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Structural Health Monitoring - Science topic

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Are there any notable conferences focused on Structural Health Monitoring (SHM)? I'm looking for good opportunities to publish my work nearby (published soon). Any recommendations?
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Mahadev Sudin thanks for answering, it is a workshop not a conference.
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Fiber optic sensors play a transformative role in structural health monitoring (SHM) because of their advanced and meaningful features tailored to complex infrastructure needs. These sensors offer exceptional sensitivity and the ability to measure key parameters like strain, temperature, and vibration with high precision.
It has been proven that fiber optic sensors outperform traditional sensors in structural health monitoring (SHM) due to their high sensitivity, resistance to electromagnetic interference, and ability to provide accurate, real-time data over long distances. These advantages make them reliable and efficient for monitoring large-scale infrastructure, even in harsh environments.
Unlike traditional sensors, they are immune to electromagnetic interference, ensuring accurate and consistent performance even in challenging conditions.
Furthermore, their lightweight and compact design allows seamless integration into structures, while their capability for long-distance data transmission without signal loss supports real-time monitoring of large-scale systems.
The durability, resistance to harsh environmental factors, and low maintenance requirements of fiber optic sensors provide a long-term, reliable solution for infrastructure health assessments.
The question is why are these advanced capabilities of fiber optic sensors preferred over traditional technologies in SHM for large-scale civil infrastructure?
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Fibre-optic sensors can be used in harsh conditions such as relatively high temperatures, high voltage, or corrosive materials due to their dielectric property; additionally, they can perform remote sensing
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Dear Researcher,
I hope this message finds you well. My professor and I are looking for a skilled and advanced programmer proficient in Python and MATLAB to join our research group. Our focus is on publishing high-quality, Q1 papers in the field of Artificial Intelligence-based Structural Health Monitoring in Civil Engineering.
The ideal candidate should have expertise in:
  • Deep Learning and Machine Learning
  • Signal and Image Processing
  • Optimization Algorithms
  • Coding and Programming with Python/MATLAB
If you are passionate about research, enjoy publishing, and have sufficient time to dedicate to our projects, we would be delighted to invite you to join us.
Please send your CV to hosein_saffaryosefi@alumni.iust.ac.ir .
Best regards, Hossein Safar Yousefifard School of Civil Engineering Iran University of Science and Technology
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Hossein Safar Yousefifard I have attached my resume below for your review. Please let me know if you need any additional information. Thank you....
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In structural health monitoring systems, such as bridge health monitoring systems, are there other data types besides time series data? What are the main nature of these data? What exactly is static data and dynamic data, and what is the difference? What are the widely used methods for monitoring data anomaly detection? Are traditional statistical probability methods (statistical-based, distance-based, density-based, cluster-based, etc.) applied to anomaly detection in structural monitoring data?
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In structural health monitoring systems, there can be various types of data collected in addition to time series data. Some examples of other data types include:
  1. Image data: Images of the structure can be captured using various techniques such as cameras, lidar, or drones. These images can be used to identify cracks, deformations, or other visible signs of damage.
  2. Vibration data: Vibration sensors can be used to measure the dynamic response of the structure to external stimuli such as wind, traffic, or earthquakes.
  3. Environmental data: Environmental sensors can be used to measure the temperature, humidity, and other environmental conditions that can affect the health of the structure.
Static data refers to data that does not change over time, such as the dimensions and material properties of the structure. Dynamic data, on the other hand, refers to data that changes over time, such as the response of the structure to external stimuli.
Anomaly detection methods can be broadly classified into statistical, machine learning, and hybrid approaches. Traditional statistical probability methods such as statistical-based, distance-based, density-based, and cluster-based methods can be used for anomaly detection in structural monitoring data.
Statistical-based methods involve the calculation of statistical parameters such as mean, standard deviation, and correlation coefficients to detect anomalies in the data. Distance-based methods use distance measures such as Euclidean distance or Mahalanobis distance to identify outliers in the data. Density-based methods use density estimates to identify regions of the data that are sparsely populated and thus likely to contain anomalies. Cluster-based methods involve clustering the data into groups and identifying outliers in each cluster.
In addition to these traditional methods, machine learning algorithms such as neural networks, support vector machines, and decision trees can also be used for anomaly detection in structural monitoring data. Hybrid approaches that combine statistical and machine learning methods can also be used for improved anomaly detection performance.
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Most of the codes in the examples in the literature are presented for discrete variables. While the main challenge in solving Bayesian networks is the use of continuous variables. Marco's chain will be used in probability inference in the solution process. Also, this network includes predicting procedures and updating processes using observations
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Here is an answer produced by ChatGPT...
Maybe it helps you:
ChatGPT answer:
There are several libraries in both MATLAB and Python that can be used to solve Continuous Bayesian Networks (CBNs). One such library is the pyMC3 package in Python, which is a probabilistic programming library that supports continuous variables.
Here is an example of how to use pyMC3 to create a simple CBN and perform model updating based on observations:
Python code:
import pymc3 as pm
import numpy as np
# Define the CBN using a graphical model
with pm.Model() as model:
# Define prior distributions for the variables
mean = pm.Normal('mean', mu=0, sigma=1)
std = pm.HalfNormal('std', sigma=1)
x = pm.Normal('x', mu=mean, sigma=std)
# Define the likelihood based on observations
obs = pm.Normal('obs', mu=x, sigma=0.1, observed=np.array([1, 2, 3]))
# Perform model inference
trace = pm.sample(1000)
In this example, we create a CBN with one continuous variable, x, which is assumed to be normally distributed with mean mean and standard deviation std. We then define the likelihood function using the observed data obs. Finally, we use the sample function to perform Markov Chain Monte Carlo (MCMC) inference and obtain posterior samples for the variables.
Similarly, in MATLAB, you can use the BayesNet toolbox to construct and solve CBNs. Here is an example code to create a CBN and perform model updating based on observations:
Matlab Code:
% Define the CBN using a graphical model
dag = zeros(2);
dag(1,2) = 1;
node_sizes = [1 1];
bnet = mk_bnet(dag, node_sizes);
% Define the prior distributions for the variables
bnet.CPD{1} = gaussian_CPD(bnet, 1, 'mean', 0, 'cov', 1);
bnet.CPD{2} = gaussian_CPD(bnet, 2, 'mean', 0, 'cov', 1);
% Generate some data from the prior distributions
data = cell(1, 2);
data{1} = randn(1000, 1);
data{2} = randn(1000, 1);
% Perform model inference
engine = jtree_inf_engine(bnet);
[engine, loglik] = enter_evidence(engine, data);
marginals = marginal_nodes(engine, 2);
% Update the model based on observations
data{2} = [1; 2; 3];
[engine, loglik] = enter_evidence(engine, data);
marginals = marginal_nodes(engine, 2);
In this example, we create a CBN with two variables, where the second variable is a function of the first variable. We define the prior distributions for the variables using the gaussian_CPD function. We then generate some data from the prior distributions and use the jtree_inf_engine function to perform inference and obtain the marginal distribution of the second variable. Finally, we update the model based on some observations and perform inference again to obtain the updated marginal distribution of the second variable.
Note that these are just simple examples and CBNs can be much more complex with many variables and dependencies. The choice of library and specific implementation may depend on the complexity of the model and the specific requirements of the problem at hand.
Regenerate response.
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Hello Everyone,
What kind of strain gauge is optimal for a bridge subject to fatigue loads? I'm conducting my PhD dissertation and wanted to know. To purchase the sensors, I need particular technical information. Could someone offer assistance with this? I appreciate any help/suggestion.
Kind Regards
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I agree with all the above answeres. From my experience, VWSGs are time taking, and not good for transient or dynamic loads. This is for any kind of gauges, say, embedded, welded to rebar, or other means to transfer the strain from body of material to the gauge. Yes, data loggers are monopoly of manufacturers and quite expensive. But they are reliable and robus. Fiber Optic sensors are new and can give better resolution and least count. I suggest, to have first hand approximate analysis to assess the level of strain expected. Then, suitable gauge within the range can be decided. Without this, entire data logging exercise may go futile. So, one should be careful on this aspect.
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i newly started my phd in structural health monitoring and need to understand some basic terms.
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It would help if you show what you measure. I cant see any meaning to the y-axis on the right as a «system order». The height of the peaks is a measure of the modal mass and damping of your measured object.
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I would like to know that ultrasonic structural health monitoring has been developed for many years. At present, in which fields has it been maturely applied? Which companies have launched corresponding products? Now I have read a lot of relevant papers, but I think this direction is still in the stage of laboratory research, and there are many problems to be solved in practical application. What is the research significance of this direction for the industry?
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Boeing has installed patch-type pzt sensors to monitor fatigue failure of the aircraft wing structure. It is not for a long range inspection but a short range inspection where sensors are installed in close proximity to the structurally vulnerable spots. "Long range inspection using guided waves blah blah...", these are all lies to publish papers. Watch out!
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What are your suggestions for innovative application and development in the field of Reliability-Based Design Optimization?
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Solution development based on proven technologies.
What are these proof-values: Reliability, ROI, TCO, ease of use.
How to check what's best: Monitoring, Predictive Measurement and Analytics, etc.
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I‘m doing some research about time-varying cable forces. I need some data about cable vibration. Where can I find the data about cable vibration ?
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Kindly for datasets check these resources:
Kaggle
Google Dataset Search
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I'm studying optimal placement of sensors in larger structures. Some metrics can be found like fisher information matrix, kinetic energy, effective independence, MAC, etc. But in your opinion and knowledge, which ones are the best?
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Dear Dr Joao Luiz Junho Pereira,
I invite you to read these articles:
A novel load-dependent sensor placement method for model updating based on time-dependent reliability optimization considering multi-source uncertainties
An adaptive sensor placement algorithm for structural health monitoring based on multi-objective iterative optimization using weight factor updating
Strategy for sensor number determination and placement optimization with incomplete information based on interval possibility model and clustering avoidance distribution index
Sensor placement algorithm for structural health monitoring with redundancy elimination model based on sub-clustering strategy
Sensor placement for structural health monitoring using hybrid optimization algorithm based on sensor distribution index and FE grids
Robust Optimal Sensor Placement for Uncertain Structures With Interval Parameters
Optimal sensor placement for deployable antenna module health monitoring in SSPS using genetic algorithm
An interval effective independence method for optimal sensor placement based on non-probabilistic approach
best regards,
Chen Yang
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Preferably datasets from long-term monitoring campaigns, including measurements of the structure response during normal conditions and damage and measurements of the most relevant environmental and operational conditions.
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In tha above, the link of one of the famous and applicable data set in SHM (Z24 Bridge - a full-scale dataset) is provided. the temporal and frequency based data are available through an email.
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It is appreciated if you recommend a benchmark study with the available dataset for video processing.
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Very interested in the topic
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i have vibration data of bridge and process the data with different possible techniques such as FFT, Wavelet decomposition, Empirical mode decomposition, Hilbert Transform, Frequency domain decomposition, spectrograms, etc. but still i am not able to locate exact or pin point frequency of the bridge structure. in the following techniques the results are in a specific range of frequency such as 2.6 to 3.1 Hz. The data showing this specific range and not providing the exact frequency. because in this range any number can be the natural frequency of the bridge structure. so the actual frequency lies in this specific range but i want to go further in depth to figure out the exact value of the frequency in Hz. but the problem is i am not able to find any technique that will give me answer of my curiosity. i recorded data from accelerometers considering normal traffic conditions. there is not closure of bridge. vehicles are passing normal situation.if anyone have any clue about it or still my question is not clear so i can explain further
i attached some of my results
i will be very grateful to anyone who let me find my answer
thanks
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Dear Ali,
the maximum response recorded by your accelerometers is mathematically the CONVOLUTION of the structural response of the bridge (with a peak expected at each natural frequency) and the excitation by the trucks (with a peak at their own suspension frequency) meaning the frequency of the maximum response is a mix of both! Of course the truck's primary suspension frequencies vary from a truck to the next, still in the same range.
In addition the natural frequency of the bridge is load dependant (weight and position of the heavy trucks at the time of the record), and temperature-dependant (meaning day/night, clear day/cloudy and seasonal fluctuations...)
Back to your precise question, you have just NO WAY to determine the exact bridge natural frequencies by this "natural response" method. As suggested, you must close the bridge (however with the same added load than the usual traffic) and use for example a dropped weight to generate a broadband shock (preferably located in consideration of the anticipated mode shape, which allows you to trigger distinctively the first flexural/torsional modes). And still the exact frequency will vary with the previously mentioned load and temperature conditions... Sorry for you, that's just the complexity of structural vibration physics!
Back to Vahid's remark, we could only appreciate the likely natural frequency range of your bridge by knowing its precise construction and span, but the natural frequency of very long bridge spans can even be below 1Hz (remember the ill-fated Tacoma bridge, destroyed by wind gusts at approx. 0.5Hz resonance https://www.youtube.com/watch?v=j-zczJXSxnw). Obviously short bridges have higher natural frequencies but you can interpret it as revealing over-designed structures! The Tacoma bridge example is also a good evidence of the 3D complexity of the mode shapes (something also well evidenced by Eric's study, which provide a very accurate in-situ modal analysis). My guess is that in your case the 2.6 to 3.1 band correspond effectively to the interaction of the trucks suspensions with one of the main natural frequencies of this bridge... in this global 2.8 +/- 0.3Hz band! But don't ask for more precision...
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Although the Structural Health Monitoring (SHM) methods can be considered relatively well-developed, it seems they have not yet become a standard for civil structures. do you know any valid guidelines or something like that in this field?
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The following link might help you:
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Preferably, I am looking for acceleration signals.
Some papers mention rae data is available in some institutional webpages. Unfortunately, those page are not working any more.
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Recently, the Journal of Bridge Engineering (ASCE) publishes Data Papers, especially bridge structures. You can refer to this journal and find some of them such as:
Download from:
Download from:
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I am interested in the changes in the vibration response of a long-span bridge structure before and after damage. I am developing a dynamic characteristic identification method, which is tested only with simulated data. It will be very helpful with the actual dynamic deformation data to verify this method' capcity of identifying the changes in the characteristics such as the frequency extracted from the monitoring series before and after the structure's damaged.
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If you can send me some relevant GNSS monitoring data , you will be gratefully acknowledged in my future publications.
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Does anyone know public datasets with data collected from accelerometer sensors preferably wireless sensors used in structural health monitoring projects?
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Lamb wave is useful for solid structure health monitoring, and it consists many modes. Unlike ultrasonic bulk wave, when given a pulse excitation (for example, 5-cycle sinusoidal pulse), only boundary or damage can reflect a signal back, so it can be easily reconstructed or simulated by MATLAB. How to reconstruct a Lamb wave like this? Start from a simple aluminum plate, and give it a 5-cycle sinusoidal pulse, how to predict the signal received at another spot?
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In addition to my above answer, Lamb wave signals can be simulated in the Dispersion Calculator v1.10 also for multilayered anisotropic specimen. The MATLAB code is included in the download (check out my RG profile) so that you have access to the algorithms. Check out the attached screenshot of the Signal simulator inside the DC.
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I would like to know more about the following issues:
1. Using images as feedback for the closed-loop control of civil structures
2. Simulating the vision-guided control on the computer without doing an experiment
P.S: There is a wealth of literature that is related to robot control. But, I intend to know more about civil structures, i.e., buildings and bridges.
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Maybe you find answer at TNO. It looks like you serching after science in the field of Digital predictive twin.
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Work is related to structural health monitoring through impedance signature variation.
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thanks for information
S M Anas
, second link will be helpfull for me
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The displacement mode shapes are determined by running the modal analysis on AnsysWorkbench. How we can have the strain mode shape and the modal strain energy using ansysWorkbench. Example: cantilevered beam.
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for example, 750 mmx12x12. E = 2E9 Mpa, poisson ratio 0.3. My question is: what are the steps to follow on Ansys Workbench in order to have strain mode shape and strain modal energy?
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I am a researcher on the prediction of service life of RC structures due to corrosion. The factors which I am considering for this case are chloride diffusion and carbonation and other corrosion related factors.
So far, I am using Life 365 which is recommended for the North American territories, and it is only for chloride related corrosion. Plus, I have found another software called EUCON. I need to download this software. How can I find it?
And are there any recommended software to this related subject.
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Hi Anuraddha,
I've came across this question you asked in 2015. How did your research go? I'm also working on the same topic. I think Eucon isn't the most suitable software to use, since it is based on deterministic models, so you only take uncertainty into account by the partial factors. I think it's better to work with probabilistic models. What were your findings?
Kind regards,
Hanne De Crits
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For condition monitoring of any part / system, can we use Internet of Things technology (IOT)? If so , how can we use it?
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Hi,
IOT is definitely one of the best ways to monitor parts of a system. To do this, you must first set up a data transmission network. This network can be Internet-based or even integrate your system wirelessly. Your sensors or data sources are located in this network and in the second step you have to analyze and sort the received values. Suppose you want to measure and monitor the temperature of a factory electric motors. You can place the temperature sensors on the motors and connect them to a Wi-Fi module. Now all you have to do is cover the factory with a Wi-Fi network. All the sensors are connected to this network. Now you can collect data and Process them.
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Can anyone help me with finding a dataset for alkali-silica reaction(ASR) cracks? Thanks
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I am doing modelling of the piezoelectric sensor in Ansys workbench but unfortunately, I am unable to find any help regarding it. There are many helps given for same work in ansys apdl, so I was thinking if I can convert ansys apdl results or work into Ansys workbench and vice versa. A reply would be appreciated. I would be thankful if I get help from anywhere in the world.
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Thank you Norie Allafi Akeel sir for the help. I will implement the same.
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I did an experiment on a glass composite thin plate and generated Lamb wave. I increased the stiffness of the plate by forming a sandwich structure. I could find Ao mode with very attenuated amplitude but So is very diminishing. Confused, as per my understanding, I should get both modes frequencies even if the amplitude is small. But only Ao I could obtain its frequency but So not.
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The dimensions of the thin plate, the configuration of shaker or input device, support and/or constraint of the specimen during testing, the location or distribution of area being measured for signal to test for Ao & So, as well as what transducer(s) or optical technique(s) is/are being used for those measurements, and what circuits and software are being used to condition and process the signal after acquisition.
The are many reasons that may be causing attenuation or lack of effective detection or isolation of the desired or expected signals, including that they actually may not be there at sufficient energy level for effective detection. Are you sure your estimated values for So of the increased-thickness sandwich plate are reasonable and don't actually predict the lower So values? Are you measuring 'lamb' waves on one skin of the sandwich only or of the entire plate (i.e. do you have transducers on both surfaces of the plate with careful and accurate reproduction of phase in both cases, and relative to one and other? Do you isolate or effectively filter frequency or wavelength anywhere in the process of your data collection, conditioning and/or post-acquisition processing? Are the 'lamb' waves on the skin or in the overall plate, what is the ratio of characteristic wavelength to plate thickness and how did this change by your structural alteration?).
Without knowing more of your setup, you experiment and your instrumentation, it is difficult or impossible to offer meaningful guidance.
In terms of a general vibration measurement problem, what signal are you expecting and why? Does the measured value represent something that seems impossible or not, it the result within or nearly within the expected range, and if not, is there something in the method or instrumentation or conditioning/processing that might explain any observed discrepancy? Hope this helps.... -TH
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Hi,
I am trying to model Lamb waves propagation in an Aluminum plate using Abaqus. If I choose the frequency of 5-cycle Hanning excitation source is 0.2 MHz (to make sure that only 2 modes S0 and A0 appear in the result), the result showing good (see Fig.1) and the amplitudes of displacements does not decrease along measuring points (which have been proven by analytical approach). When I increase the frequency to 1.5 MHz (still have only 2 modes A0 and S0 depend on the dispersion curves in Fig.2) the results become disorder and instability, and the amplitude decrease along these measuring points.
Mesh size has been chosen to satisfy CFL conditions (= 1/15 x wavelength) and the time incrementation has been chosen to ensure that the fastest wave mode can propagate through element size (= element size / longitudinal wave speed).
So why the results become inaccurate?
Thank you for reading this post.
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Hi Ductho,
I believe that you have already tried an even finer mesh and the results are the same (convergence study). Maybe you should change the element type increasing the order of the shape functions (e.g. 2nd order elements if you use 1st order elements) because of the high frequency and wavenumber.
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Online survey "Structural Health Monitoring of adhesively bonded joints"
At the Welding and Joining Institute at RWTH Aachen University, an online survey "Structural Health Monitoring of adhesively bonded joints" on methods and sensors in the field of Non-Destructive Testing (NDT) and Structural Health Monitoring (SHM) of adhesive joints is being conducted among representatives of industry and research. The aim is to clarify the question why a permanent Structural Health Monitoring of adhesive joints is not carried out in practice despite extensive research. Your personal assessment of the suitability of the methods for monitoring adhesive bonds as well as information on investigations using NDT and SHM are particularly interesting for the study.
You can participate in the survey by clicking on the attached link (see below). Please take about 15 minutes to answer the question. The data is collected and published completely anonymously in accordance with the EU Data Protection Regulation (DSGVO).
You are welcome to forward the link to the survey to your adhesive technology colleagues.
Link to the survey about Sosci-Survey: https://www.soscisurvey.de/UmfrageSHM/
Thank you and many greetings from Aachen, Germany
Josef Weiland
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Classification of Structural Health Monitoring methods for adhesively bonded joints:
- adherent strain
- adhesive layer strain
- mechanical damping
- electrical resistance
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What methods can be named to measure the temperature of a surface considering below assumptions and limitations, except for Thermography?
- Measurement of only one or a few spots is enough, and there is no necessity to measure the entire surface and display a thermal map as same as the Thermography technique.
- The methods should not be related to infrared techniques and radiation emitted from the surface.
- Without any contact and with a normal distance for inspection (NDT or SHM) like 0.5 m.
If there is no method with considering the final limitation (non-contact), this restriction can be ignored.
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Temperature measurement, surface temperature, intelligent pyrometer
The non-contact thermometer ensures precise ... Show details · Navigation: Applications · Industries Search by measurement · Acceleration & ...
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Fracture mechanics
Structural dynamics
Earthquake Engineering
Structural Health monitoring
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Hi, I recommend the following book
(recent trends in fracture and damage mechanics)
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Using Abaqus, I am trying to generate symmetric lamb wave mode in a simple Aluminum plate by applying symmetric point force parallel to the plate. The extra wave followed by the S0 mode appears all the time. This is definitely not the A0 mode because the geometry is symmetric and hence no mode conversion would take place, these are not the reflections from the boundary, I am new in this topic and I need some guidance,
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You have a wave packet due to the the impact on the plate. We do not know where is the environment of the plate. The trailing packets can be excited by a far reflection from the boundary the enclosure of the plate.
I proposed this hypnosis because as you see the second wave packet is attenuated relative to the first wave packet. So, i assume trailing pulses are echos of the first pulse. They may come from a far boundary to the plate.
Best wishes
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Hi all!
I am wondering on what would you consider to be the 10 most essential formulas in statistics and 10 in signal processing necessary for statistical pattern recognition and structural health monitoring.
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NDT is applied for quality control & assurance as well as inspection of critical components in aerospace, railway, automotive and energy industries for locating cracks and cavities, detecting defects as well as evaluating the quality of bond between different layers of composites. A large number of NDT techniques have been developed aiming at one or more of these defects, such as eddy current (ET), thermography, ultrasonic (UT) and radiography testing (RT). In Structural Health Monitoring, one or more of these techniques are used
Different NDT techniques exhibit different strengths and limitations. Given the variety of possible defects, it is often necessary to employ more than one NDT technique in order to enhance resolution. E.g., eddy current of conductive materials is useful for near-surface defect detection, while ultrasonic yields volumetric information. What are ways to combine two or more data sets, find their reliabilities; hence obtaining a better interpretability?
i
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You might also be interested in one paper of application of data fusion in predicting elastic modulus of masonry stone though nondestructive data
Ramos et al. A Bayesian approach for NDT data fusion: The Saint Torcato church case study. Engineering Structures Volume 84, 1 February 2015, Pages 120-129
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I know that there are different types of methods used in Structural Health Monitoring (SHM), such as,
  1. Vibration-based SHM
  2. Guided wave-based SHM
So, I would like to know the difference between these methods and what are advantages and disadvantages of the mentioned methods?
Also, if possible, can you provide some articles that mention the advantages and disadvantages of the methods.
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Dear Mohamed,
I agree with what Hadi said. It is a very general question and therefore, there is no satisfactory answer to that.
A few general statements can nonetheless be given:
Assuming that we are interested in linear systems it can be noted that vibration-based methods are often less sensitive towards small damages. For localized defects we then have to look at high order modes in order to see an effect. Normally, only the first few modes are considered. If high-frequency guided waves are used depending on the wavelength they will interact with damages (which are even smaller than the wavelength). However, the response of the system gets much more complex and consequently involved signal processing techniques are used.
On the other hand, you can also use nonlinear techniques as suggested by W. Staszewski. Here, the structure is excited in a suitable mode shape and additionally guided waves are send through the structure. Due to nonlinear effects introduced by defects the response of the system contains higher frequency components. Such a technique can be more sensitive towards small defects.
Another idea is to utilize higher harmonics.
There are a lot of articles out there in the wide body of literature and therefore, I suggest looking at standard books (e.g. encyclopedia of structural health monitoring) to get a first idea. Thereafter, you can post a more concise question which might yield better answers for your area of application.
Kind regards
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I am looking at different types of excitation methods introduced to a structure, they are:
  1. Shaker
  2. Impact Hammer
I would like to know what type of features can be extracted from the sensor for this type of excitation. Also, I have 2 side question:
  1. when using; for example, wavelet domain or time series models where coefficients are the output of the models, how can the coefficients be used as features in machine learning?
  2. What other excitation methods can be introduced to a structure other than the methods mentioned above?
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I don't know how should I answer this question, it looks very basic. However, I will try.
1. An accelerometer is a sensor that gives the relative acceleration in a 2 or 3-dimensional space. So if there is a movement, the output of the accelerometer will be a set of voltage values in the direction of the movement corresponding to the amount of acceleration. A microcontroller and associated circuitry are needed to collect and store this time-series data from a sensor, or smartphones that have built-it accelerometers can be used. The sensor/phone needs to be tied/fixed with the instrument at a convenient spot to measure its acceleration during its operation.
2. Regardless of the domain (time, frequency, wavelet, power...), almost any value (or a set of values) that represent the signal or has been driven from the signal can be used as a feature for learning. If you are not familiar with how, please explore the decision-tree based methods (Decision tree classifier, Random forest, Gradient boost, Extratree), they are relatively easier.
3. There are literally countless methods for feature extraction from signals. But based on the nature of the data, I suggest you start working with frequency and power features (DFT, FFT, PSD, PWELCH etc...)
Hope this helps.
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I am trying to find the pixel vales by using DAS algorithm, I have calculated the envelope of the signals by using Hilbert transform and then calculated the arrival time of a signal traveling from the actuator to the arbitrary pixel value (x,y) and then to the sensor, they actually form multiple ellipse but I cant figure out the next step to obtain the image value, E(x, y). The general formula of DAS is attached. Someone please help me.
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I don't know your problem exactly, but i can guide you how to implement this in Matlab or some other software. Follow the steps in software coding:
1. First what is i,j. Fix it. What is u and v?
2. Find t(x,y) value using the given formula.
3. Second step evaluate u and v.
4. Third step find rij.
5. Its not simple. You should interrupt like this
rij(t(x,y)) =
6. Then find E(x,y)
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In recent years Big Data has become one of the issues of modern era. So that, handling Big Data is more important to find out useful information. As mentioned in related studies, traditional analytics may not be useful in Big Data.
On the other hand, in Structural Control and Health Monitoring we are facing a heck of input which can be treated as Big Data (Due to its Volume, Velocity and Variety of input).
On the whole, finding solutions to these control problems may be interesting. I was wondering if any friend is working in this field or can introduce proper references.
Best Regards,
Arian
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Thank you Ashutosh Karna for your answer, I would be happy to know more about your work, although it is not close to my research.
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Hi guys,
I need the MatLab codes for EFDD and SSI using the stability diagram, except the ones already on File Exchange in Mathworks. Please, can anyone help me out? Thanks in advance.
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Dear all,
Let me briefly go through the problem I am facing.
Currently, I have data ( of ground acceleration) obtained from the "seismic accelerograph instrument system" which was placed at the basement of the building and the plot is shown below. According to the plot, it is showing a random waveform up to a certain time and it starts decaying (damping occurs). However, it again gets another waveform (sinusoidal, as shown in the figure) after 300 sec. It looks very unusual to me. I suspect the sinusoidal part to be a building response. But I couldn't decide whether my assumption is valid or not.
So, my questions are:
  1. Is there anything (books/journals/published or unpublished thesis/lecture notes) that talks about the limitations of the time period which we are supposed to make while plotting the ground motion data?
  2. Is there any specific guidelines or any thumb-rule to determine whether the certain waveform is coming from the earthquake motion or is a building response? Normally, what I do is- I consider the random waveform as an "earthquake response" and a sinusoidal waveform as a "building response". Is it the correct way or is there another way we need to look at?
  3. My confusion arises when I saw a portion of "sinusoidal" wave before there is damping. In the figure, it is shown under the "orange" box. So, is it acceptable if I make a statement like- the presence of sinusoidal wave along with the random wave is due to the fact that the sensors recorded the both "earthquake and building response" at a time?
  4. If No, how can it be justified? If Yes, how do I correct this problem?
Thank you so much.
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There is free software which will do this, as well as adjustment and filtering, for you.
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I'm trying to find some articles or book chapters to learn about data fusion in structural health monitoring. Can anyone help me with that please?
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You can use SPSS manual and go to to " Transform" and under transform click "recode to different variables". The SPSS MANUAL CAN BE FOUND ONLINE.
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I'm a first year Master's student and I am going to work on structural health monitoring. Can anyone suggest me some good ideas I can work on in this field?
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Dear Zahra,
This question is so general. It seems that you need to study the literature of SHM first, then you can find a suitable topic. Here are the sample papers to start with:
Also, you can find the latest works on SHM in some journals, such as:
1. Mechanical Systems and Signal Processing
2. Structural Health Monitoring
3. Structural Control and Health Monitoring
Best of luck,
Masoud
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I want to do health monitoring of an Induction Motor by collecting data like Vibration, Temperature, Current and Voltages in normal operation condition and faulty condition.
Currently I am testing some BLDC Motors using a Motor-Coupling-Generator set. I need to set up a new test rig using Induction Motor. What could be the possible setup and equipment needed for the test rig?
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You can use voltmeter and ameter at supply to measure voltage. Current and power .attach an accelerometer and thermocople to measure vibration and heat .use rpm meter and tourqe meter at the shaft to measure speed. Tourqe and shaft power .efficiency can be calculated from out to input power ..
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Hello everyone, I hope everything is alright with you all.
I am interested in utilising machine learning and data science into SHM. Does anyone know the steps involved in SHM with machine learning and data science? Also, where would I find like tutorials or blogs that would help me understand more about the application of machine learning and data science in SHM.
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there is also plenty of literature on the application of ML/DS methods and models in SHM. Here are a few good examples to start with - some of them with well-documented case studies, depending on the goal to be pursued... And this is only the tip of the iceberg =)
I hope this helps you on your journey!
Kind regards,
Patrick
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Which method has the highest sensitivity for SHM evaluation using piezoelectrics: ultrasound or electromechanical impedance?
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Both methods could be very sensitive. It depends on the frequency. However, ultrasonic guided wave are able to monitore surfaces. The impedance measurements are (to my knowledge) monitore effects next to the sensor.
What system you choose depends on the problem you want to solve or monitore.
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What are the methods for internal damage detection of structures?
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Take a look at NDE web manual designed by FHWA
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Dear researchers,
Could you please share some new ideas in structural health monitoring of composites?
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I do some experiments in using AE method to detect events.
I can plot a lot of figures such as hits, signal strength, waveform, counts, events so on.
Which data shall I concentrate on?
A little bit confused.
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Hi Ahmed,
You have to consider 2 aspects: the time series you got from measurement and its spectral analysis.
From the first one, you will decide a threshold and extract time dependent parameters such as time of hit, maximum amplitude, time of rise, number of hits, duration, signal intensity,... all of them are usually performed by commercial software.
Then you will have to perform a spectral analysis in order to detect the frequencies best represented in your signal. This may give interesting results if your sensors are wide-band. The simplest way to perform spectral analysis is to compute a Fourier transform, and look at the modulus (square).
Which are the main parameters... depends on your application and can't be decided a priori. What you can do is compute a all set of parameters and then compute a principal component analysis to detect the most relevant parameters.
Hope this helps.
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I am trying to capture a damage based nonlinear phenomenon (generation of higher harmonics) in a system but instruments induced nonlinearity (specially from high voltage amplifier) is so dominant that damage induced nonlinear phenomenon is insignificant compared to it.
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1- Use "linear" high power amplifiers in generation side. RITEC system has linear high power amplifier that means it does not inject extra higher harmonics to primary signals. You can also use high power filters to remove second harmonics. This is more affordable for group who does not have funding to buy expensive linear amplifiers. So, always make sure your wave generation method does not generate higher harmonics.
2- Try to not use any amplifier or filter on reception side. In general, PZT sensors do not need to be empowered by amplifiers. MST, and PVDF sensors are also very good in SNR, while MST can generate some sort of higher harmonics inside.
3- Do not use computer board oscilloscopes. Boards inside the computer cases are exposed to higher noise level and hard to suppress them. Make sure your Osc. has very low noise level when it is grounded.
4- Use stable grounding to make sure the noise level is minimum and electormagnetic perturbations are damped.
5- Use high number of averaging. Usually 500 averaging is a reasonable number, while some studies have used up to 2000 averaging to get rid of stochastic fluctuations.
6- Waves with different polarizations in first and second harmonics are interesting since it is possible to separate the receptions by different sensors (Please check our JAP 2018 paper). The idea is extendable to bulk waves, as some groups have been working on it (Referenced in our JAP 2017 and 2018 papers).
7- Using wave mixing, it is possible to effectively isolate majority of electronic nonlinear perturbations. We have worked on guided wave mixing in plates and you can check our papers. Plus some other papers are highlighted referring to bulk waves and surface waves.
hope my answer can be helpful!
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the use of AI in structural health monitoring of bridges.
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The application of AI to civil engineering is growing quite a bit. If you get some time, you may go through my papers which focused on AI applications to bridge infrastructure
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Suppose say i measured crack width and length on a column. I have a computer model of that column in SAP/ETABS. I want to put the crack property in that model.
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The CHBDC commentary recommends the following:
1- for cracked beams, reduce the stiffness by 65%
2- for columns, reduce the stiffness by 30%
What type of cracks are you considering?
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I intend to conduct a modal testing on a clamped-clamped steel beam in ABAQUS.
-The input is random signal with normal distribution, zero mean, and maximum amplitude of 5 (N).
-Duration of loading is 30 seconds.
-The length of the beam is 2 meters which is monitored by 5 sensors attached on top surface of the I-shape beam.
-Sampling rate is 100 so the cut-off frequency is 50 (Hz).
-The beam's natural frequencies are in range of 4 to 35 (Hz).
Have I set the right parameter to perform modal analysis?
I am recording the acceleration data of the sensors for a structural system identification method, unfortunately the identified frequencies from the Stochastic System Identification (SSI) method are not satisfying and do not match with real frequencies, I believe the above parameters should change to achieve my desired results.
I would be appreciated if anyone help me out with the right numbers for duration of the analysis, sampling rate, number of sensors, and the type of excitation applied to the beam.
Thank you.
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Do you know any applicable method to obtain/calculate displacements (rather than acceleration) in some levels of a building during external excitation, say earthquake (with an acceptable error )?
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Lidar
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I am about to perform an analysis on effects of temperature gradients on natural frequencies of an I-shape steel beam with ABAQUS, would anyone give me clues on how long I should presume for analysis duration and how much temperature gradient is common in bridges?
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I suggest you to use a conservative gradient( bigger range), because steel bridges are very sensitive to temperature change. You'd better also consider temperature gradient in 3 directions: longitudinal, transverse, and vertical.
Temperature has no direct effect on vibrational properties of the structure, but it may cause damage to it. Therefore it can change the physical parameters and then it may affect the natural frequency.
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Structural health monitoring system are used to monitor the health of the architecture of the plane and constructions when they are monitoring , they used piezoelectric sensor to log the data. Why another sensor which has high sensitive cannot be used
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In addition to the advantages mentioned in previous comments, piezoelectrics can be used to perform electromechanical impedance based SHM. In this way, the health monitoring is not just limited to the force variations in the system and any change in the state of host structure can be captured in a very fast manner (in the order of micro and milisecond). The change in the state can be because of force, boundary condition, growth of cracks and defects, initiation of failure, temperature, density, plastic deformation, etc.
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we know that temperature affects structure's dynamic properties such as stiffness and damping, so it could result in false alarm.
what are the common methods in eliminating temperature effect in damage detection?
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What could Carbon Nanotube additives in cementitious materials influence on the real time structural health monitoring?
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Contact my colleague Dr. Martín Negri.
I am quite sure he Could suggest some solutions. He is working on polymers with electric and magnetic properties.
email:
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Dear friends,
i am doing the project in structural health monitoring.
i need a help to develop and implement the coding matlab.
please kindly help me.
looking positive information
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Dear Narendrakumar
Outlier detection methods are a branch of data mining if computer science which can be used for structural health monitoring. Such methods detect anomalies in the data collected of structure state as damage candidates. There are many outlier detection algorithms such as statistical based, distance based, density based, clustering based and etc for the purpose of Outlier detection. The code of some these methods are available in Internet. Also, there are papers about health monitoring using anomaly detection algorithms which can be used as your solution. 
Best regards 
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I am not getting hint regarding which parameters to choose for the attributes and how exactly to implement it in WEKA. Can anyone help me? I am working on Structural Health Monitoring
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Greetings
I had implemented SVM classifier under Weka for a classification problematic of hydro stations, this document below helped me a lot. You have just to follow the steps
Good luck
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Hi,everyone,
I am writting the program about polymax (p-LSCF),I am very confused about it.
could you please help me about it?
thank you very much!
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Dear Shuai Li,
As far as I know Polymax is a commercial name. 
There are some free software, which you can access using Mathworks, or some of them have their own web site (see the link please)
These software may give an insight.
Good luck,
A. Oktav
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do you apply NDT test only for loadbearing elements?
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And there is now a new technique. AE. (Acoustic Technique.)
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Dear Merlin Freeda,
if you have to detect damage on framed structures, you could use a methodology based on the modal curvature evaluation (the proposed methodology works into the time-frequency domain). You can find a simpe description in the following papers. If you have any questions, do not esitate to contact me.
Sincerely,
Rocco Ditommaso
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Regarding Fiber Bragg grating sensors (FBG)
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Check this author and his publications:
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Currently, I am conducting research on building health monitoring using accelerograph data. Could anyone recommend me some method for building health monitoring. Thanks
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There are several vibration-based Structural Health Monitoring techniques described in the literature. Modal based techniques, which analyze the variations of the modal properties over time to identify damage, are probably a good starting point for your research. Other techniques are based, for instance, on autoregressive models or wavelet analysis, but the principles of vibration based monitoring are almost the same independently of the considered technique. Health monitoring, in fact, is always based on the comparison of two states of the structure, of which one is assumed to be healthy.
You can start from my papers on automated OMA and vibration based health monitoring and the references therein to start your research.
Best regards,
CR
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Well, I m working on structural health monitoring of the mechanical systems, as a part of the research, I m working on the problem called cantilever beam. As a case of, I modeled cantilever beam to my requirements. however mass and stiffness matrix of the continuous beam is obtained using ANSYS. But, the problem is I need damping matrix to be obtained without using ANSYS. can someone explain me theoretical formulation and methodology to define the damping matrix using stiffness and mass matrix? 
Thanks and regards
Dheeraj
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I came across a lot of papers describing WSN for aircraft application. The papers are very promising and lot of efforts is being spent in this direction but I am not clear whether these can be used in real aircraft. How the EMC problems and other security issues can be addressed? Any standard exists for this application.
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SAE standard ARP6461 "Guidelines for Implementation of Structural Health Monitoring on Fixed Wing Aircraft" should address your questions.
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I am looking to normalize the shape modes of a Euler-Bernoulli beam in spectral element method. The difference between this method and FEM is we have only dynamic stiffness matrices instead of mass and stiffness matrices. As you know, in FEM we use the mass matrices to normalize shape modes. What should I do now?
Thanks for your attention
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Mass normalized mode shapes make the stiffness matrix diagonal with elements equal to the eigenvalues (square of circular natural frequencies). If you know the natural frequencies, you can look for the appropriate scale factors that mass-normalize the mode shapes.
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Hi all,
I am a student researcher who does predicting the service life of the RC structures due to chloride admittance. I am trying to set up an empirical study to test the time for the concrete members to crack after initiation of corrosion. My test specimens will cover a vast range of different material properties such as W/C ratio, cover depth, bar diameter etc.
In order to corrode the samples, I am using impressed anodic current. And I will be monitoring the crack propagation on each sample until it reaches a prescribed crack width. Based on this, I am trying to establish a relationship how long it will take to crack the cover concrete. But the corrosion is done using the impressed current method.
So in this case, how things would be correlated to the natural corrosion? 
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Greetings
in our experience in the assessment of natural and accelerated embedded in concrete steel corrosion, there is no direct correlation in reference to time, however we found models lifespan for estimating useful life as the factor that initiates corrosion, carbonation and chloride ion penetration.
read the results suggest Duracon project:
Durability of concrete structures: DURACON, an iberoamerican project. Preliminary results
Effect of the marine environment on reinforced concrete durability in Iberoamerican countries:DURACON project/CYTED
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The signals are discrete wavelet transform values of strain profiles taken to assess potential damage locations
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Hi Alan,
I think you can develop some kind of correlation coefficient based on the comparison of the wavelet-decomposition coefficients. This kind of analysis has been used in weather prediction. 
Best,
Martin
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This is challenging as we might loose contact in some spots as curling happens due to thermal gradient.
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Hi Abolfazl,
The answers depend greatly on whether the concrete slab will be removed after a while, or that it stays in place, and you have only one chance of placing the sensors.
In the first case you could apply pressure sensitive foil that contains tiny ink capsules that release upon pressure, to get a pressure image.
For permanent installation with real-time readout on a large amount of places, you might apply numerous sensors distributed along an optical fiber, based upon Fiber Bragg Gratings (FBGs). These are used for monitoring all kind of large structures. FBG based sensors can be used for a wide variety of parameters, and you can even mix parameters along a fiber. Lun Cheng from TNO is a world-renowned expert on these sensors.
Kind regards, Fokko Wieringa