but closely spaced acoustic interfaces often produce overlapping echoes, which complicates detection and accurate isolation of each layer’s thickness. In this study, analysis of the pulse-echo signal from a coated sample has shown that the front-coating reflection affects each main backwall echo differently; by comparing two consecutive backwall echoes, we can cancel the acquisition system’s impulse response and isolate the propagation path-related information between the echoes. This work introduces an ultrasound echo-based methodology for estimating coating thickness by first obtaining the impulse response of the test medium (reflectivity sequence) through a deconvolution model, developed using two consecutive backwall echoes. This is followed by an enhanced detection of coating layer thickness in the reflectivity function using a 1D convolutional neural network (1D-CNN) trained with synthetic signals obtained from finite-difference time-domain (FDTD) simulations with k-Wave MATLAB toolbox (v1.4.0). The proposed approach estimates the front-side coating thickness in steel samples coated on both sides, with coating layers ranging from

60 μ

m to

740 μ

m applied over 5 mm substrates and under varying coating and steel properties. The minimum detectable thickness corresponds to approximately

λ / 5

for an 8 MHz ultrasonic transducer. On synthetic signals, where the true coating thickness and speed of sound are known, the model achieves an accuracy of approximately

8 μ

m. These findings highlight the strong potential of the model for reliably monitoring relative thickness changes across a wide range of coatings in real samples. Full article