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Non-destructive Testing and Health Monitoring of Structures and Systems

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

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 26632

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Prof. Dr. Andrzej Katunin

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Guest Editor

Department of Fundamentals of Machinery Design, Silesian University of Technology, 44-100 Gliwice, Poland
Interests: structural degradation; structural damage identification; non-destructive testing; structural health monitoring; fatigue and fracture mechanics; signal and image processing
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Special Issue Information

Dear Colleagues,

Non-destructive testing and health monitoring started to be a key action in the operation and maintenance of structures and systems in numerous industrial branches, such as aviation and aerospace, the automotive industry, nuclear power systems, and many others. This implied a continuous development of methods and techniques used for the testing and monitoring of structures and systems, which are focused primarily on improvement of sensitivity of these methods to various types of faults and damage by application novel sensing technologies, new methodologies, as well as by development of new post-processing algorithms.

This Special Issue is focused on recent attempts in the development and application of various sensing techniques and methodologies for a condition assessment of structures and systems, including a broad range of non-destructive testing and health monitoring techniques. The submissions can describe interdisciplinary studies from the borderline of sensing techniques for non-destructive testing and health monitoring, improvement of sensors used for structural and systems evaluation, post-processing algorithms with the objective of increasing damage and faults detectability, as well as practical case studies related to the aforementioned thematic areas and similar ones. High-quality articles containing original research results and review articles are welcomed.

Sensing technologies for damage assessment;
Damage detection, identification, and quantification;
Damage diagnosis and prognosis;
Non-destructive testing;
Structural health monitoring;
Health monitoring of industrial systems;
Artificial intelligence techniques for health monitoring;
Post-processing of data for faults and damage assessment.

Prof. Dr. Andrzej Katunin
Guest Editor

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Published Papers (11 papers)

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Research

19 pages, 5465 KiB

Open AccessArticle

Static Loads Influence on Modal Properties of the Composite Cylindrical Shells with Integrated Sensor Network

by Aleksey Mironov, Andrejs Kovalovs, Andris Chate and Aleksejs Safonovs

Sensors 2023, 23(6), 3327; https://doi.org/10.3390/s23063327 - 22 Mar 2023

Cited by 3 | Viewed by 1415

Abstract

This paper presents the results of experimental and numerical studies of the dynamic parameters of composite cylindrical shells loaded under axial tension. Five composite structures were manufactured and loaded up to 4817 N. The static load test was carried out by hanging the load to the lower part of a cylinder. The natural frequencies and mode shapes were measured during testing using a network of 48 piezoelectric sensors that measure the strains of composite shells. The primary modal estimates were calculated with ARTeMIS Modal 7 software using test data. The methods of modal passport, including modal enhancement, were used to improve the accuracy of the primary estimates and reduce the influence of random factors. To estimate the effect of a static load on the modal properties of a composite structure, a numerical calculation and a comparative analysis of experimental and numerical data was carried out. The results of the numerical study confirmed that natural frequency increases with increasing tensile load. The data obtained from experimental results were not fully consistent with the results of numerical analysis, but showed a consistent pattern, repeating for all samples. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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33 pages, 20848 KiB

Open AccessArticle

Monitoring of Damage in Composite Structures Using an Optimized Sensor Network: A Data-Driven Experimental Approach

by Sandris Ručevskis, Tomasz Rogala and Andrzej Katunin

Sensors 2023, 23(4), 2290; https://doi.org/10.3390/s23042290 - 18 Feb 2023

Cited by 2 | Viewed by 1849

Abstract

Due to the complexity of the fracture mechanisms in composites, monitoring damage using a vibration-based structural response remains a challenging task. This is also complex when considering the physical implementation of a health monitoring system with its numerous uncertainties and constraints, including the presence of measurement noise, changes in boundary and environmental conditions of a tested object, etc. Finally, to balance such a system in terms of efficiency and cost, the sensor network needs to be optimized. The main aim of this study is to develop a cost- and performance-effective data-driven approach to monitor damage in composite structures and validate this approach through tests performed on a physically implemented structural health monitoring (SHM) system. In this study, we combined the mentioned research problems to develop and implement an SHM system to monitor delamination in composite plates using data combined from finite element models and laboratory experiments to ensure robustness to measurement noise with a simultaneous lack of necessity to perform multiple physical experiments. The developed approach allows the implementation of a cost-effective SHM system with validated predictive performance. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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20 pages, 1744 KiB

Open AccessArticle

Residual Creep Life Assessment of High-Temperature Components in Power Industry

by Ivanna Pivdiablyk, Zhu Di Goh, Liam Kok Chye, Robert Shandro and Fabien Lefebvre

Sensors 2023, 23(4), 2163; https://doi.org/10.3390/s23042163 - 14 Feb 2023

Cited by 5 | Viewed by 2769

Abstract

A large percentage of power, petroleum, and chemical plants over the world were in operation for a long duration with the corresponding critical components being used beyond the design life of 30 to 40 years. It is generally more cost-effective to refurbish or modernize the degraded equipment or components, rather than to construct a new plant. Therefore, a reliable plant life extension assessment that can evaluate the critical components is needed. The key element in plant life extension is the residual life assessment technology. However, at present, there is still no general consensus among the industry players on the approach to adopt when performing residual life assessment for such a critical damage mechanism as creep. In this article, a three-level residual life assessment methodology is proposed as a general approach for high-temperature components prone to creep. A detailed validation of the selected guidelines and calculation models is also described. Eventually, an application of the three-level methodology to a real industrial case study is presented. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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23 pages, 10443 KiB

Open AccessArticle

Dynamic Range Compression of Thermograms for Assessment of Welded Joint Face Quality

by Wojciech Jamrozik, Jacek Górka and Gilmar Ferreira Batalha

Sensors 2023, 23(4), 1995; https://doi.org/10.3390/s23041995 - 10 Feb 2023

Cited by 1 | Viewed by 1328

Abstract

Temperature is one of the essential parameters in fusion welding. Typically, an uncooled infrared detector acquires 14-bit data, while a human observer can only distinguish about 128 levels of grey. For IR HDR (high dynamic range) images, one of the main goals of dynamic range compression is to enhance the visibility of low-contrast details. It is an important issue because the temperature span in the cross-section of a welded joint and its length are large. In the paper, global approaches for range compression are investigated, such as algorithms that include pixel transformations, histogram equalization (‘he’) and some of its variants. Additionally, multiscale decomposition methods were investigated. All results are obtained for the sequences of thermograms acquired during the TIG welding of plates made of Inconel 625 superalloy. The process was observed with an uncooled IR camera. The application of compression methods led to the generation of low-dynamic-range (LDR) IR images. The algorithms allowed the preservation of global contrast and enhancement of the visibility of hot details in dark and low-contrast areas. All IR representations of the welded samples were evaluated, and relationships between apparent temperature counted in the pixel-level value and weld-face geometry were revealed. Methods based on wavelet transforms were found to be the most suitable for this type of image; nevertheless, a relatively large local noise was generated. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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12 pages, 3849 KiB

Open AccessArticle

Simultaneous Measurement of Strain and Temperature Distributions Using Optical Fibers with Different GeO₂ and B₂O₃ Doping

by Shinsaku Hisada, Utanori Kodakamine, Daichi Wada, Hideaki Murayama and Hirotaka Igawa

Sensors 2023, 23(3), 1156; https://doi.org/10.3390/s23031156 - 19 Jan 2023

Cited by 3 | Viewed by 1591

Abstract

Compensating for the effects of temperature is a crucial issue in structural health monitoring when using optical fiber sensors. This study focused on the change in sensitivity due to differences in GeO

_{2}

and B

_{2}

_{3}

doping and then verified the [...] Read more.

_{2}

and B

_{2}

_{3}

doping and then verified the accuracy when measuring the strain and temperature distributions simultaneously. Four types of optical fiber sensors were utilized to measure the strain and temperature in four-point bending tests, and the best combination of the sensors resulted in strain and temperature errors of 28.4

μ ϵ

and 1.52 °C, respectively. Based on the results obtained from the four-point bending tests, we discussed the error factors via an error propagation analysis. The results of the error propagation analysis agreed well with the experimental results, thus indicating the effectiveness of the analysis as a method for verifying accuracy and error factors. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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19 pages, 8441 KiB

Open AccessArticle

Finite Element Model Updating of RC Bridge Structure with Static Load Testing: A Case Study of Vietnamese ThiThac Bridge in Coastal and Marine Environment

by Duc Cong Nguyen, Marek Salamak, Andrzej Katunin and Michael Gerges

Sensors 2022, 22(22), 8884; https://doi.org/10.3390/s22228884 - 17 Nov 2022

Cited by 8 | Viewed by 3353

Abstract

Diagnostic load testing refers to the use of the measured historical responses of the structure in the field data to better understand its dynamic and static structural behaviours. It is important and necessary to predict the health state, load capacity, and aging of the structure by updating the finite element (FE) model, which can give useful information to aid the design of retrofits and the maintenance of the existing bridge in the future. The paper presents an update of the full-scale FE model for the reinforced concrete (RC) bridge structure over the seawater river based on the experimental strains under the static load testing in which the representative FE model of the actual structure is determined from the optimisation procedures. The optimisation variables are applied, including the cross-sectional properties and concrete material calibrated through the genetic algorithm (GA) optimisation in the MATLAB software, which interfaces with the FE modelling in the scripting of the SOFISTIK TEDDY software automatically. The bending moments at the mid-span of the RC girders are determined in the FE modelling to compute stresses, which are compared with the measured stresses through optimisation scenarios with a percentage error of the objective function less than 10%. The measured data of concrete strains are recorded from reusable strain transducers installed on the mid-span girders for every bridge span, which are used to calibrate the bridge model in static load testing. The novelty of the solution is to implement innovative techniques using field data as an improved approach for calibrating automatically the analytical FE model parameters of all RC spans of the bridge until its static behaviours are very similar to those of the actual bridge. The final updated FE modelling is used to apply truck load configurations according to bridge design standards such as the AASHTO specifications, which can predict the load limits of the existing bridge structure more accurately and reliably. These proposed approaches can be applied to large bridges as well as complex structures with supporting FE analysis software and data processing software. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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13 pages, 3035 KiB

Open AccessArticle

Comprehensive Indicators for Evaluating and Seeking Elasto-Magnetic Parameters for High-Performance Cable Force Monitoring

by Shuangsheng Yan, Yujue Wang, Peng Li, Zhichao Gao, Bin Wu and Xiucheng Liu

Sensors 2022, 22(20), 7776; https://doi.org/10.3390/s22207776 - 13 Oct 2022

Cited by 3 | Viewed by 1769

Abstract

The elasto-magnetic method is a promising pathway for cable force monitoring in cable-stayed bridges. Under the action of an externally applied pulsed magnetic field, both the variation in the main flux recorded by the induction coil and the localized surface magnetic field measured by the packaged magnetic sensor are typical signals for observing the elasto-magnetic effect in tensioned cables. However, the performances of the parameters extracted from the two types of elasto-magnetic signals are never strictly compared in the experiment. Meanwhile, comprehensive indicators for evaluating the ability of elasto-magnetic parameters on cable force characterization are seldom discussed. As a result, it is difficult to compare the performances of elasto-magnetic devices developed by different teams, and the pathway of seeking new parameters for cable force monitoring is obstructed. In this study, elasto-magnetic calibration experiments were performed on a cable of seven-wire steel strands to simultaneously measure the variation in the main flux and the localized surface magnetic field. Comprehensive indicators considering sensitivity, hysteresis error, and cable force resolution are proposed to examine the performances of classic elasto-magnetic parameters and new candidate ones. Through comparative study, two new parameters demonstrated outstanding ability for cable force measurement, and they are the minimum amplitude of the induced voltage and the area under the curve between two points of 3 dB height of the voltage measured by a Hall sensor. The latter is recommended for high-performance cable force monitoring from the perspective of simplicity in sensor configuration. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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21 pages, 9191 KiB

Open AccessArticle

Monitoring of Hidden Corrosion Growth in Aircraft Structures Based on D-Sight Inspections and Image Processing

by Andrzej Katunin, Marko Nagode, Simon Oman, Adam Cholewa and Krzysztof Dragan

Sensors 2022, 22(19), 7616; https://doi.org/10.3390/s22197616 - 8 Oct 2022

Cited by 4 | Viewed by 1862

Abstract

Hidden corrosion in aircraft structures, not detected on time, can have a significant influence on aircraft structural integrity and lead to catastrophic consequences. According to the widely accepted damage tolerance philosophy, non-destructive inspections are performed to assess structural safety and reliability. One of the inspection techniques used for such an inspection is the optical D-Sight technique. Since D-Sight is used primarily as a qualitative method, it is difficult to assess the evolution of a structural condition simply by comparing the inspection results. In the following study, the method to monitor hidden corrosion growth is proposed on the basis of historical data from D-Sight inspections. The method is based on geometric transforms and segmentation techniques to remove the influence of measurement conditions, such as the angle of observation or illumination, and to compare corroded regions for a sequence of D-Sight images acquired during historical inspections. The analysis of the proposed method was performed on the sequences of D-Sight images acquired from inspections of Polish military aircraft in the period from 2002 to 2017. The proposed method represents an effective tool for monitoring hidden corrosion growth in metallic aircraft structures based on a sequence of D-Sight images. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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28 pages, 13286 KiB

Open AccessArticle

Vibration-Based Damage Detection Using Finite Element Modeling and the Metaheuristic Particle Swarm Optimization Algorithm

by Ilias Zacharakis and Dimitrios Giagopoulos

Sensors 2022, 22(14), 5079; https://doi.org/10.3390/s22145079 - 6 Jul 2022

Cited by 12 | Viewed by 2103

Abstract

The continuous development of new materials and larger and/or more complex structures drives the need for the development of more robust, accurate, and sensitive Structural Health Monitoring (SHM) techniques. In the present work, a novel vibration-based damage-detection method that contributes into the SHM field is presented using Metaheuristic algorithms coupled with optimal Finite Element Models that can effectively localize damage. The proposed damage-detection framework can be applied in any kind of detailed structural FE model, while requiring only the output information of the dynamic response of the structure. It can effectively localize damage in a structure by highlighting not only the affected part of the structure but also the specific damaged area inside the part. First, the optimal FE model of the healthy structure is developed using appropriate FE model updating techniques and experimental vibration measurements, simulating the undamaged condition. Next, the main goal of the proposed method is to create a damaged FE model that approximates the dynamic response of the damaged structure. To achieve this, a parametric area is inserted into the FE model, changing stiffness and mass to simulate the effect of the physical damage. This area is controlled by the metaheuristic optimization algorithm, which is embedded in the proposed damage-detection framework. On this specific implementation of the framework, the Particle Swarm Optimization (PSO) algorithm is selected which has been used for a wide variety of optimization problems in the past. On the PSO’s search space, two parameters control the stiffness and mass of the damaged area while additional location parameters control the exact position of the damaged area through the FE model. For effective damage localization, the Transmittance Functions from acceleration measurements are used which have been shown to be sensitive to structural damage while requiring output-only information. Finally, with proper selection of the objective function, the error that arises from modeling a physical damage with a linear damaged FE model can be minimized, thus creating a more accurate prediction for the damaged location. The effectiveness of the proposed SHM method is demonstrated via two illustrative examples: a simulated small-scale model of a laboratory-tested vehicle-like structure and a real experimental CFRP composite beam structure. In order to check the robustness of the proposed method, two small damage scenarios are examined for each validation model and combined with random excitations. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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13 pages, 1990 KiB

Open AccessArticle

Automatic Detection of Cracks on Concrete Surfaces in the Presence of Shadows

by Paulius Palevičius, Mayur Pal, Mantas Landauskas, Ugnė Orinaitė, Inga Timofejeva and Minvydas Ragulskis

Sensors 2022, 22(10), 3662; https://doi.org/10.3390/s22103662 - 11 May 2022

Cited by 28 | Viewed by 3170

Abstract

Deep learning-based methods, especially convolutional neural networks, have been developed to automatically process the images of concrete surfaces for crack identification tasks. Although deep learning-based methods claim very high accuracy, they often ignore the complexity of the image collection process. Real-world images are often impacted by complex illumination conditions, shadows, the randomness of crack shapes and sizes, blemishes, and concrete spall. Published literature and available shadow databases are oriented towards images taken in laboratory conditions. In this paper, we explore the complexity of image classification for concrete crack detection in the presence of demanding illumination conditions. Challenges associated with the application of deep learning-based methods for detecting concrete cracks in the presence of shadows are elaborated on in this paper. Novel shadow augmentation techniques are developed to increase the accuracy of automatic detection of concrete cracks. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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19 pages, 5904 KiB

Open AccessArticle

Change in Electrical Resistance of SMA (NiTi) Wires during Cyclic Stretching

by Sebastian Sławski, Marek Kciuk and Wojciech Klein

Sensors 2022, 22(9), 3584; https://doi.org/10.3390/s22093584 - 8 May 2022

Cited by 9 | Viewed by 3148

Abstract

In this article, the use of Nickel Titanium (NiTi) alloy as a sensor is examined. A cyclic stretching test, that has various elongations (0.5 and 1%), is administered to NiTi wires with various diameters and lengths. It is assumed that the elongation enables an observation of the change in electrical resistance of the NiTi wires, due to martensite reorientation. During the test, the stretching force, the displacement, and the electrical resistance of the NiTi wires are measured. Following the test, the resistance of all the tested samples differed compared to the starting position. Conducted research indicates that NiTi wires are very sensitive to resistance change when they are deformed. A large difference in NiTi electrical resistance was visible in all samples during the first stretching cycle. For longer wires, with a smaller diameter, resistance change was visible during almost all of the stretching cycles. However, the observed changes were very small. Based on the obtained results, it can be justifiably stated that NiTi wires could be used to build deformation sensors, which operate both online and offline. Moreover, NiTi wires with a small diameter could be used to create cyclic loading sensors. Such sensors can be used in self-sensing applications or in structural health monitoring. Full article

(This article belongs to the Special Issue Non-destructive Testing and Health Monitoring of Structures and Systems)

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