Monitoring Of Dynamic Response Research Articles

Mechanical-electric response characteristics of 1–3 connectivity pattern cement-based piezoelectric composite sensors with varying functional phase parameters under impact loading

In this study, 1–3 connectivity pattern cement-based piezoelectric composites (CPCs) and cement-based piezoelectric composite sensors (CPCSs) with varying functional phase parameters were developed. The essential properties of the CPC specimens were systematically characterized. Additionally, the mechanical-electric response characteristics of the CPCS specimens under impact loading were examined using the split Hopkinson pressure bar (SHPB) technique. The results indicate that the piezoelectric constant (d33) of the CPC specimens increases with higher functional phase volume ratios and greater composite thickness. Under impact loading, both stress and electric displacement showed similar response patterns, demonstrating a strong force-electric coupling. Furthermore, within the experimental range, the electric displacement of the CPCS specimens increased with strain rate, indicating their potential for real-time monitoring of dynamic responses under varying impact conditions.

Extreme load extrapolation and long-term fatigue assessment of offshore wind turbine tower based on monitoring data

Extreme load and fatigue damage are important parameters in the structural design of offshore wind turbines (OWTs). The purpose of this study is to obtain extreme loads and long-term fatigue damage assessment of OWT structures based on measured data. In the present study, a utility-scale OWT was monitored with a dynamic response monitoring system and long-term strains of the OWT tower were collected. Based on the monitoring strain and the operational conditions of the OWT, the load and fatigue characteristics of the OWT tower were discussed. Furthermore, statistical extrapolation of the extreme load of the OWT tower was performed and the applicability of different statistical extrapolation methods was studied. The results indicate that the same probability distribution model does not apply to all wind speeds. The maximum extreme load is extrapolated in the vicinity of the rated wind speed. Finally, the relationship between short-term fatigue damage and long-term fatigue damage of the OWT structure was discussed. Superimposing fatigue from a short calculation period underestimates the long-term fatigue of OWT structures due to significant calculation period impact. Therefore, an evaluation method for OWT structures' long-term fatigue was established to improve the accuracy of long-term fatigue calculation by superimposing short calculation periods.

A general data quality evaluation framework for dynamic response monitoring of long-span bridges

The structural health monitoring system (SHM) of long-span bridges inevitably produces low-quality data. It is important to evaluate the data quality and screen out normal data. Most existing studies on data anomaly detection have focused on abnormal data with abnormal waveforms in time domain. Usually there are pseudo-normal data in the SHM system, which seems normal in time domain. However, the pseudo-normal data of bridge dynamic responses may cause wrong dynamic characteristics identification. In this study, the existing data anomaly detection was further expanded to data quality evaluation, and both obvious abnormal and pseudo-normal data are evaluated. A general data quality evaluation framework for dynamic response monitoring of long-span bridge structures was proposed. The time–frequency characteristics of monitoring data were obtained by continuous wavelet transform, and the data quality was classified and evaluated by constructing and training a convolutional neural network (CNN). The proposed framework was verified by using acceleration monitoring data of a cable-stayed bridge. The results reveal that this framework solves the problem that CNN cannot detect pseudo-normal data through time-domain characteristics, and improves the accuracy of data quality evaluation by using time–frequency information of the monitoring data. The acceleration monitoring data of a suspension bridge and a single pylon cable-stayed bridge were used to demonstrate the feasibility of the cross-object application of the proposed framework. The evaluation accuracy for the acceleration data quality of the suspension bridge exceeded 96%. After the reinforced training of a small number of pseudo-normal data samples, the evaluation accuracy for the acceleration data quality of the cables of the cable-stayed bridge reached 96.8%. The framework shows a good generalization capacity and robustness in cross-object applications.

Intelligent real-time identification technology of stratum characteristics during slurry TBM tunneling

The rapid and accurate identification of geological characteristics during TBM tunneling is a common concern in engineering. A set of real-time dynamic response monitoring and analysis systems was installed in the slurry TBM of a water delivery tunnel in Beijing to analyze the variation of geological characteristics during TBM tunneling. The response mechanism and time–frequency characteristics of slurry TBM acceleration in five strata were deeply studied. The variation trends of thrust, torque and acceleration response characteristic values when strata change were compared, and the results show that the acceleration response is extremely sensitive to strata change. An LSTM network was established that considers slurry TBM driving parameters and acceleration response characteristic values as input parameters and realizes the intelligent identification of five kinds of strata with an accuracy of 97.4% and an F1-Score of 96.38%.

Real-time monitoring of strain and modulus of asphalt pavement using built-in strain sensor cluster

Pavement health monitoring is helpful to understand the structural state of interlayer and make reasonable maintenance decisions. This study aims to propose a real-time strain and modulus monitoring method using built-in strain sensor cluster. First, the four-point bending beam test was conducted to demonstrate the possible poor deformation compatibility between a single built-in strain sensor with asphalt mixture under different temperature. Then, the potential mapping relationship between the output of the built-in strain sensor and the real strain of the matrix material was explored by mechanical derivation. Subsequently, the real-time strain and modulus monitoring method based on built-in strain sensor cluster was discussed and proposed. Finally, a three-dimensional finite element model was developed to validate the applicability of the proposed method to the dynamic response monitoring of elastic and viscoelastic pavement systems. The results indicate that the difference in modulus between the built-in strain sensor and the asphalt mixture causes the sensor output to deviate from the true value. The modulus ratio and strain ratio between the built-in strain sensor and the asphalt mixture satisfy the mapping relationship. The monitoring method based on the built-in strain sensor cluster can overcome the strain measurement errors caused by the poor deformation compatibility and also enables real-time monitoring of pavement modulus. In general, this work provides a new framework for real-time evaluation of strain and modulus in pavement health monitoring.

An Integrated GNSS/MEMS Accelerometer System for Dynamic Structural Response Monitoring under Thunder Loading

Dynamic response monitoring is of great significance for large engineering structural anomaly diagnosis and early warning. Although the global navigation satellite system (GNSS) has been widely used to measure the dynamic structural response, it has the limitation of a relatively low sampling rate. The micro-electro-mechanical system (MEMS) accelerometer has a high sampling frequency, but it belongs to the approaches of acceleration measurements as the absolute position is unavailable. Hence, in this paper, an integrated vibration monitoring system that includes a GNSS receiver and 3-axis MEMS accelerometers was developed to obtain the dynamic responses under the thunder loading. First, a new denoising algorithm for thunderstorm-induced vibration data was proposed based on variational mode decomposition (VMD) and the characteristics of white noise, and the low-frequency disturbance was separated from the GNSS displacement time series. Then, a power spectral density (PSD) analysis using data collected by the integrated system was carried out to extract low/high natural frequencies. Finally, field monitoring data collected at Huanghuacheng, Hefangkou, and Qilianguan in Beijing’s Huairou District were used to validate the effectiveness of the integrated system and processing scheme. According to the results, the proposed integrated GNSS/MEMS accelerometer system can not only be used to detect thunder loading events, but also completely extract the natural frequency based on PSD analysis. The high natural frequencies detected from the accelerometer data of the four Great Wall monitoring stations excited by the thunderstorms are 42.12 Hz, 12.94 Hz, 12.58 Hz, and 5.95 Hz, respectively, while the low natural frequencies detected from the GNSS are 0.02 Hz, 0.019 Hz, 0.016 Hz, and 0.014 Hz, respectively. Moreover, thunderstorms can cause the Great Wall to vibrate with a maximum displacement of 14.3 cm.

Distributed fiber mountain seismic monitoring and steady-state analysis under natural earthquakes.

Mountain dynamic response monitoring plays important roles in geological disaster evolution monitoring and warning. A distributed mountain seismic monitoring and steady-state analysis method is demonstrated with distributed acoustic sensing (DAS) and a natural earthquake stimulus. In the field test, the seismic detection capability is first verified by comparing the recorded seismic waveforms from DAS and existing seismic stations. The vibration signal difference between steady-state and unsteady-state mountain parts is apparent; the operational modal analysis method is utilized to extract the response difference and to monitor the disaster evolution process. The proposed method has many advantages, including being easy to deploy, all-weather online monitoring, etc. It is believed that the proposed method will broaden the DAS application scope and promote the development of geological disaster early warning such as landslides and collapses.

Theoretical analysis on the measurement accuracy of embedded strain sensor in asphalt pavement dynamic response monitoring based on FEM

Embedded strain sensors are the primary measurement device for strain in the tensile layer of asphalt pavement. The favorable deformation compatibility between embedded strain sensor and asphalt layer is the key to ensure the precise measurement of mechanical response. However, the good deformation coordination may be difficult to maintain under different environments due to the viscoelasticity of asphalt mixture. In this study, 4-point bending beam tests were performed to investigate deformation compatibility between embedded strain sensor and asphalt mixture under different temperature. Then, a quasi-static finite element model (FEM) was employed to simulate static mechanical response of asphalt pavement, and the design requirements for embedded strain sensor were proposed considering deformation coordination. In addition, the rationality of the design requirements of the sensor was further validated in the dynamic response monitoring. The results indicate that the deformation compatibility between embedded strain sensor and pavement material changes at different temperatures. In order to ensure favorable deformation compatibility, the reinforcement of the protective housing should be eliminated and the equivalent modulus (EM) of the sensitive element shall be the same as that of the asphalt mixture. Considering the viscoelasticity of asphalt mixture, the strain sensor with lower EM is recommended in the dynamic response monitoring of pavement structure. This study provides a basis for optimizing the embedded strain sensor of asphalt pavement from the perspective of deformation compatibility.

A distributed pavement monitoring system based on Internet of Things

Pavement is an important part of transportation infrastructure. In order to maintain pavement before the damage and improve the service quality, it is necessary to develop an intelligent and durable pavement information monitoring system. However, the pavement dynamic response monitoring is highly costly, easily obsolete and statistically redundant. The emergence of the Internet of Things (IoT) technology promises to change that. In this paper, an architecture of a distributed road IoT monitoring system is proposed, which has an acquisition layer, a preprocessing layer, a processing layer, an interaction layer, an energy layer and a network layer. Then, a prototype wireless pavement vibration monitoring system based on the IoT is developed, which consists of a number of wireless sensing nodes, a gateway, a remote server and a browser. Finally, data preprocessing, wireless communication, time synchronization, data processing and visualization, which represent the key to an effective system, are tested and discussed. The prototype wireless pavement vibration monitoring system provides a viable scheme for upgrading the IoT system and its application in the road infrastructures. In the future, any smart road will have an IoT wireless monitoring system to monitor the traffic, environment, and pavement information, which help enable traffic guidance, signal control, danger warning, scientific maintenance decision-making.

Theory and method of multi-point synchronous deformation and vibration measurement based on millimeter-wave sensing

Although accelerometer-, vision-, and laser-based sensing technologies are widely used in deformation and vibration measurements, the multi-point simultaneous deformation and vibration measurement of large-scale structures with high accuracy remains a challenge. Herein, we developed a novel technology for contactless deformation and vibration measurement using millimeter-wave (mmWave) linear frequency-modulated continuous wave radar, establishing the theory and method for multi-point simultaneous deformation and vibration measurement based on mmWave sensing. The principle of mmWave multi-point vibration measurement and a method of displacement extraction were systematically described using the baseband signal model of multi-target perception. We built a prototype of the proposed mmWave vibration measurement system and a platform for simulated vibration tests. The accuracy of the mmWave multi-point vibration measurement technology was verified and compared with that of laser displacement sensors. Using the prototype system, we conducted experiments on the multi-point synchronous vibration measurement and model identification of the slender hinged flexible rod structure of a certain aerospace equipment in China and then described the dynamic response monitoring of a large bridge structure. Results showed that the deformation and vibration measurement method based on mmWave sensing developed in this work could conveniently and accurately extract the time domain information of multi-target vibration displacements. Our work provides an innovative method and approach for non-contact multi-point synchronous deformation and vibration measurements that could be applied to the mechanical performance test and health monitoring of large structures.

Measurement of Dynamic Responses from Large Structural Tests by Analyzing Non-Synchronized Videos.

Image analysis techniques have been employed to measure displacements, deformation, crack propagation, and structural health monitoring. With the rapid development and wide application of digital imaging technology, consumer digital cameras are commonly used for making such measurements because of their satisfactory imaging resolution, video recording capability, and relatively low cost. However, three-dimensional dynamic response monitoring and measurement on large-scale structures pose challenges of camera calibration and synchronization to image analysis. Without satisfactory camera position and orientation obtained from calibration and well-synchronized imaging, significant errors would occur in the dynamic responses during image analysis and stereo triangulation. This paper introduces two camera calibration approaches that are suitable for large-scale structural experiments, as well as a synchronization method to estimate the time difference between two cameras and further minimize the error of stereo triangulation. Two structural experiments are used to verify the calibration approaches and the synchronization method to acquire dynamic responses. The results demonstrate the performance and accuracy improvement by using the proposed methods.

Porous CNT/rubber composite for resistive pressure sensor

In this study, a simple and effective method is developed to prepare porous conductive nanocomposite with great stability for pressure sensing applications. Fluorine rubber and single wall carbon nanotube (SWCNT) were mixed together to produce a pressure-sensitive rubber (PSR). The conductive filler, SWCNT, can result in better composite homogeneity during the manufacturing process of conductive PSR. We choose SWCNT because of its high aspect ratio, better conductivity and nearly ohmic property; therefore, better pressure/resistance sensitivity can be achieved. This conductive PSR showed resistance variation to compressive stresses and can be used to measure applied pressures with a sensitivity of 0.35 MPa−1. To enhance the sensitivity, foaming agent (N, N'-Dinitrosopentamethylenetetramine, DPT) was mixed with the PSR to create porous structures with controllable pore size (0.43–1.8 mm) by changing the foaming agent content. The porous PSR had a better deformability and thus the sensitivity increased to 4.31 MPa−1. The porous PSR exhibits response and recovery times about 0.25 s and 0.15 s, respectively. Great shape recovery and measurement stability of the porous PSR is also observed after more than 1000 compression/release cycles. The porous PSR can be easily assembled with printed circuits to provide quick and accurate measurements. Several examples, such as punch-force measurement on a boxing game glove and plantar pressure distributions, were also demonstrated to show the capability of the porous PSR for dynamic response monitoring applications.

Identification of structural dynamic characteristics based on machine vision technology

Asa convenient and effective tool for monitoring of the structural behaviors of civil infrastructure, the machine vision-based sensing technology integrated with digital image processing algorithm has achieved great progress in the field of structural health monitoring (SHM). The prominent advantages of this kind of measurement technology mainly include non-contact, long-distance and high-resolution. Up to now, various types of vision-based systems have been developed and applied in structural performance monitoring of engineering structures, however, seldom investigations are relevant to monitoring of structural dynamic characteristics. In this paper, the method for multi-point synchronous measurement of structural dynamic displacement is proposed. The structural modal parameters are identified using measured multi-point dynamic displacements and fast Fourier transform. A simple-supported rectangle steel beam model is established for conducting experiments to investigate (i) comparison study on the measurement results obtained by the vision-based system and the accelerometer, (ii) the effect of the measurement distance on the accuracy of the vision-based system, and (iii) the feasibility of different types of targets (LED lamp and black spot). The experimental results show that the proposed vision-based method is effective, accurate and stable for structural dynamic response monitoring and modal parameter identification.

A hybrid method of optimal sensor placement for dynamic response monitoring of hydro-structures

A hybrid method for optimal sensor placement is introduced to position detection sensors on hydro-structures to maximize the monitored structural dynamic information. In the hybrid method, modal assurance criterion matrices and effective independence vectors were applied as the optimization principle for adding and eliminating potential sensor locations in coordinate sets. The energy revision factor was implemented to measure the modal strain energy and ensure the arrangement of sensors at the large energy locations. QR decomposition of the modal matrix was employed to decrease the influence of the initial sensor positions. A computational simulation of an arch dam model, considering 20 sensors and the first six orders of modal vibrations, was used to demonstrate the feasibility of the method. The advantages and disadvantages of existing methods were demonstrated by comparison criteria including the modal assurance criterion, modal kinetic energy criterion, Fisher information matrix, and root-mean square error criterion. The results showed that the method proposed in this article provides linear independent and orthogonal modal vectors, minimizing the relative mean square error of the measured vibration modes, which fundamentally indicates that the identified vibration characteristics of the concrete arch dam are accurate and reasonable.

A novel procedure for failure criteria determination at solder joints under the board level drop test

Abstract Controlling and monitoring of dynamic responses are very important to ensure consistent test results and understand mechanical behaviors, as they are closely related to the solder joint failure mechanism. The failure of a solder joint during drop impact is induced by printed circuit board (PCB) bending. The failure criteria must be clear to determine the absolute impact life for direct comparison of drop test results. In this publication, a multi-channel real time electrical monitoring system is introduced, which can measure the dynamic voltage of daisy-chained solder joints in real-time during drop impact. A new failure criteria of board level drop test is developed, which takes the function of the component into account.

Autonomous Monitoring of Dynamic Response of In-Service Structures for Decision Support

AbstractThis paper describes instrumentation and autonomous, Web-enabled remote monitoring of in-service structures to resolve concerns. Structures were subject to dynamic excitation from blasting, construction equipment, and passing trains. An integrated approach to sensing, data acquisition, communication, data aggregation, and display was developed and successfully applied to structures ranging from bridges to homes. Challenges encountered and best practices developed over many multiyear continuous remote monitoring deployments are discussed. Deployment of monitoring and communication hardware and software and development of robust, autonomous, data aggregation, dissemination, and interpretation strategies are emphasized. Three selected case studies provide context and demonstrate applications of field monitoring to real-world situations on in-service structures. Autonomously acquired data were used to allay fears of construction vibration-related damage to a historic building, possible loss of capacit...

A modal approach for dynamic response monitoring from experimental data

The objective of this paper is the definition and verification of an iterative procedure for the detailed monitoring of the dynamic response of a structural system based on the experimental modal model of the system on ground and a limited number of measurements in the operating condition. The method is formulated starting from a linear model, but it can be applied to weakly non-linear system, because of the iterative nature of the algorithm. It does not require the definition of a numerical model, but an experimental representation in the modal coordinates, achievable with a preliminary modal survey with an arbitrary large amount of experimental points. The proposed method is presented as well as its implementation and several numerical test cases in order to validate its formulation. Experimental analyses are performed on a uniform beam and on a full-scale aeronautical composite component with promising results.

Load and Response Identification for a Nonlinear Flexible Structure Subject to Harmonic Loads

Experimental monitoring of dynamic response is generally limited to few locations in the system. However, the analysis of structural performance and design of control systems would benefit from a complete knowledge of the system dynamic during service. A numerical approach is developed to numerically reconstruct the load and response of a complete structure from few reference points, based on a modal approach for projecting the response at few points on the domain of the structure. This methodology is particularly advantageous when full-field monitoring of a structure is not a possible solution. An assembly of two beams joined by a nonlinear torsional spring is analyzed in case of different load distributions acting on its span. The approach is shown to be robust and reliable.

Structural health monitoring of the Tamar suspension bridge

This paper presents experiences and lessons from the structural health monitoring practice on the Tamar Bridge in Plymouth, UK, a 335-m span suspension bridge opened in 1961. After 40 years of operations, the bridge was strengthened and widened in 2001 to meet a European Union Directive to carry heavy goods vehicles up to 40 tonnes by a process in which additional stay cables and cantilever decks were added and the composite deck was replaced with a lightweight orthotropic steel deck. At that time, a structural monitoring system comprising wind, temperature, cable tension and deck level sensors was installed to monitor the bridge behaviour during and after the upgrading. In 2006 and 2009, respectively, a dynamic response monitoring system with real-time modal parameter identification and a robotic total station were added to provide a more complete picture of the bridge behaviour, and in 2006 a one-day ambient vibration survey of the bridge was carried out to characterize low-frequency vibration modes of the suspended structure. Practical aspects of the instrumentation, data processing and data management are discussed, and some key response observations are presented. The bridge is a surprisingly complex structure with a number of inter-linked load–response mechanisms evident, all of which have to be characterized as part of a long-term structural health monitoring exercise. Structural temperature leading to thermal expansion of the deck, main cables and additional stays is a major factor on global deformation, whereas vehicle loading and wind are usually secondary factors. Dynamic response levels and modal parameters show apparently complex relationships among themselves and with the quasi-static load and response. As well as the challenges of fusing and managing data from three distinct but parallel monitoring systems, there is a significant challenge in interpreting the load and response data firstly to diagnose the normal service behaviour and secondly to identify performance anomalies. Copyright © 2012 John Wiley & Sons, Ltd.

Structural Dynamic Response Monitoring of Power Transmission Tower

In order to study the dynamic response of power transmission lines under mechanical fault, the structural dynamic response monitoring indexes based on the requirement of field measurement were determined according to the structural characteristics of steel towers. The monitoring program was put forward in terms of the monitoring principle and basis of the sensors. The vibration characteristic, dynamic alignment and stress/strain are chosen to be the monitoring indexes. Considering the synchronization function of GPS system, the three monitoring indexes of the large span high voltage tower can be simultaneously monitored by using vibration sensor, GPS and strain sensor. The monitoring scheme can provide the theoretical base for the establishment of early warning system and the collection of dynamic response of steel tower during line break or tower collapse.