170 research outputs found

    A simple method for enhanced vibration-based structural health monitoring

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    This study suggests a novel method for structural vibration-based health monitoring for beams which only utilises the first natural frequency of the beam in order to detect and localise a defect. The method is based on the application of a static force in different positions along the beam. It is shown that the application of a static force on a damaged beam induces stresses at the defect which in turn cause changes in the structural natural frequencies. A very simple procedure for damage detection is suggested which uses a static force applied in just one point, in the middle of the beam. Localisation is made using two additional application points of the static force. Damage is modelled as a small notch through the whole width of the beam. The method is demonstrated and validated numerically, using a finite element model of the beam, and experimentally for a simply supported beam. Our results show that the frequency variation with the change of the force application point can be used to detect and in the same time localize very precisely even a very small defect. The method can be extended for health monitoring of other more complicated structures

    A simple method for enhanced vibration-based structural health monitoring

    Get PDF
    This study suggests a novel method for structural vibration-based health monitoring for beams which only utilises the first natural frequency of the beam in order to detect and localise a defect. The method is based on the application of a static force in different positions along the beam. It is shown that the application of a static force on a damaged beam induces stresses at the defect which in turn cause changes in the structural natural frequencies. A very simple procedure for damage detection is suggested which uses a static force applied in just one point, in the middle of the beam. Localisation is made using two additional application points of the static force. Damage is modelled as a small notch through the whole width of the beam. The method is demonstrated and validated numerically, using a finite element model of the beam, and experimentally for a simply supported beam. Our results show that the frequency variation with the change of the force application point can be used to detect and in the same time localize very precisely even a very small defect. The method can be extended for health monitoring of other more complicated structures

    Damage and repair classification in reinforced concrete beams using frequency domain data

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    This research aims at developing a new vibration-based damage classification technique that can efficiently be applied to a real-time large data. Statistical pattern recognition paradigm is relevant to perform a reliable site-location damage diagnosis system. By adopting such paradigm, the finite element and other inverse models with their intensive computations, corrections and inherent inaccuracies can be avoided. In this research, a two-stage combination between principal component analysis and Karhunen-Loéve transformation (also known as canonical correlation analysis) was proposed as a statistical-based damage classification technique. Vibration measurements from frequency domain were tested as possible damage-sensitive features. The performance of the proposed system was tested and verified on real vibration measurements collected from five laboratory-scale reinforced concrete beams modelled with various ranges of defects. The results of the system helped in distinguishing between normal and damaged patterns in structural vibration data. Most importantly, the system further dissected reasonably each main damage group into subgroups according to their severity of damage. Its efficiency was conclusively proved on data from both frequency response functions and response-only functions. The outcomes of this two-stage system showed a realistic detection and classification and outperform results from the principal component analysis-only. The success of this classification model is substantially tenable because the observed clusters come from well-controlled and known state conditions

    A national cross-sectional survey of dental anxiety in the French adult population

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    <p>Abstract</p> <p>Background</p> <p>Dental anxiety is a public health problem but no epidemiological study has been undertaken in France to evaluate its prevalence. The aim of this study was to estimate the prevalence, severity and associations of dental anxiety in a sample of the French adult population.</p> <p>Methods</p> <p>A convenience sample of 2725 adults (mean age = 47 years, SD16, minimum = 16, maximum = 101 years), representative of the French population with regard to age and urban distribution, completed a French version of the Corah Dental Anxiety scale (DAS) and a questionnaire relating to their dental appointments.</p> <p>Results</p> <p>Moderate dental anxiety (14≥DAS≥13) was revealed for 172 persons (6.2%), while 195 (7.3%) had severe dental anxiety (DAS≥15), giving an overall prevalence of dental anxiety of 13.5%. Prevalence was lower proportionally with age (P < 0.001) and was higher in French overseas territories and in the countryside (P < 0.01). Farmers and low skilled workers were significantly more anxious than executives and shopkeepers (P < 0.001). Anxiety was associated with avoidance of care (p < 0.001) and lack of regular dental appointments (p < 0.001).</p> <p>Conclusion</p> <p>Dental anxiety in France appears to concern a similar proportion of the population as in other industrialised European, Australasian or North American countries. Recommendations for prevention and management of dental anxiety are made with reference to dental education and health care services in France.</p

    A Critical Review on the Structural Health Monitoring Methods of the Composite Wind Turbine Blades

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    With increasing turbine size, monitoring of blades becomes increasingly im-portant, in order to prevent catastrophic damages and unnecessary mainte-nance, minimize the downtime and labor cost and improving the safety is-sues and reliability. The present work provides a review and classification of various structural health monitoring (SHM) methods as strain measurement utilizing optical fiber sensors and Fiber Bragg Gratings (FBG’s), active/ pas-sive acoustic emission method, vibration‒based method, thermal imaging method and ultrasonic methods, based on the recent investigations and prom-ising novel techniques. Since accuracy, comprehensiveness and cost-effectiveness are the fundamental parameters in selecting the SHM method, a systematically summarized investigation encompassing methods capabilities/ limitations and sensors types, is needed. Furthermore, the damages which are included in the present work are fiber breakage, matrix cracking, delamina-tion, fiber debonding, crack opening at leading/ trailing edge and ice accre-tion. Taking into account the types of the sensors relevant to different SHM methods, the advantages/ capabilities and disadvantages/ limitations of repre-sented methods are nominated and analyzed
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