Concept Of Structural Health Monitoring Research Articles

Foundations and applicability of transfer learning for structural health monitoring of bridges

The number of bridges worldwide is extensive, making it financially and technically challenging for the authorities to install a structural health monitoring (SHM) system and collect large quantities of data for every bridge. Transfer learning has gained relevance in the last few years to extend the SHM concept for most bridges, while minimizing costs with monitoring systems and time with data measurement. It can be especially suitable for bridges structurally similar and replicated extensively, like overpasses integrated into highways. Therefore, this paper intends to lay down the foundations of transfer learning for SHM of bridges and to highlight the importance of the quality of knowledge transferred across different bridges for damage detection. Transfer Component Analysis, Joint Distribution Adaptation, and Maximum Independence Domain Adaptation methods are applied to data sets from different bridges, where classifiers have access to labeled training data from one bridge (source domain) and unlabeled monitoring test data from another bridge (target domain) that present similarities. The effectiveness of those methods is compared through the classification performance using real-world monitoring data sets collected from the Z-24 Bridge in Switzerland, and the PI-57 and PK 075+317 Bridges in France.

Mobile Structural Health Monitoring Based on Legged Robots

With the advancements in information, communication, and sensing technologies, structural health monitoring (SHM) has matured into a substantial pillar of infrastructure maintenance. In particular, wireless sensor networks have gradually been incorporated into SHM, leveraging new opportunities towards reduced installation efforts and enhanced flexibility and scalability, as compared to cable-based SHM systems. However, wireless sensor nodes are installed at fixed locations and need to be employed at high density to reliably monitor large infrastructure, which may cause high installation costs. Furthermore, the limited power autonomy of wireless sensor networks, installed at fixed locations for unattended long-term operation, still represents a significant constraint when deploying stationary wireless sensor nodes for SHM. To resolve the critical constraints stemming from costly high-density deployment and limited power autonomy, a mobile structural health monitoring concept based on legged robots is proposed in the study reported in this paper. The study explores the accuracy and cost-efficiency of deploying legged robots in dense measurement setups for wireless SHM of civil infrastructure, aiming to gain insights into the advantages of mobile wireless sensor nodes in general and of legged robots in particular, in terms of obtaining rich information on the structural condition. As is shown in this paper, the legged robots, as compared to stationary wireless sensor nodes, require a smaller number of nodes to be deployed in civil infrastructure to achieve rich sensor information, entailing more cost-efficient, yet accurate, SHM. In conclusion, this study represents a first step towards autonomous robotic fleets advancing structural health monitoring.

Acoustic emission-based structural health monitoring concept for corrosion of aluminum aircraft structures

In the aircraft industry, where highly optimized aluminum structures and most stringent safety requirements meet, corrosion of aluminum is an important issue to be controlled. To this end, several structural health monitoring (SHM) methods have already been demonstrated, including the acoustic emission (AE) method, which has shown potential for corrosion monitoring. Typically, immersion-like setups are used for demonstration. However, recent results at the authors’ research group also show the potential of the AE method to monitor atmospheric corrosion of aluminum aircraft structures. This contribution presents a SHM concept for the identification, i.e., detection, localization, quantification, and typification, of corrosion of thinwalled aluminum structures by AE. The proposed monitoring concept combines time and frequency domain features of corrosion triggered AE signals and AE source localization-based imaging with a-priori knowledge of structural configuration and loading by the utilization of machine learning methods to quantify and typify corrosion. Successful detection of atmospheric corrosion of aluminum by AE is briefly presented. Furthermore, the concept is theoretically discussed for quantification and typification of corrosion forms typical for atmospheric corrosion conditions.

Review of Structural Health Monitoring Techniques in Pipeline and Wind Turbine Industries

There has been enormous growth in the energy sector in the new millennium, and it has enhanced energy demand, creating an exponential rise in the capital investment in the energy industry in the last few years. Regular monitoring of the health of industrial equipment is necessary, and thus, the concept of structural health monitoring (SHM) comes into play. In this paper, the purpose is to highlight the importance of SHM systems and various techniques primarily used in pipelining industries. There have been several advancements in SHM systems over the years such as Point OFS (optical fiber sensor) for Corrosion, Distributed OFS for physical and chemical sensing, etc. However, these advanced SHM technologies are at their nascent stages of development, and thus, there are several challenges that exist in the industries. The techniques based on acoustic, UAVs (Unmanned Aerial Vehicles), etc. bring in various challenges, as it becomes daunting to monitor the deformations from both sides by employing only one technique. In order to determine the damages well in advance, it is necessary that the sensor is positioned inside the pipes and gives the operators enough time to carry out the troubleshooting. However, the mentioned technologies have been unable to indicate the errors, and thus, there is the requirement for a newer technology to be developed. The purpose of this review manuscript is to enlighten the readers about the importance of structural health monitoring in pipeline and wind turbine industries.

Embedding eddy current sensors into LPBF components for structural health monitoring

Laser powder bed fusion (LPBF) facilitates the integration of external elements like sensors into workpieces during manufacturing. These embedded components enable e.g. part monitoring, thus being a fundamental application of industry 4.0. This study assesses the feasibility of embedding eddy current (EC) sensors for non-destructive testing (NDT) into SLM components aiming at structural health monitoring (SHM). A reliable embedding process for EC sensors is developed, ensuring the survivability of the sensors for the LPBF process and its harsh conditions. The experiments conducted demonstrate the possibility to use the embedded EC sensor to observe and detect a controlled crack growth. The cracks are realized either with direct EDM cutting or on the course of a fatigue test of CT specimens. The data retrieved by the embedded EC sensors are proven to provide a direct information about the severity of a damage and its evolution over time for both approaches. Thus, supporting the validation of such an innovative and promising SHM concept.

Integrative approach for transducer positioning optimization for ultrasonic structural health monitoring for the detection of deterministic and probabilistic damage location

The concept of structural health monitoring has been introduced to ensure structural integrity during the design lifetime of a structure. The main objectives of structural health monitoring are to detect, locate, quantify, and predict any damage that occurs during this lifetime of the structure so that effective and efficient maintenance and repair procedures can be performed. The location of structural damage events can be discretized as deterministic and probabilistic. A deterministic location specifies that the damage occurs in high-stress regions or other regions that can be predicted by the structural design, such as the most probable location for a fatigue crack. A probabilistic damage event is one where the location of the damage is independent of structural design parameters, such as hail impact, bird strike, and impact from ground vehicles. A structural health monitoring system should be able to handle both these damage occurrences. In our previous work, we optimized the transducer placement in Lamb wave–based structural health monitoring for the detection of a fatigue crack that emerges from a rivet hole. In this article, we demonstrate a combination of that method with a different sensor placement optimization method to add the capability to detect probabilistic damage location. First, we considered the ultrasonic wave attenuation in the structure and based on this attenuation, we created a fitness function. Since this fitness function is difficult to solve due to its combinatorial nature, we compared three common metaheuristic stochastic strategies: global random search, greedy algorithm, and genetic algorithm, for solving this problem. The results of this analysis were then integrated with the previously described deterministic approach, making a global structural health monitoring sensor placement strategy that balances the need to detect both pre-determined and random damage location occurrences. The analytical result of the study presented is validated by experiment.

Prognosis and fail detection in a dynamic rotor using artificial immunological system

PurposeIn recent years, the mechanical industries began to apply many investments in research and technological development to obtain efficient methods to analyze the integrity of structures and prevent disasters and/or accidents, ensuring people’s lives and preventing economic losses. Any structure, whether mechanical or aeronautical, before being put into use undergoes a structural integrity assessment and testing. In this case, non-destructive evaluations are performed, aiming to estimate the degree of safety and reliability of the structure. For this, there are techniques traditionally used such as ultrasonic inspection, X-ray, acoustic emission tests, among other techniques. The traditional techniques may even have a good instrumental apparatus and be well formulated for structural integrity assessment; however, these techniques cannot meet growing industrial needs, even more so when structures are in motion. The purpose of this paper is to demonstrate artificial immune systems (AISs), ate and strengthen the emergence of an innovative technological tool, the biological immune systems and AISs, and these are presented as computing methods in the field of structural health monitoring (SHM).Design/methodology/approachThe concept of SHM is based on a fault detection mechanism used in industries, and in other applications, involving the observation of a structure or a mechanical system. This observation occurs through the dynamic response of periodic measurements, later related to the statistical analysis, determining the integrity of the system. This study aims to develop a methodology that identifies and classifies a signal in normal signals or in faults, using an algorithm based on artificial immunological systems, being the negative selection algorithm, and later, this algorithm classifies the failures in probabilities of failure and degree of fault severity. The results demonstrate that the proposed SHM is efficient and robust for prognosis and failure detection.FindingsThe present study aims to develop different fast access methodologies for the prognosis and detection of failures, classifying and judging the types of failures based on AISs. The authors declare that the present study was neither published in any other vehicle of scientific information nor is under consideration for publication in another scientific journal, and that this paper strictly followed the ethical procedures of research and publication as requested.Originality/valueThis study is original by the fact that conventional structural integrity monitoring methods need improvements, which intelligent computing techniques can satisfy. Intelligent techniques are tools inspired by natural and/or biological processes and belong to the field of computational intelligence. They present good results in problems of pattern recognition and diagnosis and thus can be adapted to solve problems of monitoring and identifying structural failures in mechanical and aeronautical engineering. Thus, the proposal of this study demonstrates and strengthens the emergence of an innovative technological tool, the biological immune system and the AIS, and these are presented as computation methods in the field of SHM in rotating systems – a topic not yet addressed in the literature.

Guided wave time-reversal imaging of macroscopic localized inhomogeneities in anisotropic composites

Estimation of damage position and extent in the inspected structure is among the emerging problems of active structural health monitoring (SHM) with elastic guided waves. Unlike conventional non-destructive testing (NDT) techniques, which assume continuous surface scanning, SHM systems operate only with data from a limited number of sensors. Nevertheless, in the case of isotropic (metal) plate-like structures, computational time-reversal techniques have proved to be effective for estimating in situ the location and size of wave sources and/or local scatterers within the SHM concept. With composite plates, the reconstruction procedure faces additional difficulties associated with the complexity of wave phenomena caused by their lamination and anisotropy. In this article, we present an extension of the time reversal technique for the case of composite laminate plate-like structures. This technique relies on the simulation of the reversed guided waves generated by reciprocal surface loads applied at a sparse set of measurement points of a real sensor network. The proposed implementation is based on the far-field asymptotics for guided waves generated in arbitrarily anisotropic laminate waveguides by a prescribed source, which have been derived from the path integral representations in terms of Green’s matrix for the structures considered. The performance of this approach has been experimentally tested on cross-ply carbon fiber-reinforced plastic plates showing reliable and adequate results for both active (piezoactuators) and passive (artificial defects) source characterization.

A Quantitative Approach for the Bone-implant Osseointegration Assessment Based on Ultrasonic Elastic Guided Waves

Quantitative and reliable monitoring of osseointegration will help further evaluate the integrity of the orthopaedic construct to promote novel prosthesis design and allow early mobilisation. Quantitative assessment of the degree or the lack of osseointegration is important for the clinical management with the introduction of prosthetic implants to amputees. Acousto-ultrasonic wave propagation has been used in structural health monitoring as well as human health monitoring but so far has not extended to osseointegrated implants or prostheses. This paper presents an ultrasonic guided wave approach to assess the osseointegration of a novel implant. This study explores the potential of integrating structural health monitoring concepts into a new osseointegrated implant. The aim is to demonstrate the extension of acousto-ultrasonic techniques, which have been widely reported for the structural health monitoring of engineering structures, to assess the state of osseointegration of a bone and implant. To illustrate this potential, this paper will report on the experimental findings which investigated the unification of an aluminium implant and bone-like geometry surrogate. The core of the test specimen is filled with silicone and wrapped with plasticine to simulate the highly damped cancellous bone and soft tissue, respectively. To simulate the osseointegration process, a 2-h adhesive epoxy is used to bond the surrogate implant and a bone-like structure. A series of piezoelectric elements are bonded onto the surrogate implant to serve as actuators and sensors. The actuating piezoelectric element on an extramedullary strut is excited with a 1 MHz pulse signal. The reception of the ultrasonic wave by the sensing elements located on the adjacent and furthest struts is used to assess the integration of this implant to the parent bone structure. The study shows an Osseointegration Index can be formulated by using engineering and acousto-ultrasonic methods to measure the unification of a bone and implant. This also highlights a potential quantitative evaluation technique regardless of bone-implant geometry and soft tissue damping.

Applying an Ultrasonic Lamb Wave Based Rechnique to Testing the Condition of V96ts3T12 Aluminum Alloy

Possibilities offered by an ultrasonic inspection technique that is based on using Lamb waves for monitoring the state of metal materials under static and cyclic loading have been studied. Dogbone V96ts3T12-aluminum-alloy specimens of the following two types have been used for research: initial material and a sample with a weld at the working zone center. The digital-image correlation method has been used as an additional source of information. Based on the tests, dependences of various informative parameters of acoustic vibrations on the applied load (for static tests) and running time (for cyclic tests) have been obtained. These dependences have been further supplemented with the results of calculation of deformation fields. The data gathered indicate sensitivity of the proposed ultrasonic inspection technique to various (elastic and plastic) deformation processes and allow one to monitor the growth of cracks under cyclic tests. Further development of the method assumes its examination from the viewpoint of embedded testing systems (the Structural Health Monitoring concept).

Hybrid motion sensing and experimental modal analysis using collocated smartphone camera and accelerometers

State-of-the-art multisensory technologies and heterogeneous sensor networks propose a wide range of response measurement opportunities for structural health monitoring (SHM). Measuring and fusing different physical quantities in terms of structural vibrations can provide alternative acquisition methods and improve the quality of the modal testing results. In this study, a recently introduced SHM concept, SHM with smartphones, is focused to utilize multisensory smartphone features for a hybridized structural vibration response measurement framework. Based on vibration testing of a small-scale multistory laboratory model, displacement and acceleration responses are monitored using two different smartphone sensors, an embedded camera and accelerometer, respectively. Double-integration or differentiation among different measurement types is performed to combine multisensory measurements on a comparative basis. In addition, distributed sensor signals from collocated devices are processed for modal identification, and performance of smartphone-based sensing platforms are tested under different configuration scenarios and heterogeneity levels. The results of these tests show a novel and successful implementation of a hybrid motion sensing platform through multiple sensor type and device integration. Despite the heterogeneity of motion data obtained from different smartphone devices and technologies, it is shown that multisensory response measurements can be blended for experimental modal analysis. Getting benefit from the accessibility of smartphone technology, similar smartphone-based dynamic testing methodologies can provide innovative SHM solutions with mobile, programmable, and cost-free interfaces.

Extending structural health monitoring concepts for bone healing assessment

AbstractA series of experimental investigations are performed to show the potential of integrating sensing elements into an external fixation for healing assessment of a fracture femur. This investigation is supported by finite element analyses that highlight the fundamental structural dynamics, which enable a stiffness‐based healing assessment methodology. A saw‐bone femur externally fixated with a Hoffman II will be subjected to an artificial fracture. The healing of the fractured femur is simulated with the curing of epoxy applied to the fractured region. The finite element analyses results will help determine the useful modes for assessing the state of healing of the fracture that can be attributed to the changes in the stiffness of the fixated structure. The findings will be tested against a set of experiments to show how the stiffness‐related quantities can be delineated from the dynamic response. The results reported will show distinct changes to the frequency response functions as the epoxy cures demonstrating the potential of integrating sensors onto an external fixation for healing and fracture union assessment.

Structural health monitoring: An orthopaedic perspective

Having unstable sacral fractures requires patients to be bedridden for a significant period of time for healing to take place without complications. This causes severe muscle atrophy, along with blood circulation problems in older patients. It is therefore highly beneficial to fast-track weight-bearing activities to reduce these complications by monitoring the recovery of the fracture. Past experimental work shows that dynamic response of a fixated synthetic (fourth-generation composite sawbone) pelvis is affected by the change in stiffness at the fracture location. The changes in this dynamic response can be observed by placing sensors on the pelvis and on the fixation. However, placing sensors on the pelvis is not practical. The aim of this article is to report on a set of computational investigation on the potential of placing sensors on the fixation to determine the stiffness restoration of the fractured region of the pelvis. This work will focus on the Denis I fracture, where the fracture is located in the sacrum. The ability to relate the dynamic response of a particular section of the fixation that is remote to the fracture location will have significant implication in the extending structural health monitoring concept to determine the state of healing of a fractured pelvis. A fourth-generation composite sawbone pelvis was used in the work reported in this article.

Magnetic Flux Leakage and Principal Component Analysis for metal loss approximation in a pipeline

Safety and reliability of hydrocarbon transportation pipelines represent a critical aspect for the Oil an Gas industry. Pipeline failures caused by corrosion, external agents, among others, can develop leaks or even rupture, which can negatively impact on population, natural environment, infrastructure and economy. It is imperative to have accurate inspection tools traveling through the pipeline to diagnose the integrity. In this way, over the last few years, different techniques under the concept of structural health monitoring (SHM) have continuously been in development.This work is based on a hybrid methodology that combines the Magnetic Flux Leakage (MFL) and Principal Components Analysis (PCA) approaches. The MFL technique induces a magnetic field in the pipeline's walls. The data are recorded by sensors measuring leakage magnetic field in segments with loss of metal, such as cracking, corrosion, among others. The data provide information of a pipeline with 15 years of operation approximately, which transports gas, has a diameter of 20 inches and a total length of 110 km (with several changes in the topography). On the other hand, PCA is a well-known technique that compresses the information and extracts the most relevant information facilitating the detection of damage in several structures. At this point, the goal of this work is to detect and localize critical loss of metal of a pipeline that are currently working.

Importance of in situ experimental testing in estimation of seismic stability of structures and implementation in structural health monitoring

The paper gives a common presentation of the most popular testing methods, procedures and sensors related to in situ full scale experimental testing of structures for definition of their dynamic characteristics. These structural properties are necessary for reliable estimation of seismic stability when structures are located in seismically active regions. The importance of such testing becomes even greater when sophisticated non-linear methods for analysis are used to check structural stability, as well as when an investigation requires verification by shaking table testing of representative scaled models. The implementation of the obtained results by in situ testing in structural health monitoring concept for a particular structure enables consideration of the dynamic properties and their changes over time as a useful indication in definition of the behavior of the structure and, if the structure is in a seismic active region, identification of damage occurence during earthquakes.

Analysis of wave propagation in periodic 3D waveguides

Structural Health Monitoring (SHM) is a growing research field in the realm of civil engineering. SHM concepts are implemented using integrated sensors and actuators to evaluate the state of a structure. Within this work, wave-based techniques are addressed. Dispersion effects for propagating waves in waveguides of different materials are analyzed for various different cross-sections. Since analytical theory is limited, a general approach based on the Waveguide Finite Element Method is applied. Numerical results are verified experimentally.

Automatic guided wave PPM communication system for potential SHM of flooding members in sub-sea oilrigs

An automatic guided wave pulse position modulation system, using steel tubes as the communication channel, for detecting flooding in the hollow sub-sea structures of newly built offshore oilrigs is presented. Underwater close visual inspections (CVI) are normally conducted during swim-round surveys in pre-selected areas or areas suspected of damage. An acceptable alternative to CVI is a non-destructive testing (NDT) technique called flood member detection (FMD). Usually, this NDT technique employs ultrasound or x-rays to detect the presence of seawater in the tubular structures, requiring divers or remote operating vehicles (ROVs). The field-proven FMD technique, integrated within the concept of structural health monitoring, offers an alternative to these traditional inspection methods. The system employs two smart sensors and modulators, which transmit 40 kHz guided wave pulses, and a digital signal processing demodulator, which performs automatic detection of guided wave energy packets. Experiments were performed in dry conditions, inside and outside the laboratory; in the former using a steel tube 1.5 m×0.27 m×2 mm, and in the latter using a tubular steel heliport structure approximately 15 m×15 m in area and the base deck of an oilrig under construction. Results confirm that, although there was significant dispersion of the transmitted pulses, the system successfully distinguished automatically guided wave encoded information that could potentially be used in sub-sea oilrigs.

Structural health monitoring of cylindrical structures using guided ultrasonic waves

The research field of structural health monitoring (SHM) in the realm of civil engineering has emerged rapidly. SHM concepts are based on integrated sensors and actuators to evaluate the structural state. Beside common structural response methods and other nondestructive testing techniques, wave-based ultrasonic techniques are widely used especially because of their flexibility. Monitoring cable structures such as overhead transmission lines or stay cables in suspension bridges is one objective of those wave-based methods. These structures are subject to aging, corrosion and other static and dynamic loads (e.g., wind, temperature). The cylindrical structures act as waveguides whereby monitoring of large distances with a single ultrasonic transducer is possible. However, the wave propagation is multimodal and dispersive, which complicates analysis of the wave motion and development of monitoring applications. This work addresses several aspects of the propagation of guided waves in cylinders, especially the analysis of reflection and transmission at discontinuities using finite element and boundary element methods.

Structural health monitoring of slab-column connections using FBG sensors

Health monitoring of reinforced concrete structures is a very important technique to maintain structural integrity. Early detection of damage can save lives and costly repairs. The information obtained from monitoring is generally used to plan and design maintenance activities, increase the safety, verify hypotheses, and reduce uncertainty. The current research is focused on the development and optimization of a structural health monitoring concept to detect damage initiation for slab-column connections. The research objective is to detect, localize and quantify flexural (service) cracks and shear cracks in slab-column connections. The experimental program is divided into three phases. The first phase is focused on detection of flexural cracks using embedded fibre Bragg grating (FBG) sensors. Detection of flexural cracks includes the initiation of first crack as well as the initial crack width. The second phase is focused on mapping of crack patterns using FBG sensors arrays. The last phase of the experimental work includes detection and localization of shear cracks as well as quantification of high compressive (bearing) zones using three-dimensional configuration of FBG sensor arrays. The current research presents the first phase of the experimental work. Test results revealed that embedded FBG sensors exhibited excellent performance and it was able to monitor the width and location of the first crack.

Fiber Optic Sensors in Structural Health Monitoring

Structural Health Monitoring (SHM) can be understood as the integration of sensing and intelligence to enable the structure loading and damage-provoking conditions to be recorded, analyzed, localized, and predicted in such a way that nondestructive testing becomes an integral part of them. In addition, SHM systems can include actuation devices to take proper reaction or correction actions. SHM sensing requirements are very well suited for the application of optical fiber sensors (OFS), in particular, to provide integrated, quasi-distributed or fully distributed technologies. In this tutorial, after a brief introduction of the basic SHM concepts, the main fiber optic techniques available for this application are reviewed, emphasizing the four most successful ones. Then, several examples of the use of OFS in real structures are also addressed, including those from the renewable energy, transportation, civil engineering and the oil and gas industry sectors. Finally, the most relevant current technical challenges and the key sector markets are identified. This paper provides a tutorial introduction, a comprehensive background on this subject and also a forecast of the future of OFS for SHM. In addition, some of the challenges to be faced in the near future are addressed.