Novel Approaches for Structural Health Monitoring II

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 16802
Related Special Issue: Novel Approaches for Structural Health Monitoring

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Guest Editor
Head of the Laboratory of Bio-Inspired Nanomechanics “G.M. Pugno”, Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, 10129 Turin, Italy
Interests: structural dynamics, structural health monitoring; machine learning; nonlinear dynamics; signal processing; structural engineering; vibration analysis; biomechanics
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Dear Colleagues,

The thirty-plus years of progress in the field of structural health monitoring (SHM) have left a paramount impact on our everyday lives. Be it for the monitoring of fixed- and rotary-wing aircrafts, for the preservation of the cultural and architectural heritage, or for the predictive maintenance of long-span bridges or wind farms, SHM has shaped the framework of many engineering fields. Given the current state of quantitative and principled methodologies, it is now possible to rapidly and consistently evaluate the structural safety of industrial machines, modern concrete buildings, historical masonry complexes, etc., to test their capability to serve their intended purpose. However, old unsolved problems as well as new challenges exist. Unmodeled nonlinearities, ineffective sensor placement, and the effects of confounding influences due to operational and environmental variability still harm the effectiveness of state-of-the-art SHM apparatuses. Unprecedented conditions such as hypersonic flight, stricter safety requirements, and aging civil infrastructure pose new challenges for confrontation. Therefore, the aim of this Special Issue is to gather the main contributions of academics and practitioners in civil, aerospace, and mechanical engineering to provide a common ground for structural health monitoring. Studies concerning nondestructive testing, machine learning, signal processing, sensor fusion, vibration-based techniques, and related fields are all welcome, both numerical and experimental.

Prof. Dr. Cecilia Surace
Guest Editor

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Keywords

  • structural health monitoring
  • nondestructive testing
  • machine learning
  • vibration-based
  • signal processing

Published Papers (9 papers)

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Editorial

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3 pages, 174 KiB  
Editorial
Editorial for the Special Issue on Novel Approaches for Structural Health Monitoring II
by Cecilia Surace
Appl. Sci. 2023, 13(8), 5027; https://doi.org/10.3390/app13085027 - 17 Apr 2023
Cited by 1 | Viewed by 612
Abstract
The emphasis of this Special Issue is on showcasing the most recent advancements in the field of Structural Health Monitoring (SHM), accounting for all its applications in mechanical systems and civil structures or infrastructures [...] Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)

Research

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18 pages, 3679 KiB  
Article
Determining the Severity of Open and Closed Cracks Using the Strain Energy Loss and the Hill-Climbing Method
by Cristian Tufisi, Catalin V. Rusu, Nicoleta Gillich, Marius Vasile Pop, Codruta Oana Hamat, Christian Sacarea and Gilbert-Rainer Gillich
Appl. Sci. 2022, 12(14), 7231; https://doi.org/10.3390/app12147231 - 18 Jul 2022
Cited by 8 | Viewed by 1319
Abstract
Evaluating the integrity of structures is an important issue in engineering applications. The use of vibration-based techniques has become a common approach to assessing cracks, which are the most frequently occurring damage in structures. When involving an inverse method, it is necessary to [...] Read more.
Evaluating the integrity of structures is an important issue in engineering applications. The use of vibration-based techniques has become a common approach to assessing cracks, which are the most frequently occurring damage in structures. When involving an inverse method, it is necessary to know the influence of the position and the geometry of the crack on the modal parameter changes. The geometry of the crack, both in size and shape, defines the damage severity (DS). In this study, we present a method (DS-SHC) used for estimating the DS for closed and open transverse cracks in beam-like structures using the intact and damaged beam deflections under its weight and a Stochastic Hill Climbing (SHC) algorithm. After describing the procedure of applying DS-SHC, we calculate for a prismatic cantilever beam the severities for different crack types and depths. The results are tested by comparing the DS obtained with DS-SHC with those acquired from dynamic tests made using professional simulation software. We obtained a good fit between the severities determined in these two ways. Subsequently, we performed laboratory experiments and found that the severities obtained with the DS-SHC method can accurately predict the frequency changes due to the crack. Hence, these severities are a valuable tool for damage detection. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
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16 pages, 6508 KiB  
Article
Modal Identification of Structures with Interacting Diaphragms
by Rosario Ceravolo, Erica Lenticchia, Gaetano Miraglia, Valerio Oliva and Linda Scussolini
Appl. Sci. 2022, 12(8), 4030; https://doi.org/10.3390/app12084030 - 15 Apr 2022
Cited by 3 | Viewed by 1738
Abstract
System identification proves in general to be very efficient in the extraction of modal parameters of a structure under ambient vibrations. However, great difficulties can arise in the case of structures composed of many connected bodies, whose mutual interaction may lead to a [...] Read more.
System identification proves in general to be very efficient in the extraction of modal parameters of a structure under ambient vibrations. However, great difficulties can arise in the case of structures composed of many connected bodies, whose mutual interaction may lead to a multitude of coupled modes. In the present work, a methodology to approach the identification of interconnected diaphragmatic structures, exploiting a simplified analytical model, is proposed. Specifically, a parametric analysis has been carried out on a numerical basis on the simplified model, i.e., a multiple spring–mass model. The results were then exploited to aid the identification of a significant case study, represented by the Pavilion V, designed by Riccardo Morandi as a hypogeum hall of the Turin Exhibition Center. The structure is indeed composed of three blocks separated by expansion joints, whose characteristics are unknown. As the main result, light was shed on the contribution of the stiffness of the joints to the global dynamic behavior of structures composed of interacting diaphragms, and, in particular, on the effectiveness of the joints of Pavilion V. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
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21 pages, 17107 KiB  
Article
Interferometric Satellite Data in Structural Health Monitoring: An Application to the Effects of the Construction of a Subway Line in the Urban Area of Rome
by Giulia Delo, Marco Civera, Erica Lenticchia, Gaetano Miraglia, Cecilia Surace and Rosario Ceravolo
Appl. Sci. 2022, 12(3), 1658; https://doi.org/10.3390/app12031658 - 05 Feb 2022
Cited by 13 | Viewed by 1754
Abstract
In recent years, the use of interferometric satellite data for Structural Health Monitoring has experienced a strong development. The urban environment confirms its fragility to adverse natural events, made even more severe by climate change. Hence, the need to carry out continuous monitoring [...] Read more.
In recent years, the use of interferometric satellite data for Structural Health Monitoring has experienced a strong development. The urban environment confirms its fragility to adverse natural events, made even more severe by climate change. Hence, the need to carry out continuous monitoring of structures and artefacts appears increasingly urgent. Furthermore, satellite data could considerably increase the feasibility of traditional Structural Health Monitoring (SHM) approaches. This study aims to explore this remote sensing approach, focusing on the representation techniques that can be adopted to highlight their advantages and provide an interpretation of the results. In particular, the study analyzes records from the urban area of Rome (Italy), subject to the construction of a new subway line. These data are exploited to create a velocity map to highlight the possible subsidence phenomenon induced by excavations. Then, the paper focuses on single buildings or building complexes through the entropy-energy representation. Beyond the different limitations caused by the input data, a correlation is identified between the results of the two representation techniques. Accordingly, the effects of excavation on the urban area are demonstrated, and the methodologies are validated. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
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19 pages, 7006 KiB  
Article
An Application of Instantaneous Spectral Entropy for the Condition Monitoring of Wind Turbines
by Marco Civera and Cecilia Surace
Appl. Sci. 2022, 12(3), 1059; https://doi.org/10.3390/app12031059 - 20 Jan 2022
Cited by 20 | Viewed by 1647
Abstract
For economic and environmental reasons, the use of renewable energy sources is a key aspect of the ongoing transition to a sustainable industrialised society. Wind energy represents a major player among these natural, carbon-neutral sources. Nevertheless, wind turbines are often subject to mechanical [...] Read more.
For economic and environmental reasons, the use of renewable energy sources is a key aspect of the ongoing transition to a sustainable industrialised society. Wind energy represents a major player among these natural, carbon-neutral sources. Nevertheless, wind turbines are often subject to mechanical faults, especially due to ageing. To alleviate Operation and Maintenance costs, Vibration-Based Inspection and Condition Monitoring have been proposed in recent times. This research proposes Instantaneous Spectral Entropy and Continuous Wavelet Transform for anomaly detection and fault diagnosis, departing from gearbox vibration time histories. The approach is validated on experimental data recorded from a turbine suffering bearing failure and total gearbox replacement. From a computational point of view, the proposed algorithm was found to be efficient and therefore even potentially applicable for real-time monitoring. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
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19 pages, 6428 KiB  
Article
Response-Only Parametric Estimation of Structural Systems Using a Modified Stochastic Subspace Identification Technique
by Chang-Sheng Lin and Yi-Xiu Wu
Appl. Sci. 2021, 11(24), 11751; https://doi.org/10.3390/app112411751 - 10 Dec 2021
Cited by 5 | Viewed by 1889
Abstract
The present paper is a study of output-only modal estimation based on the stochastic subspace identification technique (SSI) to avoid the restrictions of well-controlled laboratory conditions when performing experimental modal analysis and aims to develop the appropriate algorithms for ambient modal estimation. The [...] Read more.
The present paper is a study of output-only modal estimation based on the stochastic subspace identification technique (SSI) to avoid the restrictions of well-controlled laboratory conditions when performing experimental modal analysis and aims to develop the appropriate algorithms for ambient modal estimation. The conventional SSI technique, including two types of covariance-driven and data-driven algorithms, is employed for parametric identification of a system subjected to stationary white excitation. By introducing the procedure of solving the system matrix in SSI-COV in conjunction with SSI-DATA, the SSI technique can be efficiently performed without using the original large-dimension data matrix, through the singular value decomposition of the improved projection matrix. In addition, the computational efficiency of the SSI technique is also improved by extracting two predictive-state matrixes with recursive relationship from the same original predictive-state matrix, and then omitting the step of reevaluating the predictive-state matrix at the next-time moment. Numerical simulations and experimental verification illustrate and confirm that the present method can accurately implement modal estimation from stationary response data only. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
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15 pages, 5177 KiB  
Article
Fast, Accurate, and Reliable Detection of Damage in Aircraft Composites by Advanced Synergistic Infrared Thermography and Phased Array Techniques
by Janardhan Padiyar M., Luca Zanotti Fragonara, Ivan Petrunin, Joao Raposo, Antonios Tsourdos, Iain Gray, Spyridoyla Farmaki, Dimitrios Exarchos, Theodore E. Matikas and Konstantinos G. Dassios
Appl. Sci. 2021, 11(6), 2778; https://doi.org/10.3390/app11062778 - 19 Mar 2021
Cited by 6 | Viewed by 2425
Abstract
This paper presents an advanced methodology for the detection of damage in aircraft composite materials based on the sensor fusion of two image-based non-destructive evaluation techniques. Both of the techniques, phased-array ultrasonics and infra-red thermography, are benchmarked on an aircraft-grade painted composite material [...] Read more.
This paper presents an advanced methodology for the detection of damage in aircraft composite materials based on the sensor fusion of two image-based non-destructive evaluation techniques. Both of the techniques, phased-array ultrasonics and infra-red thermography, are benchmarked on an aircraft-grade painted composite material skin panel with stringers. The sensors systems for carrying out the inspections have been developed and miniaturized for being integrated on a vortex-robotic platform inspector, in the framework of a larger research initiative, the Horizon-2020 ‘CompInnova’ project. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
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21 pages, 5463 KiB  
Article
A Model-Based SHM Strategy for Gears—Development of a Hybrid FEM-Analytical Approach to Investigate the Effects of Surface Fatigue on the Vibrational Spectra of a Back-to-Back Test Rig
by Franco Concli, Ludovico Pierri and Claudio Sbarufatti
Appl. Sci. 2021, 11(5), 2026; https://doi.org/10.3390/app11052026 - 25 Feb 2021
Cited by 9 | Viewed by 1568
Abstract
Transmissions are extensively employed in mechanical gearboxes when power conversion is required. Being able to provide specific maintenance is a crucial factor for both economics and reliability. However, although periodic transmission maintenance increases the systems’ longevity, it cannot prevent or predict sporadic major [...] Read more.
Transmissions are extensively employed in mechanical gearboxes when power conversion is required. Being able to provide specific maintenance is a crucial factor for both economics and reliability. However, although periodic transmission maintenance increases the systems’ longevity, it cannot prevent or predict sporadic major failures. In this context, structural health monitoring (SHM) represents a possible solution. Identifying variations of a specific measurable signal and correlating them with the type of damage or its location and severity may help assess the component condition and establish the need for maintenance operation. However, the collection of sufficient experimental examples for damage identification may be not convenient for big gearboxes, for which destructive experiments are too expensive, thus paving the way to model-based approaches, based on a numerical estimation of damage-related features. In this work, an SHM approach was developed based on signals from numerical simulations. To validate the approach with experimental measurements, a back-to-back test rig was used as a reference. Several types and severities of damages were simulated with an innovative hybrid analytical–numerical approach that allowed a significant reduction of the computational effort. The vibrational spectra that characterized the different damage conditions were processed through artificial neural networks (ANN) trained with numerical data and used to predict the presence, location, and severity of the damage. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
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Review

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25 pages, 744 KiB  
Review
Scour Detection with Monitoring Methods and Machine Learning Algorithms—A Critical Review
by Sinem Tola, Joaquim Tinoco, José C. Matos and Eugene Obrien
Appl. Sci. 2023, 13(3), 1661; https://doi.org/10.3390/app13031661 - 28 Jan 2023
Cited by 3 | Viewed by 2274
Abstract
Foundation scour is a widespread reason for the collapse of bridges worldwide. However, assessing bridges is a complex task, which requires a comprehensive understanding of the phenomenon. This literature review first presents recent scour detection techniques and approaches. Direct and indirect monitoring and [...] Read more.
Foundation scour is a widespread reason for the collapse of bridges worldwide. However, assessing bridges is a complex task, which requires a comprehensive understanding of the phenomenon. This literature review first presents recent scour detection techniques and approaches. Direct and indirect monitoring and machine learning algorithm-based studies are investigated in detail in the following sections. The approaches, models, characteristics of data, and other input properties are outlined. The outcomes are given with their advantages and limitations. Finally, assessments are provided at the synthesis of the research. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring II)
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