Design Of Structural Health Monitoring System Research Articles

Numerical Simulations in Ultrasonic Guided Wave Analysis for the Design of SHM Systems—Benchmark Study Based on the Open Guided Waves Online Platform Dataset

Structural health monitoring (SHM) strategies based on ultrasonic guided waves are very promising regarding thin-walled lightweight structures. To study the performance of such systems, validated numerical analysis tools have to be used. For that procedure, a benchmark between two numerical methods will be presented. The first promising approach is the elastodynamic finite integration technique (EFIT). Miscellaneous research shows that its capability of capturing wave characteristics and interactions is advanced in various media and structures, including thin-walled composites. The second approach employs conventional shell-type finite elements following the Reissner–Mindlin theory for modelling layered composite structures. The advantage of using such finite element methods (FEM) is their high availability in general purpose simulation tools. As a reference model, the measurement data coming from the Open Guided Waves Project (OGW) was taken into account. The OGW dataset provides the experimental data of ultrasonic guided wave propagation in carbon fiber composite plates with an additional omega stringer. By using this contribution, this experiment was reproduced by simulation. The paper presents the results of a validation and motivates further research, such as in research related to the probability of detection analysis and numerical performance.

Structural health monitoring system design for historical heritage building

Abstract Structural Health Monitoring (SHM) systems play an important role in the defence of historical heritage. In fact, it is necessary to monitor and analyse the information that highlight the state of health of the structure. Unfortunately, in the realization of the monitoring system it is necessary to place several sensor nodes in place where it is not simple or possible the connection to the mains power supply. Moreover, it is necessary the fast detection of critical situation in which the state of conservation of an historical building can deteriorate. For these reasons in the paper is proposed the design of a low power consumption long range communication system. This design is proposed as an innovation of previous work, and the use of machine learning an algorithm to analyse the data.

A Development Strategy for Structural Health Monitoring Applications

Abstract Permanently installed structural health monitoring (SHM) systems are now a viable alternative to traditional periodic inspection (nondestructive testing (NDT)). However, their industrial use is limited, and this article reviews the steps required in developing practical SHM systems. The transducers used in SHM are fixed in location, whereas in NDT, they are generally scanned. The aim is to reach similar performance with high temporal frequency, low spatial frequency SHM data to that achievable with conventional high spatial frequency, and low temporal frequency NDT inspections. It is shown that this can be done via change tracking algorithms such as the generalized likelihood ratio (GLR), but this depends on the input data being normally distributed, which can only be achieved if signal changes due to variations in the operating conditions are satisfactorily compensated; there has been much recent progress on this topic, and this is reviewed. Since SHM systems can generate large volumes of data, it is essential to convert the data to actionable information, and this step must be addressed in the SHM system design. It is also essential to validate the performance of installed SHM systems, and a methodology analogous to the model-assisted probability of detection (POD) (MAPOD) scheme used in NDT has been proposed. This uses measurements obtained from the SHM system installed on a typical undamaged structure to capture signal changes due to environmental and other effects and to superpose the signal due to damage growth obtained from finite element predictions. There is a substantial research agenda to support the wider adoption of SHM, and this is discussed in this study.

Ultrasonic data transmission across metal structures affected by environmental conditions

Variable environmental conditions present a major hurdle for Structural Health Monitoring (SHM) systems which involve the signal processing of Ultrasonic Guided Waves (UGW). Two important cases of variable conditions are investigated in this article: (i) The effect of changing temperature and (ii) the impact of water surrounding a technical structure. In two complementary case studies, an aluminum plate and a steel pipe with flange are examined. The article concentrates on the emerging task of UGW-based data transmission across these solid waveguides. In particular, permanently attached piezoelectric transceivers are deployed for digital communication using amplitude modulation, namely on-off keying (OOK). The laboratory experiments are accompanied by a mathematical treatment as well as numerical simulations. Successful data transmission is established and analyzed. Based on the provided analysis, distinct strategies are identified for reliable communication in the presence of changing environmental conditions. The results are of eminent importance in the framework of SHM where, apart from monitoring, the supplementary capability of the transceivers to exchange health-related information across the waveguide itself, represents an innovative feature for the design of future intelligent SHM systems.

Emerging Trends in Optimal Structural Health Monitoring System Design: From Sensor Placement to System Evaluation

This paper presents a review of advances in the field of Sensor Placement Optimisation (SPO) strategies for Structural Health Monitoring (SHM). This task has received a great deal of attention in the research literature, from initial foundations in the control engineering literature to adoption in a modal or system identification context in the structural dynamics community. Recent years have seen an increasing focus on methods that are specific to damage identification, with the maximisation of correct classification outcomes being prioritised. The objectives of this article are to present the SPO for SHM problem, to provide an overview of the current state of the art in this area, and to identify promising emergent trends within the literature. The key conclusions drawn are that there remains a great deal of scope for research in a number of key areas, including the development of methods that promote robustness to modelling uncertainty, benign effects within measured data, and failures within the sensor network. There also remains a paucity of studies that demonstrate practical, experimental evaluation of developed SHM system designs. Finally, it is argued that the pursuit of novel or highly efficient optimisation methods may be considered to be of secondary importance in an SPO context, given that the optimisation effort is expended at the design stage.

Structural health monitoring of towers and blades for floating offshore wind turbines using operational modal analysis and modal properties with numerical-sensor signals

In the present study, a structural health monitoring (SHM) method for floating offshore wind turbines (FOWTs) is suggested and tested using operational modal analysis (OMA) with numerical-sensor signals. The numerical accelerometer signals along the tower and blade of FOWT in dynamic wind field are used for the OMA. The numerical-sensor signals are simulated using a time-domain turbine-floater-mooring fully-coupled dynamic simulation computer program. To perform the SHM of a FOWT through OMA, natural frequencies, displacement mode shapes (DMS), and curvature mode shapes (CMS) of the tower and blades are obtained and analyzed. The modal properties are systematically compared between the intact and damaged conditions. Their differences are used for damage detection. The results show that CMS is found to be the most effective modal property to detect damage locations and intensities. The performance of the damage detection based on the OMA-CMS analysis is verified by independent FEM (finite element method) results. This study is unique in that the SHM using OMA and CMS for FOWTs is implemented including the floater-tower-blade coupling effects. The technology can contribute to the design of remote SHM system for future FOWTs. A further validated model with field data may build up a huge database for various damage scenarios so that it can be applied to digital-twin-based smart health monitoring technology.

Estimation of airframe weight reduction by integration of piezoelectric and guided wave–based structural health monitoring

Current design rules are analyzed and challenged by considering better damage-detection capabilities offered by structure health monitoring systems. The weight-saving potential associated to the integration of such sensing systems is discussed with regards to structural and structure health monitoring system design. Three prospective scenarios are analyzed and considered in a specific use case. According to the most promising scenario (i.e. robust detectability of damages larger than 300 mm2), structural weight reductions of approximately 9% can be achieved. Considering the weight added by the structure health monitoring system, effective weight savings in the order of 5% are achievable. Although this potential is rather modest, applying structure health monitoring systems on structures mainly driven by the damage tolerance criterion is expected to provide reductions far beyond 5%.

Definition of a load adaptive baseline by inverse finite element method for structural damage identification

Abstract One principle limitation to the implementation of Structural Health Monitoring (SHM) systems in real structures is the influence of different operational conditions with respect to those adopted during SHM system design, potentially leading to damage misclassifications. To overcome this issue, this work proposes a methodology to perform Structural Health Monitoring leveraging on the inverse Finite Element Method (iFEM). The iFEM methodology, based on the minimisation of a weighted least-squares functional defined as a comparison between the experimental strains and the corresponding numerical ones, enables the reconstruction of the strain field of a structure by means of a number of strain sensors without requiring any a-priori knowledge of the boundary load conditions. This allows providing a load-adaptive baseline based on an anomaly index that highlights the actual health state of the structure by comparing the strain reconstructed by the iFEM at some test locations with the strain measured by a test sensor in the same position, independently from the applied load and without training requirements for load cancelling. When the analysed structure is in a “healthy” condition, the two values match, otherwise they do not. If multiple test positions are considered, the damage position can also be inferred. Though the formulation of the diagnostic problem is general for an arbitrary component geometry and damage type, the proposed method is numerically demonstrated by means of a clamped plate subjected to different loads in the presence of single and multiple fatigue crack damages.

Nonlinear features of guided wave scattering from rivet hole nucleated fatigue cracks considering the rough contact surface condition

This article presents the investigation of nonlinear scattering features of guided waves from rivet hole nucleated fatigue cracks considering the rough contact surface condition. A small-size numerical model based on the local interaction simulation approach is developed, enabling the efficient analysis of the contact acoustic nonlinearity during the wave crack interactions. The study starts with an idealized breathing crack model possessing smooth, perfectly kissing contact surfaces. Then, the nature of rough crack surfaces is considered with randomly distributed initial openings and closures. Several distinctive aspects of the nonlinear scattering phenomenon are discussed: (1) the amplitude effect, which renders significantly different nonlinear response under various levels of excitation wave amplitudes; (2) the directivity and mode conversion features, which addresses the scattering direction dependence of the fundamental and superharmonic wave mode components; (3) the nonlinear resonance phenomenon, which maximizes the nonlinear response during the wave crack interactions at certain excitation frequency ranges. This study demonstrates that these nonlinear features are substantially influenced by the crack surface condition and differ much between an idealized breathing crack and a rough crack in most practical cases. Fatigue tests on a thin aluminum plate with a rivet hole is conducted to induce cracks in the specimen. An active sensor array surrounding the crack zone is implemented to generate and receive ultrasonic guided waves in various directions. Current work emphasizes on using a highly efficient numerical model to explain the nonlinear features of scattered waves from fatigue cracks considering the rough crack surface condition. These special features may provide insights and guidelines for nonlinear guided wave based nondestructive evaluation and structural health monitoring system design. The paper finishes with discussion, concluding remarks, and suggestions for future work.

Design of nonlinear-Lamb-wave-based structural health monitoring systems with mitigated adhesive nonlinearity

Structural health monitoring (SHM) techniques with nonlinear Lamb waves offer the possibility of detecting incipient damages through the second harmonic generation. Particularly, the primary S0-secondary S0 Lamb wave mode pair in a weakly nonlinear plate is promising for SHM due to its appealing characteristics such as the cumulative second harmonic generation and flexible frequency selection. In a practical PZT-actuated SHM system, apart from the damage-related material nonlinearity of the plate (MNP), the adhesive nonlinearity (AN) is also proven to be a non-negligible nonlinear source, which may jeopardize damage diagnosis if not properly apprehended. By combining a nonlinear shear-lag model and the normal mode expansion method, a theoretical model is proposed in this work, which allows the investigation and the comparison of these two types of important nonlinearities in the system (AN and MNP). With the developed model, optimized nonlinear Lamb wave-based SHM systems can be designed with the mitigated influence of the undesired AN on the system. Finite element (FE) simulations are carried out to validate the proposed model and the effectiveness of the optimized systems through a tactical adjustment of the different nonlinear sources. The designed optimized system is verified by experiments, in comparison with an arbitrarily chosen one. The dominance level of the nonlinear sources in the two systems is evaluated through changing the MNP, which is realized by a thermal aging treatment. Both FE and experimental results demonstrate that the proposed model can effectively guide the design of SHM systems to mitigate AN so that the MNP can be well measured and further used as an indicator of the incipient structural damage.

Embedded application of convolutional neural networks on Raspberry Pi for SHM

To date, the authors are not aware of an in-depth investigation about embedded applications of the convolutional neural network (CNN) algorithm on small, lightweight, and low-cost hardware (e.g. microcontroller, FPGA, DSP, and Raspberry Pi) applied to detect faults in structural health monitoring (SHM) systems. In this Letter, the authors implement and evaluate both feasibility and performance of an embedded application of the CNN algorithm on the Raspberry Pi 3. The CNN-embedded algorithm quantifies and classifies dissimilarities between the frames representing healthy and damaged structural conditions. In a case study, the CNN-embedded application was experimentally evaluated using three piezoelectric patches glued onto an aluminium plate. The results reveal an impressively effective 100% hit rate. This performance may significantly impact the design and analysis of CNN-based SHM systems where embedded applications are required for identifying structural damage such as those encountered by aerospace structures, rotating machineries, and wind turbines.

Application of sensor technologies for local and distributed structural health monitoring

SUMMARY The work presented in this paper deals with the application of different sensor technologies for fatigue crack damage monitoring of metallic helicopter fuselages. A test programme has been conducted, consisting of seven fatigue crack propagation tests on aluminium panels (skin with riveted stringers) representative of the rear fuselage of a helicopter. Electrical crack gauges and comparative vacuum monitoring sensors have been used locally to monitor propagating cracks. A network of optical fibre Bragg gratings is presented as a valid possibility for distributed monitoring (based on strain field dependence on damage), alternative to consolidated electrical resistance-based strain gauges. A Smart Layer based on piezoelectric transducers that emit and receive Lamb wave signals has also been analysed in this paper for distributed monitoring. Two damages have been considered: a skin crack artificially initiated on a panel bay and a skin crack propagating from a rivet hole after stringer failure. Damage sensitivity has been evaluated and compared among the considered technologies, thus providing useful recommendations for each considered system, together with advantages and drawbacks concerning their suitability for on-board installation and monitoring. The damage index sensitivity to operative condition, load in particular, is verified and compared with damage effect for distributed networks. A finite element model able to describe any selected feature sensitivity to the monitored damage is also presented as a useful tool for the optimization of the structural health monitoring system design process. Copyright © 2013 John Wiley & Sons, Ltd.

Structural Intensity Modeling and Simulations for Damage Detection

Structural health monitoring (SHM) techniques have previously been proposed based on structural intensity (SI) due to its sensitivity to changes in boundary and loading conditions, and impedance, as well as to various damage mechanisms. In this paper, computational techniques for SI-based SHM are presented. Finite element solvers combined with SI equations can yield intensity maps over structures to determine characteristic changes in power flow due to damage. Numerical techniques for structural surface intensity (SSI) are also introduced using two alternative methods: A time domain approach that directly uses SSI equations that are valid at the surface of any elastic solid, and a frequency domain technique, which computes SI for very thin plate elements located at the surface of the structure. Advanced contact features such as nonlinearity can also be included in the model to increase the damage detection sensitivity. A plate model is used to illustrate these capabilities using SSI maps at nonlinear harmonics (NSSI). The results show both improved damage sensitivity and more global detection capabilities in a NSSI-based SHM system. A complex structure is also included to show global and local changes in SSI due simulated damage scenario. The techniques developed can be applied to general SI/SSI assessments and the design of SI-based SHM systems.

Piezoelectric Wafer Active Sensor Structural Health Monitoring of Space Structures

Structural Health Monitoring (SHM) is a valuable tool for in-service assessment of structural condition. Despite a broad use in many engineering fields, SHM has seen limited application in space systems. This article explores specifics of SHM applied to space systems and satellites in particular. It is suggested that SHM may be considered for aiding rapid assembly of spacecraft components, monitoring system dynamics during launch, and model updating from an assessment of in-service variation of structural properties. The article presents a discussion of factors affecting realization of the SHM system for spacecraft and provides recommendations for the system configuration and its practical use. The SHM system design based on a network of piezoelectric active sensors is considered. System operation focuses on SHM of improperly tightened bolts, assessment of adhesive bonds, and embedded material characterization techniques. Synergistic use of the same hardware for acoustoelastic, non-linear acoustic, and material characterization methods is recommended, and further system integration options are proposed.

Multi-mode Damage Detection Methods with Piezoelectric Wafer Active Sensors

PWAS are small and non-invasive transducers that can be easily affixed to a structure to interrogate it at will. Their wideband non-resonant properties make them advantageous candidates for multiple modes structural health monitoring (SHM) and nondestructive evaluation (NDE) simply by changing the driving frequencies. This paper presents research results obtained by using PWAS transducer for SHM/NDE. The results are given in the following directions: (1) PWAS operation principles; (2) PWAS electromechanical impedance measurements; (3) PWAS ultrasonic SHM/NDE; and (4) PWAS multi-mode corrosion detection. The analytical methods and experimental results can be successfully used in the design of active SHM systems to be embedded on operational structures, such as aircraft panels.

Designing strategy for multi-agent system based large structural health monitoring

Density and different kinds of sensors have to be adopted to have a reliable monitoring of large scale engineering structures. To deal with the diverse, heterogeneous and distributed information obtained by these sensors at different sites on the structure, multi-agent system (MAS) based structural health monitoring (SHM) technology is researched in detail in this paper. A general framework to design the multi-agent system for large scale structural health monitoring is proposed. Compared to past work, this framework is typical and flexible, which is easy to be referenced by other researchers to develop their own multi-agent based SHM system. The design strategy of the MAS based SHM is discussed in detail, including function design, ontology design, individual agent design, facilitator design, society behavior and learning behavior design. A MAS based composite SHM system is researched as a case study to evaluate the efficiency of the proposed MAS based SHM system design strategy and the advantages of the MAS based SHM system. Very detail introduction of the implementation of this system is given in the paper.