Special Issue "Vibration-Based Structural Health Monitoring"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 29 March 2020.

Special Issue Editor

Prof. Dr. Junhong Park
E-Mail Website
Guest Editor
School of Mechanical Engineering, Hanyang University, 222 Wangsimni-ro Seoul, Korea
Interests: engineering acoustics; noise and vibration; structural health monitoring; signal processing

Special Issue Information

As structures become more complex, the need for structural health monitoring is increasing in many applications. Vibration occurs from wide different sources including internal and external excitations and other sources in the surrounding environments. The use of vibration for structural integrity monitoring allows robust, efficient, and straightforward implementation. The utilization of vibration for inspection requires the contribution and understanding of multidisciplinary research fields. Due to various aspects of a vibrating system, the vibration-based approach requires investigations from many different fields including applied mechanics, solid mechanics, fluid mechanics, acoustics, signal processing, electronics, material science, etc.

Prof. Junhong Park
Guest Editor

Manuscript Submission Information

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Keywords

  • Audio signal processing
  • Modeling and simulation of vibration
  • Theoretical and experimental investigations of vibration generation and transfer
  • Experimental modal analysis for vibration characterization
  • Structural acoustics
  • Vibration analysis of infrastructures
  • Optimization for structural health monitoring
  • Ambient excitations and resulting vibrations
  • Excitations from moving loads
  • AI-based understanding of vibration characteristics
  • AI-assisted feature extractions and condition monitoring
  • IoT for structural health monitoring

Published Papers (15 papers)

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Open AccessArticle
Investigation of a Bragg Grating-Based Fabry–Perot Structure Inscribed Using Femtosecond Laser Micromachining in an Adiabatic Fiber Taper
Appl. Sci. 2020, 10(3), 1069; https://doi.org/10.3390/app10031069 - 05 Feb 2020
Abstract
This paper presents the fabrication of a fiber Bragg grating (FBG)-based Fabry–Perot (FP) structure (7 mm total length) in an adiabatic fiber taper, investigates its strain and temperature characteristics, and compares the sensing characteristics with a standard polyimide coated FBG sensor. Firstly, a [...] Read more.
This paper presents the fabrication of a fiber Bragg grating (FBG)-based Fabry–Perot (FP) structure (7 mm total length) in an adiabatic fiber taper, investigates its strain and temperature characteristics, and compares the sensing characteristics with a standard polyimide coated FBG sensor. Firstly, a simulation of the said structure is presented, followed by the fabrication of an adiabatic fiber taper having the outer diameter reduced to 70 μ m (core diameter to 4.7 μ m). Next, the sensing structure, composed of two identical uniform FBG spaced apart by a small gap, is directly inscribed point-by-point using infrared femtosecond laser (fs-laser) micromachining. Lastly, the strain and temperature behavior for a range up to 3400 μ ε and 225 ° C, respectively, are investigated for the fabricated sensor and the FBG, and compared. The fabricated sensor attains a higher strain sensitivity (2.32 pm/ μ ε ) than the FBG (0.73 pm/ μ ε ), while both the sensors experience similar sensitivity to temperature (8.85 pm/ ° C). The potential applications of such sensors include continuous health monitoring where precise strain detection is required. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Vibration Feature Analysis for Gas-Insulated Switchgear Mechanical Fault Detection under Varying Current
Appl. Sci. 2020, 10(3), 944; https://doi.org/10.3390/app10030944 - 01 Feb 2020
Abstract
As a key component to ensure the safe operation of the power grid, mechanical defect diagnosis technology of gas-insulated switchgear (GIS) during operation is often neglected. At present, GIS mechanical fault detection based on vibration information has not been developed. The main reason [...] Read more.
As a key component to ensure the safe operation of the power grid, mechanical defect diagnosis technology of gas-insulated switchgear (GIS) during operation is often neglected. At present, GIS mechanical fault detection based on vibration information has not been developed. The main reason is that the excitation current is considerable but uncontrollable in the actual operation of GIS. It is difficult to eliminate the influence of excitation on the vibration amplitude and form an effective vibration feature description technology. Therefore, this paper proposes a unified feature-extraction method for GIS vibration information that reduces the influence of current amplitude for mechanical fault diagnosis. Starting from the GIS mechanical analysis, the periodicity of vibration excitation and the influence of amplitude are discussed. Then, combined with the non-linear characteristics of GIS systems and non-linear vibration theory, the multiplier frequency energy ratio (MFER) is designed to extract vibration-unified features of GIS for diagnosing the mechanical fault under different current levels. The diagnosis results of the experimental data with different feature-extraction methods show the applicability and superiority of the proposed method in the GIS’s mechanical fault-detection field based on vibration information. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Regularization-Based Dual Adaptive Kalman Filter for Identification of Sudden Structural Damage Using Sparse Measurements
Appl. Sci. 2020, 10(3), 850; https://doi.org/10.3390/app10030850 - 25 Jan 2020
Abstract
This paper proposes a dual adaptive Kalman filter to identify parameters of a dynamic system that may experience sudden damage by a dynamic excitation such as earthquake ground motion. While various filter techniques have been utilized to estimate system’s states, parameters, input (force), [...] Read more.
This paper proposes a dual adaptive Kalman filter to identify parameters of a dynamic system that may experience sudden damage by a dynamic excitation such as earthquake ground motion. While various filter techniques have been utilized to estimate system’s states, parameters, input (force), or their combinations, the filter proposed in this paper focuses on tracking parameters that may change suddenly using sparse measurements. First, an advanced state-space model of parameter estimation employing a regularization technique is developed to overcome the lack of information in sparse measurements. To avoid inaccurate or biased estimation by conventional filters that use covariance matrices representing time-invariant artificial noises, this paper proposes a dual adaptive filtering, whose slave filter corrects the covariance of the artificial measurement noises in the master filter at every time-step. Since it is generally impossible to tune the proposed dual filter due to sensitivity with respect to parameters selected to describe artificial noises, particle swarm optimization (PSO) is adopted to facilitate optimal performance. Numerical investigations confirm the validity of the proposed method through comparison with other filters and emphasize the need for a thorough tuning process. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Integration of Refined Composite Multiscale Cross-Sample Entropy and Backpropagation Neural Networks for Structural Health Monitoring
Appl. Sci. 2020, 10(3), 839; https://doi.org/10.3390/app10030839 - 24 Jan 2020
Abstract
This study developed a structural health monitoring (SHM) system based on refined composite multiscale cross-sample entropy (RCMCSE) and an artificial neural network for monitoring structures under ambient vibrations. RCMCSE was applied to enhance the reliability of entropy estimations. First, RCMCSE was implemented to [...] Read more.
This study developed a structural health monitoring (SHM) system based on refined composite multiscale cross-sample entropy (RCMCSE) and an artificial neural network for monitoring structures under ambient vibrations. RCMCSE was applied to enhance the reliability of entropy estimations. First, RCMCSE was implemented to extract damage features, and finite element analysis software was then used to generate training samples, which included stiffness reductions to achieve various damage patterns. A neural network model was constructed and trained using entropy values for these damage patterns. An experiment was conducted on a seven-story steel benchmark structure to validate the performance of the proposed system. Additionally, a confusion matrix was established to evaluate the performance of the proposed system. The results obtained for a scaled-down benchmark structure indicated that 89.8% of the floors were accurately classified, and 90% of the practical damaged floors were correctly diagnosed. The performance evaluation demonstrated that the proposed SHM system exhibited increased damage location accuracy. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Determination of Clamping Force Using Bolt Vibration Responses during the Tightening Process
Appl. Sci. 2019, 9(24), 5379; https://doi.org/10.3390/app9245379 - 09 Dec 2019
Abstract
This paper presents a novel method to measure clamping force by using the vibration of bolts. The resonance frequency of the bolt increases in line with the clamping force during the tightening process. These characteristics were measured and utilized in the k-means clustering [...] Read more.
This paper presents a novel method to measure clamping force by using the vibration of bolts. The resonance frequency of the bolt increases in line with the clamping force during the tightening process. These characteristics were measured and utilized in the k-means clustering algorithm. Bolt specimens were fastened to the load cell using a nutrunner for verification of the proposed method. The precisely measured clamping force was labeled. The labeled data was used to predict the clamping force from the vibration responses. To use the proposed method in assembly of actual parts, an accelerometer was attached to the nutrunner for vibration measurements. This enabled continuous monitoring of the clamping force without influence on the parts. The estimated clamping force was compared with those from the torque method. When the vibration of a bolt was transmitted through the nutrunner, loss of high-frequency vibration energy occurred. The resonant frequency band vibrations of the bolt were preserved to determine the fastening force. The components in the low frequency band were excluded using a band-pass filter. The clamping force of the bolt used in the vehicle’s lower arm and the link was also evaluated precisely. By using the proposed method, it is possible to continuously monitor variations of the clamping force during the manufacturing process. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Frequency Response Analysis of Perforated Shells with Uncertain Materials and Damage
Appl. Sci. 2019, 9(24), 5299; https://doi.org/10.3390/app9245299 - 05 Dec 2019
Abstract
In this paper, we give an overview of the issues one must consider when designing methods for vibration based health monitoring systems for perforated thin shells especially in relation to frequency response analysis. In particular, we allow either the material parameters or the [...] Read more.
In this paper, we give an overview of the issues one must consider when designing methods for vibration based health monitoring systems for perforated thin shells especially in relation to frequency response analysis. In particular, we allow either the material parameters or the structure or both to be random. The numerical experiments are computed using the standard high order finite element method with stochastic collocation for the cases with random material and Monte Carlo for those with damaged or random structures. The results display a wide range of responses over the experimental configurations. In perforated shell structures, the internal boundary layers can play an important role especially when damage is allowed within the penetration patterns. The computational methodology advocated here can be used to build statistical databases that are necessary for development of probabilistic damage identification methods. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Damage Detection Using Modal Rotational Mode Shapes Obtained with a Uniform Rate CSLDV Measurement
Appl. Sci. 2019, 9(23), 4982; https://doi.org/10.3390/app9234982 - 20 Nov 2019
Abstract
With the rapid development of a continuously scanning laser Doppler vibrometer (CSLDV) technique, the full-field mode shapes of structures with high accuracy can be obtained. In this paper, a novel damage detection method using modal rotational mode shapes obtained with a uniform rate [...] Read more.
With the rapid development of a continuously scanning laser Doppler vibrometer (CSLDV) technique, the full-field mode shapes of structures with high accuracy can be obtained. In this paper, a novel damage detection method using modal rotational mode shapes obtained with a uniform rate CSLDV measurement is proposed. The modal rotational damage indicators considering the changes of modal rotational mode shapes between the damaged and the undamaged states are established. Because the modal rotational mode shapes are obtained through the derivative of the detailed displacement mode shapes of transitional degree-of-freedoms (DOFs) with respect to the orthogonal directions, they are more sensitive than the normal displacement mode shapes. The uniform rate CSLDV measurement is essentially a uniform straight-line scanning technique and the measured mode shapes can be directly obtained through the demodulation of vibration signals. Besides, taking it for granted that a priori knowledge of the undamaged structure is not known, the undamaged mode shapes can be reconstructed from the measured damaged data using the fitted polynomial functions in which the minimum number of polynomial function coefficients are determined by a fit value threshold. The proposed method is firstly demonstrated by numerical simulation of the crack plate and then a plate structure with three damaged cases is taken as an example for further experimental study. The experimental results indicate the following: (1) The uniform rate CSLDV measurement can obtain the high accuracy modal rotational mode shapes with the advantage of eliminating the contaminated noise in the measurement; (2) the modal rotational damage indicators of the torsional modes are the most sensitive to the crack damage and they can clearly identify single, multiple damages and locations of the plate, and even slight crack damage, respectively. The effectiveness of the method paves the way for practical applications, such as ultra-light or composite structures. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Experimental Validation of Optimal Parameter and Uncertainty Estimation for Structural Systems Using a Shuffled Complex Evolution Metropolis Algorithm
Appl. Sci. 2019, 9(22), 4959; https://doi.org/10.3390/app9224959 - 18 Nov 2019
Abstract
The uncertainty in parameter estimation arises from structural systems’ input and output measured errors and from structural model errors. An experimental verification of the shuffled complex evolution metropolis algorithm (SCEM-UA) for identifying the optimal parameters of structural systems and estimating their uncertainty is [...] Read more.
The uncertainty in parameter estimation arises from structural systems’ input and output measured errors and from structural model errors. An experimental verification of the shuffled complex evolution metropolis algorithm (SCEM-UA) for identifying the optimal parameters of structural systems and estimating their uncertainty is presented. First, the estimation framework is theoretically developed. The SCEM-UA algorithm is employed to search through feasible parameters’ space and to infer the posterior distribution of the parameters automatically. The resulting posterior parameter distribution then provides the most likely estimation of parameter sets that produces the best model performance. The algorithm is subsequently validated through both numerical simulation and shaking table experiment for estimating the parameters of structural systems considering the uncertainty of available information. Finally, the proposed algorithm is extended to identify the uncertain physical parameters of a nonlinear structural system with a particle mass tuned damper (PTMD). The results demonstrate that the proposed algorithm can effectively estimate parameters with uncertainty for nonlinear structural systems, and it has a stronger anti-noise capability. Notably, the SCEM-UA method not only shows better global optimization capability compared with other heuristic optimization methods, but it also has the ability to simultaneously estimate the uncertainties associated with the posterior distributions of the structural parameters within a single optimization run. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Gradient Descent-Based Optimization Method of a Four-Bar Mechanism Using Fully Cartesian Coordinates
Appl. Sci. 2019, 9(19), 4115; https://doi.org/10.3390/app9194115 - 01 Oct 2019
Abstract
Machine vibrations often occur due to dynamic unbalance inducing wear, fatigue, and noise that limit the potential of many machines. Dynamic balancing is a main concern in mechanism and machine theory as it allows designers to limit the transmission of vibrations to the [...] Read more.
Machine vibrations often occur due to dynamic unbalance inducing wear, fatigue, and noise that limit the potential of many machines. Dynamic balancing is a main concern in mechanism and machine theory as it allows designers to limit the transmission of vibrations to the frames and base of machines. This work introduces a novel method for representing a four-bar mechanism with the use of Fully Cartesian coordinates and a simple definition of the shaking force (ShF) and the shaking moment (ShM) equations. A simplified version of Projected Gradient Descent is used to minimize the ShF and ShM functions with the aim of balancing the system. The multi-objective optimization problem was solved using a linear combination of the objectives. A comprehensive analysis of the partial derivatives, volumes, and relations between area and thickness of the counterweights is used to define whether the allowed optimization boundaries should be changed in case the mechanical conditions of the mechanism permit it. A comparison between Pareto fronts is used to determine the impact that each counterweight has on the mechanism’s balancing. In this way, it is possible to determine which counterweights can be eliminated according to the importance of the static balance (ShF), dynamic balance (ShM), or both. The results of this methodology when using three counterweights reduces the ShF and ShM by 99.70% and 28.69%, respectively when importance is given to the static balancing and by 83.99% and 8.47%, respectively, when importance is focused on dynamic balancing. Even when further reducing the number of counterweights, the ShF and ShM can be decreased satisfactorily. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Damping Assessment of Lightweight Timber Floors Under Human Walking Excitations
Appl. Sci. 2019, 9(18), 3759; https://doi.org/10.3390/app9183759 - 09 Sep 2019
Abstract
Vibrations on timber floors are among the most common serviceability problems in social housing projects. The presence of low damping levels on these floors could cause excessive vibrations in a range of frequency and amplitude that generate discomfort in users. This study focuses [...] Read more.
Vibrations on timber floors are among the most common serviceability problems in social housing projects. The presence of low damping levels on these floors could cause excessive vibrations in a range of frequency and amplitude that generate discomfort in users. This study focuses on the influence of the damping ratio in the dynamic serviceability of social housing timber floors due to walking excitations. More than 60 human-walking vibration tests were conducted on both laboratory and in-situ timber floors. The floors were instrumented with accelerometers, and fundamental modal damping ratios were estimated by applying Enhanced Frequency Decomposition Domain (EFDD) and Subspace Stochastic Identification (SSI) methods. The vibration dose value (VDV) was used to estimate the dynamic serviceability of floors. The results indicated that timber floors had an impulsive-type vibration response, with fundamental damping ratios between 1.9% and 14.8%, depending on their constructive characteristics. The in-situ floors had damping ratios between two to three times greater than the laboratory floors due to the presence of non-structural elements. Finally, it was possible to demonstrate that the floors with the highest damping ratios reached lower vibration dose values and, therefore, a better dynamic serviceability performance. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
A Kriging Surrogate Model for the Interference Reduction in the Settlement Surveillance Sensors of Steel Transmission Towers
Appl. Sci. 2019, 9(16), 3343; https://doi.org/10.3390/app9163343 - 14 Aug 2019
Abstract
The utilization of modal frequency sensors is a feasible and effective way to monitor the settlement problem of the transmission tower foundation. However, the uncertainties and interference in the real operation environment of transmission towers highly affect the accuracy and identification of modal [...] Read more.
The utilization of modal frequency sensors is a feasible and effective way to monitor the settlement problem of the transmission tower foundation. However, the uncertainties and interference in the real operation environment of transmission towers highly affect the accuracy and identification of modal frequency sensors. In order to reduce the interference of modal frequency sensors for transmission towers, a Kriging surrogate model is proposed in this study. The finite element model of typical transmission towers is created and validated to provide the effective original database for the Kriging surrogate model. The prediction accuracy and convergences of the Kriging surrogate model are measured and confirmed. Besides the merits in computational cost and high-efficiency, the Kriging surrogate model is proven to have a satisfied and robust interference reduction capacity. Therefore, the Kriging surrogate model is feasible and competitive for interference filtration in the settlement surveillance sensors of steel transmission towers. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Condition Monitoring of Railway Tracks from Car-Body Vibration Using a Machine Learning Technique
Appl. Sci. 2019, 9(13), 2734; https://doi.org/10.3390/app9132734 - 05 Jul 2019
Cited by 1
Abstract
A track condition monitoring system that uses a compact on-board sensing device has been developed and applied for track condition monitoring of regional railway lines in Japan. Monitoring examples show that the system is effective for regional railway operators. A classifier for track [...] Read more.
A track condition monitoring system that uses a compact on-board sensing device has been developed and applied for track condition monitoring of regional railway lines in Japan. Monitoring examples show that the system is effective for regional railway operators. A classifier for track faults has been developed to detect track fault automatically. Simulation studies using SIMPACK and field tests were carried out to detect and isolate the track faults from car-body vibration. The results show that the feature of track faults is extracted from car-body vibration and classified from proposed feature space using machine learning techniques. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Simple Degree-of-Freedom Modeling of the Random Fluctuation Arising in Human–Bicycle Balance
Appl. Sci. 2019, 9(10), 2154; https://doi.org/10.3390/app9102154 - 27 May 2019
Abstract
In this study, we propose a new simple degree-of-freedom fluctuation model that accurately reproduces the probability density functions (PDFs) of human–bicycle balance motions as simply as possible. First, we measure the time series of the roll angular displacement and velocity of human–bicycle balance [...] Read more.
In this study, we propose a new simple degree-of-freedom fluctuation model that accurately reproduces the probability density functions (PDFs) of human–bicycle balance motions as simply as possible. First, we measure the time series of the roll angular displacement and velocity of human–bicycle balance motions and construct their PDFs. Next, using these PDFs as training data, we identify the model parameters by means of particle swarm optimization; in particular, we minimize the Kolmogorov–Smirnov distance between the human PDFs from the participants and the PDFs simulated by our model. The resulting PDF fitnesses were over 98.7 % for all participants, indicating that our simulated PDFs were in close agreement with human PDFs. Furthermore, the Kolmogorov–Smirnov statistical hypothesis testing was applied to the resulting human–bicycle fluctuation model, showing that the measured time responses were much better supported by our model than the Gaussian distribution. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessArticle
Reliability of Field Experiments, Analytical Methods and Pedestrian’s Perception Scales for the Vibration Serviceability Assessment of an In-Service Glass Walkway
Appl. Sci. 2019, 9(9), 1936; https://doi.org/10.3390/app9091936 - 11 May 2019
Cited by 7Correction
Abstract
The vibration performance of pedestrian structures attracts the attention of several studies, especially with respect to unfavorable operational conditions or possible damage scenarios. Given a pedestrian system, specific vibration comfort levels must be satisfied in addition to basic safety requirements, depending on the [...] Read more.
The vibration performance of pedestrian structures attracts the attention of several studies, especially with respect to unfavorable operational conditions or possible damage scenarios. Given a pedestrian system, specific vibration comfort levels must be satisfied in addition to basic safety requirements, depending on the class of use, the structural typology and the materials. To this aim, guideline documents of the literature offer simplified single-degree-of-freedom (SDOF) approaches to estimate the maximum expected vibrations and to verify the required comfort limits. Most of these documents, however, are specifically calibrated for specific scenarios/structural typologies. Dedicated methods of design and analysis, in this regard, may be required for structural glass pedestrian systems, due to their intrinsic features (small thickness-to-size ratios, high flexibility, type and number of supports, live-to-dead load ratios, use of materials that are susceptible to mechanical degradation with time/temperature/humidity, etc.). Careful consideration could be then needed not only at the design stage, but also during the service life of a given glass walkway. In this paper, the dynamic performance of an in-service glass walkway is taken into account and explored via field vibration experiments. A set of walking configurations of technical interest is considered, involving 20 volunteers and several movement features. The vibration comfort of the structure is then assessed based on experimental estimates and existing guideline documents. The intrinsic uncertainties and limits of simplified approaches of literature are discussed, with respect to the performance of the examined glass walkway. In conclusion, the test predictions are also used to derive “perception index” data and scales that could support a reliable vibration comfort assessment of in-service pedestrian glass structures. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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Open AccessCorrection
Correction: Bedon, C.; Fasan, M. Reliability of Field Experiments, Analytical Methods and Pedestrian’s Perception Scales for the Vibration Serviceability Assessment of an In-Service Glass Walkway. Appl. Sci. 2019, 9, 1936
Appl. Sci. 2020, 10(3), 1032; https://doi.org/10.3390/app10031032 - 04 Feb 2020
Abstract
We, the authors, wish to make the following corrections to our paper [...] Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring)
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