Presence Of Structural Damage Research Articles

Bridge anomaly detection based on reconstruction error and structural similarity of unsupervised convolutional auto-encoder

This study presents a novel bridge anomaly detection approach that employs the reconstruction error and structural similarity of an unsupervised convolutional auto-encoder. The presence of structural damage in a bridge typically results in changes in its vibration signals, and thus, the use of these signals for structural damage detection (SDD) has been widely investigated, with many methods relying on supervised learning. However, such existing SDD methods based on the supervised learning require prior knowledge of the damage states and cannot process monitoring data in real-time, thereby limiting their application to in-service bridges. To address this challenge, the authors propose the use of a convolutional auto-encoder as the reconstruction algorithm for real-time vibration signals. The auto-encoder is trained using normal signals and then used to reconstruct new inputs (either normal or abnormal). Two damage indicators (reconstruction error and structural similarity) are then calculated based on the reconstruction results and clustered to detect abnormal signals. The proposed approach was applied to the detection of various abnormalities in the old ADA Bridge, the results were 100% accurate, and about a 10% increase in accuracy was observed when compared to other control experiments. These results demonstrate the effectiveness of the proposed approach, with the auto-encoder achieving excellent reconstruction results for normal signals and clear discrepancies for abnormal signals. The proposed method was also validated on a cable-stayed bridge and an arch bridge, demonstrating its wide applicability in bridge anomaly detection.

Comparing MRI and conventional radiography for the detection of structural changes indicative of axial spondyloarthritis in the ASAS cohort.

To compare MRI and conventional radiography of SI joints for detection of structural lesions typical for axial spondyloarthritis (axSpA). Adult patients from the Assessment of SpondyloArthritis international Society (ASAS) cohort with symptoms suggestive of axSpA and both SI joint MRI and radiographs available for central reading were included. Radiographs were evaluated by three readers according to the modified New York (mNY) criteria grading system. The presence of structural damage on radiographs was defined as fulfilment of the radiographic mNY criterion and, additionally, a lower threshold for sacroiliitis of at least grade 2 unilaterally. MRI scans were assessed for the presence of structural changes indicative of axSpA by seven readers. Diagnostic performance [sensitivity, specificity, positive and negative predictive values (PPV and NPV) and positive and negative likelihood ratios (LR+ and LR-)] of MRI and radiographs (vs rheumatologist's diagnosis of axSpA) were calculated. Overall, 183 patients were included and 135 (73.7%) were diagnosed with axSpA. Structural lesions indicative of axSpA on MRI had sensitivity 38.5%, specificity 91.7%, PPV 92.9%, NPV 34.6%, LR+ 4.62 and LR- 0.67. Sacroiliitis according to the mNY criteria had sensitivity 54.8%, specificity 70.8%, PPV 84.1%, NPV 35.8%, LR+ 1.88 and LR- 0.64. Radiographic sacroiliitis of at least grade 2 unilaterally had sensitivity 65.2%, specificity 50.0%, PPV 78.6%, NPV 33.8%, LR+ 1.30 and LR- 0.69. Structural lesions of the SI joint detected by MRI demonstrated better diagnostic performance and better interreader reliability compared with conventional radiography.

Terapi Latihan, Infrared, Serta Transcutaneous Electrical Nerve Stimulation Pada Pasien Osteoarthritis Knee

Osteoarthritis is a degenerative disease in the supply that involves cartilage, joint layers, ligaments, and bones so that it can cause pain and stiffness in the joints. Almost 70% of osteoarthritis is experienced by those over the age of 50 years characterized by the presence of structural damage in the joints. The purpose of this study is to control the pain felt by the patient and improve the functional ability of the daily activities carried out by the patient. This study included a case study conducted at one of the hospitals in the city of Sragen on a patient Mrs. SNR, aged 71 years, working as a housewife. The patient complains of pain in both knees, the patient also has difficulty performing squat movements to the stand, standing for a long time, rising from sitting to standing, difficulty in praying. This research method was carried out by therapeutic patients for 2 x / week in 3 weeks, one therapy followed for 30 minutes. Patients are given therapy in the form of exercise, infrared and tens therapy. Pain was measured using the Numeric Rating Scale (NRS) and Western Ontario and the McMaster Universities Arthritis Index (WOMAC) to measure patient functional activity. Conclusion: modalities given by physiotherapy such as Quadriceps Setting Exercises, Passive Stretching, infrared (IR) and Transcutaneous Electrical Nerve Stimulation (TENS) given as many as 4 meetings can increase daily functional activities and there is a decrease in pain.

Local bispectral characteristics of nonlinear vibro-acoustic modulations for structural damage detection

Higher order spectral analysis is used for structural damage detection based on nonlinear vibro-acoustic modulations. A combined low-frequency vibration and high-frequency ultrasonic excitation is used, leading to nonlinear vibro-acoustic modulated responses in the presence of structural damage. The response data are analysed using a modulation signal bispectrum and bicoherence. The analysis of local amplitude and phase of these characteristics is proposed for structural damage detection. The method is illustrated using numerical simulations and experimental data. The latter involves impact damage detection in composite plates. The results show that – in contrast to the classical higher order spectral analysis – the method identifies all nonlinear damage-related coupled components correctly, distinguishes these components from undesired non-damage related modulations, and therefore shows a potential for reliable structural damage detection.

Prospects of Structural Damage Identification Using Modal Analysis and Anomaly Detection

Structural health monitoring (SHM) has significant importance in providing reliability, safety, and economical sensibility for structures. High sensitivity and precision of SHM techniques can be quite demanding. Some SHM testing procedures require structures, for example, wind turbine blades or aircraft structures, to be taken out of operation, which increases costs and causes downtime. Other techniques include sophisticated signal processing and data analysis, which require skilled personnel. An alternative is to use a form of system identification technique called Operational Modal Analysis, during which an operator performs structural vibration measurements without disrupting normal operation of structure. The aim of the current study is to develop a machine learning algorithm, which is able to identify damaged states of a structure, based on the assessment of its modal parameters. The assessment of the structural health is performed using machine learning technique called Anomaly Detection. The proposed method establishes a description of normality using features representing undamaged conditions and then test for abnormality which indicates presence of damage in structure. Structure under test is one-meter-long laminated composite beam. The finite element model of the beam is developed using eight-node shear-deformable shell elements. Damage in the beam is introduced as delamination between the plies representing 5% of the total area of the beam. Numerical modal analysis is carried out to obtain modal frequencies and corresponding mode shapes for the first three bending modes of both the healthy and damaged beams. The results of the numerical experiments show possibilities of the proposed structural health monitoring method to identify damage in composite structures under varying modal parameters.

The Thioredoxin Family Proteins: Histopathological Time Course Study in the Asphyctic Male Rat Brain

Summary:Thioredoxin Family of proteins as Thioredoxin (Trxs), Glutaredoxins (Grxs) and Peroxiredoxins (Prxs) are one of the most important agents in the defense of oxidative stress and redox regulation. Perinatal asphyxia (AP) a disorder generated at the expense of the deficit of oxygen associated or not to ischemia, affects 5 to 10 of every 1,000 live births in developing country and is a serious health problem worldwide. Alterations in antioxidant protection systems are involved in the pathogenesis of hypoxic-ischemic insult and neuronal death. For these reasons it is proposed that the AP can cause changes in the distribution and expression of antioxidant proteins and enhance their deleterious or neuroprotective effects on the CNS. Methods: to determine the implication of the proteins role induced in the hypoxic brain injury, an animal model in vivo of PA was used in this work. In the first instance, the identification of the distribution of Trxs family proteins Trx1, Trx2, TrxR1, TrxR2, Txnip, Grx1, Grx2, Grx3, Grx5, γ-GCS, Prx1, Prx2, Prx3, Prx4, Prx5 and Prx6 was performed by immunohistochemistry on areas most sensitive to a hypoxia-ischemia insult: cerebellum, striatum, hippocampus, spinal cord, sustantia nigra, cortex and retina. Previous studies suggest that these proteins have an extensive and characteristic distribution in various cell types and regions of the CNS, although we observed significant differences in labeling intensity and distribution with conventional and fluorescence optical microscopy. After determining the cellular localization of Trxs, their behavior was studied by during a hypoxic- ischemic event by setting a time course at different times (2, 4, 6, 12, 24 and 72 hours post AP). Results: Trx1, Trx2, Grx1 and Grx2 proteins constitutes the main oxidoreductases in the cytosol and mitochondria, both in physiological and pathological conditions. Thus, for the short asphyxia times in which they were studied, Trx1 was detected with increased expression at 2 hours and up to 4 hours post-AP, arguing a probable neuroprotective effect, although not enough, if taken into account tissue liability and high levels of free radicals detected at initial hours and the presence of structural damage at 7 days post-AP. Trx2 shows its increase at 6 and 12 hours and Grx1 at 24 hours. For Grx2, values elicited with the ELISA technique in the initial time curve were not representative in their expression in the hippocampus, contrary to the findings in the distribution in the striatum, where Grx2 was observed to be increased. Although at 7 hours post-AP levels begin to decline, these redoxins appears to be essential in the initial response to injury. Conclusions: by demonstrating of the presence of these enzymes in different cell types and specific regions of the brain in rats subjected to AP provided us with important morphological evidence base to study later some of the molecular mechanisms involved in the pathogenesis of cerebral ischemia that will help to generate new therapeutic tools to mitigate a disease whose neurological complications have no definitive solution.

Multi-scale method for recognizing damage in high-efficiency milling cutter

Under the influence of a high-speed, interrupted-cutting impact load, the damage degree quickly increases following any structural damage in a milling cutter. The presence of structural damage must be explored given the fact that these conditions may result in irreparable and serious accidents if not immediately detected. Milling cutter damage has multi-scale characteristics. Therefore, the single-scale damage research method cannot reveal the formation and evolution of the multi-scale damage of a milling cutter, which makes it difficult to identify and control the damage of a milling cutter. The damage scales of a milling cutter are divided according to the multi-scale characteristics of milling cutter damage. Based on continuum mechanics, the dislocation theory, and molecular dynamics, the damage characterization method of the macrostructure, lattice structure, and mesoscopic structure of a milling cutter were proposed in this study. Utilizing the multi-scale finite element method and the force connection method, the loading boundary conditions of the multi-scale damage of a milling cutter were established in order to achieve a trans-scale load transfer. The damage characteristics of the macrostructure, lattice structure, and mesoscopic structure of the milling cutter were studied, and the critical value of the multi-scale damage characteristic variable of the milling cutter was obtained. Thereby, the damage position, types, and size and damage occurrence sequences of the milling cutter were revealed, and the damage formation process and the characteristics of the milling cutter were clarified. Based on this, a method for recognizing the multi-scale damage in a milling cutter was proposed and verified by experiments. The results showed that the above method could effectively identify multi-scale damage characteristics and reveal the formation and evolution process of the damage of a high-efficiency milling cutter.

Sustainable concrete construction by microorganism and monitoring using EMI technique: A review

Construction of concrete infrastructures is developing worldwide from the ancient period therefore; sustainable concrete is required for clean environment reason. The formation of cracks/fissures creates problems to the concrete which reduces durability of concrete structures. These cracks/fissures in concrete originate due to the natural forces viz., weathering and landslide, seismic, flooding and human interventions which affect the service life of structures. The application of microorganisms in concrete is the innovative technology for sustainable construction and self-healing of cracks. These microorganisms' bacterium produces calcium carbonate in presence of moisture and carbon dioxide. The use of bacteria in concrete consumes carbon dioxide available in the atmosphere and produces solid substances like calcium carbonate for self-healing of the cracks and develop sustainable infrastructure. Electro-Mechanical Impedance (EMI) technique is based on smart materials and used for monitoring of crack/fissures present in structures. The impedance and admittance signatures can be used for determination of the presence of damage. Admittance signature consists of conductance (real part) and susceptance (imaginary part) signature, respectively. The changes in the signature from the healthy state baseline signature indicate presence of damage in structures. The research review article is focused on microbial-based concrete and its importance related to the clean environment and sustainable construction development. Furthermore, the types of bacteria used in concrete and its optimal concentration have been covered. Moreover, the EMI technique and its application on concrete industry for monitoring the health of structures have been taken into consideration. The use of EMI technique to monitor the performance of bacterial concrete will be helpful for sustainable buildings. The review article will suggest new research directions in the field of sustainable construction industry.

Crack detection in prestressed concrete structures by measuring their natural frequencies

When inspecting the health of a civil structure, it is important to have efficient techniques to detect the possible presence of structural damage. This work deals with the detection of damage in prestressed concrete structures, which are widely used in road bridges and long span slabs, among others. Concrete structures can be affected by different pathologies, with the transverse cracks beingone of the most dangerous damages, since they involve a localized reduction of the flexural rigidity of the structure. Such cracks change both the static and dynamic behavior of the structure. In this paper, an inverse method of damage detection is applied on two experimental beams built in the laboratory, from the measurement of the first three natural frequencies of vibration. An algorithm for solving the system of equations has been developed by the authors. Explicit equations were obtained to calculate both the crack position and its depth. The predicted damages by the algorithm have been in good agreement with the real damages of the experimental models. An important aspect of this methodology for crack detection is the simplicity of its experimental implementation.

Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification

Vibration-based Structural Health Monitoring (SHM) techniques are among the most common approaches for structural damage identification. The presence of damage in structures may be identified by monitoring the changes in dynamic behavior subject to external loading, and is typically performed by using experimental modal analysis (EMA) or operational modal analysis (OMA). These tools for SHM normally require a limited number of physically attached transducers (e.g. accelerometers) in order to record the response of the structure for further analysis. Signal conditioners, wires, wireless receivers and a data acquisition system (DAQ) are also typical components of traditional sensing systems used in vibration-based SHM. However, instrumentation of lightweight structures with contact sensors such as accelerometers may induce mass-loading effects, and for large-scale structures, the instrumentation is labor intensive and time consuming. Achieving high spatial measurement resolution for a large-scale structure is not always feasible while working with traditional contact sensors, and there is also the potential for a lack of reliability associated with fixed contact sensors in outliving the life-span of the host structure. Among the state-of-the-art non-contact measurements, digital video cameras are able to rapidly collect high-density spatial information from structures remotely. In this paper, the subtle motions from recorded video (i.e. a sequence of images) are extracted by means of Phase-based Motion Estimation (PME) and the extracted information is used to conduct damage identification on a 2.3-m long Skystream® wind turbine blade (WTB). The PME and phased-based motion magnification approach estimates the structural motion from the captured sequence of images for both a baseline and damaged test cases on a wind turbine blade. Operational deflection shapes of the test articles are also quantified and compared for the baseline and damaged states. In addition, having proper lighting while working with high-speed cameras can be an issue, therefore image enhancement and contrast manipulation has also been performed to enhance the raw images. Ultimately, the extracted resonant frequencies and operational deflection shapes are used to detect the presence of damage, demonstrating the feasibility of implementing non-contact video measurements to perform realistic structural damage detection.

Structural health monitoring with statistical methods during progressive damage test of S101 Bridge

For the last decades vibration based damage detection of engineering structures has become an important issue for maintenance operations on transport infrastructure. Research in vibration based structural damage detection has been rapidly expanding from classic modal parameter estimation to modern operational monitoring. Since structures are subject to unknown ambient excitation in operation conditions, all estimates from the finite data measurements are of statistical nature. The intrinsic uncertainty due to finite data length, colored noise, non-stationary excitations, model order reduction or other operational influences needs to be considered for robust and automated structural health monitoring methods. In this paper, two subspace-based methods are considered that take these statistical uncertainties into account, first modal parameter and their confidence interval estimation for a direct comparison of the structural states, and second a statistical null space based damage detection test that completely avoids the identification step. The performance of both methods is evaluated on a large scale progressive damage test of a prestressed concrete road bridge, the S101 Bridge in Austria. In an on-site test, ambient vibration data of the S101 Bridge was recorded while different damage scenarios were introduced on the bridge as a benchmark for damage identification. It is shown that the proposed damage detection methodology is able to clearly indicate the presence of structural damage, if the damage leads to a change of the structural system.

Leakage monitoring using percolation sensors for revealing structural damage in engineering structures

There is a continuous need for the monitoring of engineering structures, especially when scheduled inspections are difficult to perform or if they are too expensive. The present paper gives some results on the performance of sensors on the basis of percolation thresholds that are able to detect leakage of diverse harmful liquids, such as water, hydraulic liquids, kerosene and jet engine oils. The focus here lies on sensor systems that give semi-quantitative, fuse-like information on the presence of harmful liquids, which indirectly gives evidence on the presence of structural damage. The common underlying principle is the interruption of percolation conductivity when the respective sensing material is exposed to harmful liquids; that is, the electrical conductivity is essentially lost by sorption and swelling of a dedicated matrix material. The temperature dependence and response times give valuable information on the usability of the sensor in the respective environments. The sensor can be manufactured as a cord sensor or as self-adhesive patches where the functional layer is deposited by screen printing. Copyright © 2013 John Wiley & Sons, Ltd.

Dynamically Reconfigurable Multivariable MEMS Sensor Array for Unattended Systems

This paper presents a dynamically reconfigurable multivariable Micro-Electro-Mechanical Systems (MEMS) sensor array, capable of reconfiguration in real time, to meet the sensing demands of unattended systems operating in highly variable environments, with an emphasis on maintaining operation of these systems in the presence of structural damage. This array is comprised of multiple instances of identical sensors which can be dynamically reconfigured to target a variety of measurands including acceleration, rotational rate, magnetic fields, temperature, air pressure and density. A simulated environment is used to illustrate how the array can be dynamically reconfigured to respond to variations in several of these parameters. Also shown are simulations that demonstrate the ability of such a sensor array to continue operation in the presence of structural damage.

FRI0436 Radiographic spinal progression and clinical disease activity are both relevant for the functional outcome in patients with early axial spondyloarthritis

BackgroundIn cross-sectional studies, it has been shown already that functional status in ankylosing spondylitis (AS), which represents probably the most important long-term outcome, is related to both the presence of...

Physical Examination of the Overhead Athlete’s Shoulder

Overhead athletes seek the services of an orthopedic surgeon because of pain and/or dysfunction. It is important to address the cause of the symptoms more so than the source of the patient's pain, so that treatment will eliminate the problem rather than merely ameliorate symptoms temporarily. In order to accomplish a thorough assessment of shoulder function, the examiner must expand his/her view from isolated assessment of the glenohumeral joint range of motion, stability, assessment of rotator cuff strength, palpation and provocative maneuvers, and add assessment of the shoulder in the context of the kinetic chain. The examination of the thrower's shoulder, coupled with a thorough history, will usually provide a solid functional diagnosis and provide a good idea as to the presence of structural damage. As a result, the value of rehabilitation and the benefit of surgical intervention are made more predictable.

Developments and Comparisons on the Definition of an Instantaneous Damping Estimator for Structures under Natural Excitation

Accurate identification of damping constitutes a relevant issue for structural health monitoring. In fact, high modal or localized damping ratios are often associated with the presence of structural damage. This question may become even more challenging when identifying a structure from its natural vibration (due to wind, traffic etc.). This article describes the results of the latest studies, conducted by this research group, focusing on the definition of an instantaneous estimator of damping for the identification of structures under unknown non-stationary excitation. A method is presented, in particular, which is based on instantaneous curve-fitting applied directly to time-frequency representations of dynamic response signals. One of the strong points of this technique is its flexibility: from each signal, in fact, a time function of damping is extracted, providing punctual information on estimate stability. A series of numerical applications to Multiple Degree of Freedom (M-DOF) systems is presented; the performance of the method is examined under increasing levels of non stationarity of the excitation. Finally, the results are compared with those obtained, on the same data, through the use of three known time-domain identification methods: Direct System Parameter Identification (DSPI), Eigensystem Realisation Algorithm (ERA), Polyreference Time Domain (PRTD). The latter two were used with the Random Decrement function.

Qualitative impedance-based health monitoring of civil infrastructures

This paper presents a qualitative health monitoring technique to be used in real-time damage evaluation of civil infrastructures such as bridge joints. The basic principle of the technique is to monitor the structural mechanical impedance which will be changed by the presence of structural damage. The mechanical impedance variations are monitored by measuring the electrical impedance of a bonded piezoelectric actuator/sensor patch. This mechanical-electrical impedance relation is due to the electromechanical coupling property of piezoelectric materials. This health monitoring technique can be easily adapted to existing structures, since only a small PZT patch is needed, giving the structure the ability to constantly monitor its own structural integrity. This impedance-based method operates at high frequencies (above 50 kHz), which enables it to detect incipient-type damage and is not confused by normal operating conditions, vibrations, changes in the structure or changes in the host external body. This health monitoring technique has been applied successfully to a variety of light structures. However, the usefulness of the technique for massive structures needs to be verified experimentally. For this purpose, a 500 lb quarter-scale deck truss bridge joint was built and used in this experimental investigation. The localized sensing area is still observed, but the impedance variations due to incipient damage are slightly different. Nevertheless, by converting the impedance measurements into a scalar damage index, the real-time implementation of the impedance-based technique has been proven feasible.