SHM System Research Articles

Sensor placement optimization applied to laminated composite plates under vibration

The location optimization of sensors is a essential problem in structural health monitoring systems. Taking the cost of sensors into account, it is uneconomical to install sensors on every part of a structure and moreover in aeronautical industry, the weight is a crucial factor. In this paper, a optimal placement optimization of sensor locations for structural health monitoring systems is studied. Several techniques of optimization of sensors are approached and applied in a shell structure. The structure, a laminate of carbon fiber, was modeled by the finite element method (FEM) and then subject to free vibration. Genetic algorithms (GAs) are then employed to locate the best sensor distribution to cover a specific number of low frequency modes. Numerical results have demonstrated the overall efficiency of sensor delivery methods. Specific problems occurred, especially regarding the method of effective independence, being less efficient and discrepant in relation to the other methods employed. In summary, the results obtained in this paper provide an optimal position for sensors in real SHM systems and experiments.

A case study for application of fuzzy inference and data mining in structural health monitoring

In this study, a system for monitoring the structural health of bridge deck and predicting various possible damages to this section was designed based on measuring the temperature and humidity with the use of wireless sensor networks, and then it was implemented and investigated. A scaled model of a conventional medium sized bridge (length of 50 meters, height of 10 meters, and with 2 piers) was examined for the purpose of this study. This method includes installing two sensor nodes with the ability of measuring temperature and humidity on both side of the bridge deck. The data collected by the system including temperature and humidity values are received by a LABVIEW-based software to be analyzed and stored in a database. Proposed SHM monitoring system is equipped by a novel method of using data mining techniques on the database of climatic conditions of past few years related to the location of the bridge to predict the occurrence and severity of future damages. In addition, this system has several alarm levels which are based on analysis of bridge conditions with fuzzy inference method, so it can issue proactive and precise warnings and alarms in terms of place of occurrence and severity of possible damages in the bridge deck to ensure total productive (TPM) and proactive maintenance. Very low costs, increased efficiency of the bridge service, and reduced maintenance costs makes this SHM system a practical and applicable system. The data and results related to all mentioned subjects were thoroughly discussed .

Numerical and experimental study of a SHM system for a drop-ply delaminated configuration

The present paper presents the experimental and FE numerical analyses of a Structural Health Monitoring system for a drop-ply configuration. In order to verify the mechanical experimental setup of the assembling between the host structure and the piezo-film patches in term of constraint, transient and modal analyses are first performed in order to compare the experimental responses to those obtained by from the numerical analyses performed with the commercial code COMSOL Multiphysics®. Then the Finite Element modelling of the piezoelectric sensors, to be used in the numerical analysis of the assembled structure, is validated through the comparison with the experimental data provided by the sensors manufacturer. Lastly, dynamic experimental and numerical analyses are performed on the undamaged and damaged drop-ply configuration in order to verify the effectiveness of a damage index in highlighting the position of the delamination tips.

Assessment of a monumental masonry bell-tower after 2016 Central Italy seismic sequence by long-term SHM

The response of the San Pietro monumental bell-tower located in Perugia, Italy, to the 2016 Central Italy seismic sequence is investigated, taking advantage of the availability of field data recorded by a vibration-based SHM system installed in December 2014 to detect earthquake-induced damages. The tower is located about 85 km in the NW direction from the epicenter of the first major shock of the sequence, the Accumoli Mw6.0 earthquake of August 24th, resulting in a small local PGA of about 30 cm/s2, whereby near-field PGA was measured as 915.97 cm/s2 (E–W component) and 445.59 cm/s2 (N–S component). Similar PGA values also characterized the two other major shocks of the sequence (Ussita Mw5.9 and Norcia Mw6.5 earthquakes of October 26th and 30th, respectively). Despite the relatively low intensity of such earthquakes in Perugia, the analysis of long-term monitoring data clearly highlights that small permanent changes in the structural behavior of the bell-tower have occurred after the earthquakes, with decreases in all identified natural frequencies. Such natural frequency decays are fully consistent with what predicted by non-linear finite element simulations and, in particular, with the development of microcracks at the base of the columns of the belfry. Microcracks in these regions, and in the rest of tower, are however hardly distinguishable from pre-existing ones and from the physiological cracking of a masonry structure, what validates the effectiveness of the SHM system in detecting earthquake-induced damage at a stage where this is not yet detectable by visual inspections.

Damage Detection in Composite Skin Stiffener with Hybrid PZT-FO SHM System

A hybrid piezoelectric (PZT)/fibre optic diagnostic system has been developed for damage detection in built up composite structures. The hybrid system uses PZT transducers to actuate the structure and fibre optic (FO) sensors to capture the propagating wave. The diagnostic system will then have the advantages of both PZT and FO sensors. The applicability of the system is then tested for detecting an artificial damage at a skin/stiffener interface of a thick composite structure. The response of the FO sensors is then compared to PZT sensors and presented.

Improved axle detection for bridge weigh-in-motion systems using fiber optic sensors

Bridge weigh-in-motion (B-WIM) systems provide a non-destructive means of gathering traffic loading information by using an existing bridge as a weighing scale to determine the weights of vehicles passing over. In this research critical locations for sensors for the next-generation B-WIM were determined from a full 3D explicit finite element analysis (FEA) model. Although fiber optic sensors (FOS) have become increasingly popular in SHM systems there are currently no commercially available fiber optic WIM systems available. The FEA in this research facilitated the development of the first ever full fiber optic B-WIM and its potential has been demonstrated with the site installation of this system. The system combined nothing-on-the-road axle detection and alternative methods of measuring strain at the supports. The system was installed on a 20-m span beam and slab RC bridge in Northern Ireland and the results presented in this paper confirm the suitability of FOS in providing the clear defined peaks required for accurate axle detection in B-WIM.

SHM of a stayed bridge during a structural failure, case study: the Rio Papaloapan Bridge

The Rio Papaloapan Bridge in Mexico is a stayed structure that has reported structural problems; it has required extra rehabilitation works besides a SHM system for continuous remote monitoring. The main problems were identified as structural deficiencies in the upper anchoring elements of the cables and up till now, these have caused two fractures and loosening of cables. The first failure, reported in 2000, was produced by deficiencies of the constitutive material and, in June 2015; a second failure took place due to a defective weld. In 2013 a SHM system was installed in the bridge for permanent remote monitoring, and although it did not have the ability to prevent the second failure, it was possible to measure, reproduce and evaluate the structural behavior of the bridge during and after this event; this information was very valuable to assess the overall structural integrity of the bridge and to quantify the effect of the failure to decide immediate preventive actions and to verify the effectiveness of the rehabilitation to recuperate the initial condition. This case study describes how the problem was addressed using the information collected from the monitoring system, and from the point of view of cost effectiveness of the SHM system, an initial evaluation of the costs and benefits has been done to estimate the value of having the information in almost real time for decision-making and to assure the bridge safety and integrity, versus the initial investment cost for the SHM system. As an initial conclusion, SHM are cost effective when structures are under many external or structural uncertainties affecting the bridge´s reliability.

Potentiality of SHM and PFA for a new design approach of low weight aircraft structures

The object of this work is to show the potentiality of the application of SHM systems and PFA methodology, from the beginning of the design phase of wing box composite stiffened panels, for obtaining lighter structures respect to the current ones. The common industrial approach to satisfy the certification requirements (EASA AMC 20-29) for composite structures, based mainly on the application of high conservative knockdown factors to the material strength properties and/or performing extensive test campaigns, can lead to oversized structures and to an increase in costs and timing. The use of information coming from SHM systems and of the PFA methodology could exploit the full potential of damaged composite materials, in favour of a greater weight reduction. By detecting the damages thanks to SHM systems, the structure could be designed with higher design allowables (more reliable detection of BVID) improving the static strength for a reduced damage size detection.Two aircraft wing box composite stiffened panels have been preliminary designed under static compressive load, one panel at the wing root and the other one at the wing tip, according to the traditional industrial design approach. Then, they have been re-designed releasing some of the current conservative criteria, because they were considered resolved by SHM systems: no BVID knockdown factor, no notch material design allowables (only bonded joints and bonded repair are considered) have been applied. The new design has shown the potential weight reduction achievable, the design parameters and panel subparts to which the panel weight is more sensitive. The results of these analyses provide fundamental requirements for the SHM system definition in terms of “where to monitor and why”.Successively, in order to exploit the actual residual strength of impact damaged panels, PFA has been performed also on the stiffened panels considering a discrete damage model against the traditional design approach; the latter, based on the first ply failure design criteria and assuming the structure uniformly damaged by using reduced design allowable obtained at coupon level. The results show that a significant weight reduction is potentially achievable by using PFA, and the potentiality of this methodology as a valid design tool to investigate a new design philosophy based on the evaluation of the residual strength of panels with discrete damages.

Cognitive Sensor Technology for Structural Health Monitoring

Current paper presents artificial neural network architecture based on Cognitive Sensor technology which may be used for development of intelligent SHM systems. Dynamic Artificial Neural Network (DANN) has time dependent structure which is defined by experience of processing input data streams. Advantages of proposed model include ability to learn both linear and non-linear patterns on the basis of processing data streams. Evolution of DANN architecture includes stage of autonomous growth of subnets developed by separate Cognitive Sensors and stage of cooperative growth of resulting network. Example application of proposed cognitive technology for solution of Structural Health Monitoring problems is discussed.

Wind Turbine vibration based SHM system: influence of the sensors layout and noise

With the goal of reducing the investment in monitoring equipment and simultaneously keep an adequate accuracy in structural condition assessment, this paper studies the results that can be obtained with different strategies of instrumentation of a 2.0 MW onshore wind turbine. The data processing strategy is based on the continuous tracking of the wind turbine main vibration modes using Operational Modal Analysis techniques combined with algorithms that deal with the particularities of operation of the wind turbines and that permit an online automated identification. A database of continuously collected acceleration time series during one year is used to evaluate the efficiency on the monitoring system on the detection of simulated damage scenarios, considering variations on the number of sensors, on their distribution in the wind turbine tower and on their noise level.

Interdigital lamb wave transducers for applications in structural health monitoring

Interdigital transducers (IDTs), thanks to their multiple capabilities have the potential of increasing versatility of SHM systems. Migration of the IDT technology in SHM systems and devices is reviewed in this paper. A summary review of different types of IDTs is presented and their salient features are presented in terms of their applicability in the Lamb wave based SHM systems. Comprehensive review is provided concerning the implementation of the IDT capabilities towards the development of SHM systems. Experimental results obtained with prototype IDTs are provided for illustration. Finally, future development directions of the IDTs dedicated to SHM systems are outlined.

SHM and evaluation of a continuous reinforced concrete pavement

To assess the long-term behavior of a new concept of a continuous reinforced concrete pavement (CRCP), an SHM system was designed using 27 strain, 2 acceleration and 5 temperature FBG optical sensors, all embedded in concrete. The main objective was to monitor the performance of the reinforcement steel and concrete, considering vibrations and strains due to live loads and thermal effects. The test pavement was built on one of the most important highways in Mexico with nearly 50,000 vehicles per day, where 40 % are heavy vehicles. The CRCP has been evaluated under controlled and operational live loads, and dynamic responses have been correlated to temperature changes and thermal gradients. After almost 3 years of regular monitoring, it has been found that the FBG sensor system has been able to evaluate the structural evolution of the pavement. At present, structural changes have been identified due to mayor cracking as a result of combined thermal stresses, pavement deformations and dynamic loads. Stress changes and distributions have been measured, and although the pavement did not achieve the expected useful life; monitoring data has become a very useful data base to understand the pavement behavior and to redesign an operational cost-effective pavement. As for the CRCP performance, results show that the proposed design is not adequate for high loads and high traffic conditions. Pavement redesign must consider the use of more steel reinforcement to control cracking and should also take into account temperature gradients and the base–pavement interaction.

Computational model for supporting SHM systems design: Damage identification via numerical analyses

This work presents a computational model to simulate thin structures monitored by piezoelectric sensors in order to support the design of SHM systems, which use vibration based methods. Thus, a new shell finite element model was proposed and implemented via a User ELement subroutine (UEL) into the commercial package ABAQUS™. This model was based on a modified First Order Shear Theory (FOST) for piezoelectric composite laminates. After that, damaged cantilever beams with two piezoelectric sensors in different positions were investigated by using experimental analyses and the proposed computational model. A maximum difference in the magnitude of the FRFs between numerical and experimental analyses of 7.45% was found near the resonance regions. For damage identification, different levels of damage severity were evaluated by seven damage metrics, including one proposed by the present authors. Numerical and experimental damage metrics values were compared, showing a good correlation in terms of tendency. Finally, based on comparisons of numerical and experimental results, it is shown a discussion about the potentials and limitations of the proposed computational model to be used for supporting SHM systems design.

Multi-stage temperature compensation method for Lamb wave measurements

One of the important issues related to the applications of Lamb waves for structural health monitoring is their undesired sensitivity to variation of environmental conditions. Temperature is the main factor that can affect wave propagation and hence significantly reduce performance of a SHM system. Therefore, there is a need for development of robust monitoring methods with low sensitivity to temperature variations. This paper is aimed at verification of efficiency of four methods designed for damage detection using Lamb wave measurements performed in variable environmental conditions. The methods investigated in the comparison are the following: optimal baseline selection approach, the damage index based on a signal alignment with respect to instantaneous phase, and a group measurement approach capable of distinguishing local damage-related changes from temperature-induced global ones. The fourth method relies on fusion all these solutions simultaneously. The methods’ ability to damage detection is compared using a specimen that is subjected to large temperature changes. It is found that although all the methods have their strengths and weaknesses, a cooperation of all solutions allows for significant increase of the damage detection efficiency.

A Sensor Fault Detection Methodology applied to Piezoelectric Active Systems in Structural Health Monitoring Applications

Damage detection is the basis of the damage identification task in Structural Health Monitoring. A good damage detection process can ensure the adequate work of a SHM System because allows to know early information about the presence of a damage in a structure under evaluation. However this process is based on the premise that all sensors are well installed and they are working properly, however, it is not true all the time. Problems such as debonding, cuts and the use of the sensors under different environmental and operational conditions result in changes in the vibrational response and a bad functioning in the SHM system. As a contribution to evaluate the state of the sensors in a SHM system, this paper describes a methodology for sensor fault detection in a piezoelectric active system. The methodology involves the use of PCA for multivariate analysis and some damage indices as pattern recognition technique and is tested in a blade from a wind turbine where different scenarios are evaluated including sensor cuts and debonding.

Field monitoring and numerical simulation of the thermal actions of a supertall structure

Summary Structural temperature is an important loading that must be considered during the design, construction, and safety assessment. The thermal action of supertall structures has rarely been investigated because of insufficient real measurement data, as compared with that on bridges. In this study, the thermal action of the 600-m-tall Canton Tower is investigated on the basis of the comprehensive long-term SHM system installed on the structure and the numerical simulation. First, the temperature model of the entire structure is derived by using the field monitoring and numerical heat transfer analysis data. In particular, (i) the temperature difference between different facades of the inner tube, (ii) the temperature difference profile of the outer tube, and (iii) the distribution of the temperature difference between the inner and outer tubes along the structural height are presented in detail. Results show that the nonuniform distribution of the temperature field between the different components of the structure is significant and should be carefully considered in the analysis of such a complex supertall structure. Second, the temperature effects on structural displacement, stress, and internal forces consisting of (i) the tower top horizontal displacement during different seasons, (ii) the stresses of different levels/components, and (iii) the bending moments/shear forces along the structural height are investigated. The simulated results obtained by using the global finite element model of the tower are verified through a comparison with the measurements. This study provides first-hand data for the design of supertall structures in the tropical region of China. Copyright © 2016 John Wiley & Sons, Ltd.

Real‐time damage detection based on pattern recognition

AbstractStructural health monitoring (SHM) can be defined as the process of developing and implementing structural damage detection strategies. Ideally, this detection should be carried out in real time before damage reaches a critical state and impairs structural performance and safety. Hence, it must be based on sensorial systems permanently installed on the target structures and on fully automatic detection methodologies.The ability to detect damage in real‐time is vital for controlling the safety of old structures or for post‐retrofitting/post‐accident situations, where it might even be mandatory for ensuring a safe service. Under these constraints, SHM systems and strategies must be capable of conducting baseline‐free damage identification, i.e. they must not rely on comparing newly acquired data with baseline references in which structures must be assumed as undamaged.The present paper describes an original strategy for baseline‐free damage detection based on the application of artificial neural networks and clustering methods in a moving windows process. The proposed strategy was tested on and validated with numerical and experimental data obtained from a concrete cable stayed bridge and proved effective for the automatic detection of small stiffness reductions in single stay cables as well as the detachment of neoprene pads in anchoring devices, requiring only a small number of inexpensive sensors.

Proof of Concept of Crack Localization Using Negative Pressure Waves in Closed Tubes for Later Application in Effective SHM System for Additive Manufactured Components

Additive manufactured components have a different metallurgic structure and are more prone to fatigue cracks than conventionally produced metals. In earlier papers, an effective Structural Health Monitoring solution was presented to detect fatigue cracks in additive manufactured components. Small subsurface capillaries are embedded in the structure and pressurized (vacuum or overpressure). A crack that initiated at the component’s surface will propagate towards the capillary and finally breach it. One capillary suffices to inspect a large area of the component, which makes it interesting to locate the crack on the basis of the pressure measurements. Negative pressure waves (NPW) arise from the abrupt encounter of high pressure fluid with low pressure fluid and can serve as a basis to locate the crack. A test set-up with a controllable leak valve was built to investigate the feasibility of using NPW to localize a leak in closed tubes with small lengths. Reflections are expected to occur at the ends of the tube, possibly limiting the localization accuracy. In this paper, the results of the tests on the test set-up are reported. It will be shown that the crack could be localized with high accuracy (millimeter accuracy) which proves the concept of crack localization on basis of NPW in a closed tube of small length.

Structural Monitoring with Distributed-Regional and Event-based NN-Decision Tree Learning Using Mobile Multi-Agent Systems and Common Java Script Platforms

Among the Internet-of-Things, one major field of application deploying agent-based sensor and information processing is Structural Load and Structural Health Monitoring (SLM/SHM) of mechanical structures. This work investigates a data processing approach for material-integrated and mobile ubiquitous SHM and SLM systems by using self-organizing mobile multi-agent systems (MAS), executed on a highly portable JavaScript-based Agent Processing Platform (APP), and optimized Machine Learning (ML) methods providing load class recognition from a set of sensors embedded in the technical structure. Machine learning approaches usually require a large amount of computational power and storage resources and ML is commonly performed off-line, not suitable for resource constrained sensor network implementations. Instead, a novel distributed-regional on-line learning is applied, with on-line distributed sensor processing and learning performed by the agent system. The APP provides ML as a service, and the agent itself only collects training and analysis data passed to the APP, finally returning a learned model that is saved by the agent in a compact format (and is available on any other location). A case study shows that the learning algorithm is suitable (stable) for noisy and time varying sensor data. Spatial global learning is reduced and mapped on local region learning with global voting.

Application of the Fatigue Crack Opening/Closing Effect for SHM Using Electromechanical Impedance Technology

Earlier the effect of fatigue crack opening/closing (FCOC) to ultrasound guided wave propagation was investigated. The purpose of this article is to evaluate this effect to the electromechanical impedance (EMI) of the system "piezoelectric transducer / host structure. Experimental study performed using the flat samples of aluminum alloy. One of them had the 4 mm central hole. Other sample after fatigue testing had central fatigue crack of 40 mm length (including a 4 mm central hole for the initiation of a fatigue crack. Each sample was loaded by tensile axial static load from zero to 12 kN and the EMI measurement after eacn 2 kN incrementat of load. The EMI was measured in the frequency range of 20-40 kHz. It is established that the FCOC effect to magnitude and reactance of EMI mainly associated with variation of the capacitance of PZT under mechanical load. But the effect to the PZT resistance is more complex and more significant. The result of the study is the base of some procedure of fatigue crack detecting by the EMI method without baseline use. The developed model of EMI of ’host structure – PZT’ that is based on the modal decomposition of dynamic response of this system allows to solve main problems of the SHM system designing and optimizing of its parameters.