Structural Monitoring System Research Articles

Structural monitoring system for proactive detection of corrosion and coating failure

Performance and availability of high priority structures, systems and products can be greatly affected by corrosion damage. The application of protective coatings, frequent inspections and scheduled based maintenance activities result in huge direct and indirect financial loss to organisations. The expeditious detection of coating failure and corrosion damage can result in precise and cost-effective condition-based maintenance. Coating failure and corrosion phenomena are driven by complex multi-disciplinary parameters according to extensive research findings in the literature. State-of-the-art prognostic models proposed in recent years incorporate complex multi-disciplinary parameters, therefore a real-time prognostic monitoring system must acquire these complex parameters to allow accurate prediction. The work reported here covers the development of a real-time monitoring system by using micro-sensors and includes the validation of the system through accelerated corrosion and coating failure testing. The system contains a remote terminal unit that includes a linear polarisation method for corrosion detection under the coating and a micro-strain gauge method for monitoring stress behaviour over the coating. The software at a base station includes a graphical user interface and database to store parameters for further processing and failure prediction. Real-time monitoring system can be applied to remote, stationary and mobile assets to monitor mechanical and chemical changes within coating-substrate systems.

Research on Applicability of Fiber Bragg Grating Sensor for Ship Structure Monitoring System

A complete application research of Fiber Bragg Grating sensing technology in ship structure stress monitoring and evaluation system is studied in this paper. The working principles of Fiber Bragg Grating strain sensor in monitoring system are briefly introduced. And a kind of new differential FBG strain sensor for ship structure stress monitoring is applied and verified by a series of calibration and force measurement test systematically. Through finite element calculation and test towards ship structure, some defects of monitoring sensor used in bending deformation are found. Then, a three-dimensional strain sensor arrangement for stress monitoring of hull structure is designed and developed. The satisfactory test results are obtained by this sensor arrangement. Finally, the accuracy and reliability of hull structure monitoring system is improved further through this research results.

A review on deep learning-based structural health monitoring of civil infrastructures

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

Development of Rail Precision Cleaning Vehicle for Modern Tramway

Supported by the Zhuhai Collaborative Innovation Project, we develop a Road-Rail Precision Cleaning Vehicle for the rail of the first modern tramway based on the Tram Wave system in China, which has been built in Zhuhai City. Development scheme of overall mechanical structure, electrical control and condition monitoring system and man-machine interface system has been realized. We also designed a target recognition algorithm based on OpenCV to control actuators like solenoid valve, electromagnetic clutch and air pressure regulating valve and so on.

Continuous monitoring of the Milan Cathedral: dynamic characteristics and vibration-based SHM

The traditional collaboration between Politecnico di Milano and Veneranda Fabbrica del Duomo di Milano—the historic institution established by Gian Galeazzo Visconti in 1387 and having in charge all operational aspects related to the Milan Cathedral since more than 600 years—recently focused on the design and installation of a structural monitoring system, with the objective of assisting the condition-based structural maintenance of the historic church through the continuous interrogation of sensors installed in the structure and the extraction from measured data of features which are representative of the current state of structural health. The new monitoring system of the Milan Cathedral includes different types of measurements and sensors: quasi-static acquisition of strain in selected tie-rods and biaxial tilt of selected piers and the main spire, monitoring of inner and outer environmental parameters and dynamic measurement of the velocity response at the top of 14 piers and at 3 levels of the main spire. After a concise description of the historic church and of the monitoring system, the paper focuses on the dynamic characteristics of the Milan Cathedral, their evolution during the first months of monitoring (since October 16th, 2018) and the lessons learned in view of the structural health monitoring of the monument. The presented results from the vibration monitoring highlight that: (a) 8 global modes of vibration are automatically detected in the frequency range 1.0–5.0 Hz; (b) the resonant frequencies exhibit a distinctive trend of variation, which is mainly driven by temperature; (c) the mode shapes of the cathedral do not show appreciable fluctuations associated with the environmental effects.

Novel technologies open new frontiers in structural engineering

Civil infrastructures, being essential for modern and advanced societies, are the foundation of the dynamic economy and improvement of the quality of people’s lives. The design and construction of such infrastructures involve a significant cost to a country, but the proper use of the scientific methods to monitor and maintain these structures can improve their cost-effectiveness. Civil engineers strive to design and construct structures meeting the highest standards of engineering in order to enhance the durability and functionality of such infrastructures. However, civil engineers have been rather slow in adopting civionics engineering to improve the useful life of infrastructures. It is noted that the new term ‘civionics’ was coined recently to denote structural health monitoring of civil structures with the help of electronic sensors. This article will discuss several lessons learned during the implementation of health monitoring systems for civil structures.

Long-term monitoring for the condition-based structural maintenance of the Milan Cathedral

The Milan Cathedral, whose main structures were erected between 1386 and 1813, is one of the largest masonry monuments ever built. Within the traditional collaboration between Politecnico di Milano and Veneranda Fabbrica del Duomo di Milano–the historic Institution established in 1387 and responsible for the preservation and development of the Cathedral–a structural monitoring system was recently designed and implemented with the two-fold objective of assisting the condition-based structural maintenance of the Cathedral and creating a large archive of experimental data, useful to improve the knowledge of the monument.The new monitoring system, fully computer based and with efficient transmission of the collected data, includes static and dynamic measurements. The static monitoring system consists of: (a) bi-axial tilt-meters installed at the top of selected piers and at 3 levels of the Main Spire; (b) vibrating wire extensometers mounted on the iron tie-rods which are characterized by the higher tensile stress; (c) temperature and humidity sensors for the measurement of internal and external environmental parameters. The dynamic monitoring is performed through seismometers (electro-dynamic velocity sensors) installed at the top of 14 selected piers and at 3 levels of the Main Spire.After a concise historic background on the Milan Cathedral and the description of the sensing devices installed in the church, the paper focuses on the results obtained during the first months of monitoring (since October 16th, 2018) and the lessons learned in view of the Structural Health Monitoring (SHM) of the monument.

Research and Implementations of Structural Monitoring for Bridges and Buildings in Japan

Abstract This paper provides a review on the development of structural monitoring in Japan, with an emphasis on the type, strategy, and utilization of monitoring systems. The review focuses on bridge and building structures using vibration-based techniques. Structural monitoring systems in Japan historically started with the objective of evaluating structural responses against extreme events. In the development of structural monitoring, monitoring systems and collected data were used to verify design assumptions, update specifications, and facilitate the efficacy of vibration control systems. Strategies and case studies on monitoring for the design verification of long-span bridges and tall buildings, the performance of seismic isolation systems in building and bridges, the verification of structural retrofit, the verification of structural control systems (passive, semi-active, and active), structural assessment, and damage detection are described. More recently, the application of monitoring systems has been extended to facilitate efficient operation and effective maintenance through the rationalization of risk and asset management using monitoring data. This paper also summarizes the lessons learned and feedback obtained from case studies on the structural monitoring of bridges and buildings in Japan.

An Orthogonal Matching Pursuit based signal compression and reconstruction approach for electromechanical admittance based structural health monitoring

Abstract Signal compression and reconstruction were critical for damage detection in engineering structural health monitoring (SHM), on account of large amounts of sensor data collected and processed in signal acquisition system. A signal compression and recovery approach for damage detection using piezoelectric ceramic transducer (PZT) in structural monitoring system was proposed in this article. The basis of this approach was to first perform a linear projection of the transmitted data x in the monitoring system onto y by a random matrix and subsequently to feedback the data y to the receiving system. An algorithm of sparsity-adaptive Orthogonal Matching Pursuit (OMP) modified via optimal parameter analysis was explored to improve both the recovery effect and the compression ratio (CR) of compressed sensing (CS) in data processing stage. A statistical index was then introduced to identify the vector characteristics. The proposed method was sufficiently validated with the electromechanical admittance (EMA) data collected in an experiment for local damage detection on a simply-supported steel beam, and further applied to a long-time health monitoring of full-scaled shield tunnel segment structure. Qualitative and quantitative comparisons between the reconstructed and the original signals in structural damage detection under multiple conditions indicated that the proposed compression and recovery approach was of high accuracy and robustness to immune from the sensor conditions and temperature/environment impact, thus providing promising assistance to the impedance/admittance based SHM practice.

Piezoceramic patches for energy harvesting and sensing purposes

This paper deals with a design, modelling, simulation, and test of vibrating mechanical cantilever with bonded piezoelectric patches for energy harvesting and sensing purposes. An experimental flexible structure was designed and piezoceramic patches were placed originally as energy harvesting devices. Furthermore, additional sensing functionality of piezoceramic patches is investigated in this paper. Such piezoceramic patches are integrated in the cantilever design and they could represent, for example, smart layers of an advanced aircraft structure. The design and position of the piezoceramic patches were analysed in the ANSYS environment. The finite element model was used to predict output voltage and power for varied vibration modes. This proposed design of the cantilever with piezoceramic patches was tested in laboratory conditions, and voltage response for varied mechanical excitation was measured and analysed for both energy harvesting and sensing purposes. Proposed paper will also present an example of practical usage of the tested design for impact detection. It could be mainly used in structural monitoring systems or health and usage systems in aircraft applications.

THE DEVELOPMENT OF INFORMATION TECHNOLOGY OF STRUCTURAL HEALTH MONITORING SYSTEMS

Objectives. The aim of the study is to develop information technology design systems for monitoring load-bearing structures of buildings and structures of a higher category of responsibility based on the initial data on the construction object and the results of engineering surveys.Method. The article discusses the approach to the formalization of the description of the procedure for developing projects for monitoring buildings and structures, based on the design features of the SMC building structures, the engineering experience of designing these systems.Result. The article presents the conceptual foundations of the developed information technology, the algorithm for determining the monitoring mode based on information about the construction object, the algorithm for the macro to determine the most loaded nodes and elements in the complex finite element modeling. Recommendations are given for determining the control parameters, the composition of the measuring equipment.Conclusion. The conceptual foundations of information technology developed in the course of the research allow for the further development of algorithms and programs for the automated analysis of information about the object and the construction site in order to obtain the automatic mode of the results necessary for developing monitoring systems for buildings and structures of a higher category of responsibility.

Wireless sensor network for structural health monitoring: A contemporary review of technologies, challenges, and future direction

The importance of wireless sensor networks in structural health monitoring is unceasingly growing, because of the increasing demand for both safety and security in the cities. The speedy growth of wireless technologies has considerably developed the progress of structural monitoring systems with the combination of wireless sensor network technology. Wireless sensor network–based structural health monitoring system introduces a novel technology with compelling advantages in comparison to traditional wired system, which has the benefits of reducing installation and maintenance costs of structural health monitoring systems. However, structural health monitoring has brought an additional complex challenges in network design to wireless sensor networks. This article presents a contemporary review of collective experience the researchers have gained from the application of wireless sensor networks for structural health monitoring. Technologies of wired and wireless sensor systems are investigated along with wireless sensor node architecture, functionality, communication technologies, and its popular operating systems. Then, comprehensive summaries for the state-of-the-art academic and commercial wireless platform technologies used in laboratory testbeds and field test deployments for structural health monitoring applications are reviewed and tabulated. Following that, classification taxonomy of the key challenges associated with wireless sensor networks for structural health monitoring to assist the researchers in understanding the obstacles and the suitability of implementing wireless technology for structural health monitoring applications are deeply discussed with available research efforts in order to overcome these challenges. Finally, open research issues in wireless sensor networks for structural health monitoring are explored.

Modern european methods of non-destructive diagnostics of bridge structures

Introduction. Various existing methods of non-destructive diagnostics, in particular for diagnostics of bridge structures are analyzed. However, nowadays in different countries of the world the researches are under way on the search for the most informative methods of non-destructive diagnostics of building structures, facilities, in particular bridge structures, which would enable to receive reliable data on the processes occurring in the structures under the influence of various factors. Problem Statement. Existing methods of non-destructive diagnostics which are used for the diagnostics of bridge structures basically consist in periodic placement of sensors on structures. Having gathered information, the sensors are dismantled. Such actions are repeated as the time of the next inspection comes. In addition, measurements are fulfilled only at the discrete points, as the most devices and equipment have a limited operating range of measurements. The small amount of data received and the long interval between their acquisitions cannot provide signaling about the inevitable disaster that may be caused by various impact factors. Purpose. The ultimate goal of the international scientific organization FEHRL, within the framework of which the SENSKIN Consortium works, is to develop a system for monitoring bridge structures in the framework of the international research project «SENSKIN» – «Sensing Skin for monitoring-based maintenance on the transport infrastructure». Conclusions. Participants of the project «SENSKIN», including «DerzhorNDI» SE as a Consortium member, developed the sensors that will collect information on bridges, power supplies, data transmission and processing modules, software and other components of the bridge structure monitoring system. At this stage, the prototype of the monitoring system has been tested on the full-scale objects. Current information on the monitoring system can be found on the website of the SENSKIN Consortium http://www.senskin.eu. For more reliable operation of non-standard bridges (the bridges which parameters exceed the limit values according to the adopted classification of bridges) in Ukraine, it is necessary to plan the transition to monitoring of bridge structures using the systems that would enable the acquisition of the necessary information about the state of structures in the event of catastrophic situations that will allow avoiding, in particular, the death of people.

Modern european methods of non-destructive diagnostics of bridge structures / Сучасний європейський метод неруйнівної діагностики мостових конструкцій

Introduction. Various existing methods of non-destructive diagnostics, in particular for diagnostics of bridge structures are analyzed. However, nowadays in different countries of the world the researches are under way on the search for the most informative methods of non-destructive diagnostics of building structures, facilities, in particular bridge structures, which would enable to receive reliable data on the processes occurring in the structures under the influence of various factors. Problem Statement. Existing methods of non-destructive diagnostics which are used for the diagnostics of bridge structures basically consist in periodic placement of sensors on structures. Having gathered information, the sensors are dismantled. Such actions are repeated as the time of the next inspection comes. In addition, measurements are fulfilled only at the discrete points, as the most devices and equipment have a limited operating range of measurements. The small amount of data received and the long interval between their acquisitions cannot provide signaling about the inevitable disaster that may be caused by various impact factors. Purpose. The ultimate goal of the international scientific organization FEHRL, within the framework of which the SENSKIN Consortium works, is to develop a system for monitoring bridge structures in the framework of the international research project «SENSKIN» – «Sensing Skin for monitoring-based maintenance on the transport infrastructure». Conclusions. Participants of the project «SENSKIN», including «DerzhorNDI» SE as a Consortium member, developed the sensors that will collect information on bridges, power supplies, data transmission and processing modules, software and other components of the bridge structure monitoring system. At this stage, the prototype of the monitoring system has been tested on the full-scale objects. Current information on the monitoring system can be found on the website of the SENSKIN Consortium http://www.senskin.eu. For more reliable operation of non-standard bridges (the bridges which parameters exceed the limit values according to the adopted classification of bridges) in Ukraine, it is necessary to plan the transition to monitoring of bridge structures using the systems that would enable the acquisition of the necessary information about the state of structures in the event of catastrophic situations that will allow avoiding, in particular, the death of people.

A 3D-printed stretchable strain sensor for wind sensing

Stretchable strain sensors with large strain range, high sensitivity, and excellent reliability are of great interest to applications in soft robotics, wearable devices, and structure-monitoring systems. Unlike conventional template lithography-based approaches, 3D-printing can be used to fabricate complex devices in a simple and cost-effective manner. In this paper, we report 3D-printed stretchable strain sensors that embed a flexible conductive composite material in a hyper-elastic substrate. Three commercially available conductive filaments are explored, among which the ETPU from Rubber3D Printing, Sweden, shows the highest sensitivity (gauge factor of 20), with a working strain range of 0%–12.5%. The ETPU strain sensor exhibits an interesting behavior where the conductivity increases with the strain. In addition, the resistance change of the ETPU sensor in a doubly-clamped configuration in response to a wind stimulus is characterized, and the sensor shows sensitivity to wind velocity beyond 3.5 m s−1. The experimentally identified material parameters are used in finite-element modeling and simulation to investigate the behavior of the 3D-printed stretchable strain sensor when subjected to wind loading. In particular, the model-predicted sensor output at different wind speeds, obtained with the computed sensor strain and the experimentally characterized strain-resistance relationship, achieves good match with the experimental data.

Scalable Monitoring System for the Localization of Damaging Events in Thin-Walled CFRP Structures Based on Acoustic Emission Analysis and Neural Networks

A constant challenge for the design and operation of CFRP primary structures is their sensitivity towards impact loading. This can lead to the formation of externally invisible delaminations which endanger the structural integrity. In practice, this circumstance is encountered with elaborate inspections or conservative design. Structural Heath Monitoring (SHM) systems offer the potential for permanent monitoring and represent an alternative approach that has drawn more attention in the last decade. The biggest barriers to market entry for this technology are system costs and reliability. This study is dedicated to these two points with the development of a low-cost system with which representative acoustic emission sources can be located reliably in a complex CFRP structure. The implementation is carried out using acoustic emission analysis, which represents a promising solution for the integral monitoring of primary structures. It is based on the detection of acoustic waves that are released during crack initiation and growth and propagate over large areas in thin-walled structures as Lamb waves. The challenges of source localization in thin-walled CFRP structures lie in the consideration of wave dispersion, anisotropic material properties, variable component geometry and interfaces. In this thesis, this complexity is captured by training a neural network. For this purpose, artificial sources are used which imitate acoustic emissions of typical damaging events in the material in frequency and mode content. The demonstrating component is an omega profile equipped with a network of piezoelectric sensors that is designed for reliable localization within a defined window. Signal processing takes place on a single-board computer which, together with a digital oscilloscope, completes the measurement chain. The system represents a modular, low-cost approach that can be transferred to other applications by adapting the hardware and training.

A Colorimetric Multifunctional Sensing Method for Structural-Durability-Health Monitoring Systems.

A colorimetric multifunctional phototransmittance-based structural durability monitoring system is developed. The system consists of an array with four indium gallium zinc oxide (IGZO)-based phototransistors, a light source at a wavelength of 405 nm through a side-emitting optical fiber, and pH- and Cl-selective color-variable membranes. Under illumination at the wavelength of 405 nm at corrosion status, the pH- and Cl-responsive membrane, showing a change in their color, generates a change in the intensity of the transmitted light, which is received by the phototransistor array in the form of an electrical current. Ids and R (Ids /IpH 12 ) are inversely proportional to the pH, which ranges from 10 to 12. When the pH drops from 12 to 10, the magnitude of Ids and R increases to ≈103 . In the case of Cl detection, Ids and R (Ids /ICl 0 wt% ) increase nearly 50 times with an increase in Cl concentration of 0.05 wt%, and when the Cl concentration reaches 0.30 wt%, Ids and R increase to ≈103 times greater. This multifunctional colorimetric durability sensing system demonstrates considerable potential as a novel smart-diagnostic tool of structural durability with high stability, high sensitivity, and multifunction.

Piezoresistive Load Sensing and Percolation Phenomena in Portland Cement Composite Modified with In-Situ Synthesized Carbon Nanofibers.

Carbon nanofibers (CNFs) were directly synthesized on Portland cement particles by chemical vapor deposition. The so-produced cements contained between 2.51–2.71 wt% of CNFs; depending on the production batch. Several mortar mixes containing between 0 and 10 wt% of the modified cement were produced and the electrical properties at various ages and the load sensing capabilities determined. The percolation threshold related to the electrical conductivity was detected and corresponded to the amount of the present CNFs, 0.271, 0.189, 0.135 and 0.108 wt%. The observed threshold depended on the degree of hydration of the Portland cement. The studied mortars showed a strong piezoresistive response to the applied compressive load reaching a 17% change of the electrical resistivity at an applied load of 3.5 MPa and 90% at 26 MPa. This initial study showed that the studied material is potentially suitable for future development of novel fully integrated monitoring systems for concrete structures.

Failure Analysis of Topside Facilities on Oil/Gas Platforms in the Bohai Sea

The jacket platform in the Bohai Sea oilfield is an important engineering development, offering design alternatives in this economically important region. However, ice-induced vibration in cold areas threatens the safety and operation of these platforms. On two occasions, intense ice-induced vibrations triggered the rupture of a well’s blow down pipeline, loosening the flanges on the Bohai platform, and leading to the ejection of high-pressure natural gas. Subsequent mechanical analysis of the failed parts helped define the mechanism of failure and identified the failure criteria, based on a prototype structure monitoring system. The analysis revealed that the deck’s inertial force, which resulted in ice-induced steady-state vibration, was the major cause of the accident. Three fixed cones were thus installed on the platform the following winter, effectively reducing the vibrations.

Lamb Wave Mode Decomposition Based on Cross-Wigner-Ville Distribution and Its Application to Anomaly Imaging for Structural Health Monitoring.

Lamb waves are characterized by their multimodal and dispersive propagation, which often complicates analysis. This paper presents a method for separation of the mode components and reflected components in sensor signals in an active structural health monitoring (SHM) system. The system is trained using linear chirp signals but works for arbitrary excitation signals. The training process employs the cross-Wigner-Ville distribution (xWVD) of the excitation signal and the sensor signal to separate the temporally overlapped modes in the time-frequency domain. The mode decomposition method uses a ridge extraction algorithm to separate each signal component in the time-frequency distribution. Once the individual modes are separated in the time-frequency domain, they are reconstructed in the time domain using the inverse xWVD operation. The propagation impulse response associated with each component can be directly estimated for chirp inputs. The estimated propagation impulse response can be used to separate the modes resulting from arbitrary excitation signals as long as their frequency components fall in the range of the chirp signal. The usefulness of the mode decomposition algorithm is demonstrated on a new health monitoring system for composite structures. This system performs anomaly imaging using the first arriving mode extracted from sensor array signals acquired from the structure. The anomaly maps are computed using a sparse tomographic reconstruction algorithm. The reconstructed map can locate anomalies on the structure and estimate their boundaries. Comparisons with methods that do not employ mode decomposition and/or sparse reconstruction techniques indicate a substantially better performance for the method of this paper.