Papers by Keyword: Structural Health Monitoring (SHM)

Abstract: The process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring. Many different types and degrees accidents take place, especially some important collapse accidents, the significance of steel structural health monitoring has been recognized. The introduction begins with a brief research status of steel structural health monitoring in china and the world. The paper analyzes the projects and contents of steel structures monitoring from nine aspects and summarizes the diagnosis methods of steel structural damages which include power fingerprint analysis, the methods of model correction and system identification, neural network methods, genetic algorithm and wavelet analysis, it provides us theoretical guidence. In conclusion, structural health monitoring for steel structures could reduce the impact of such disasters immediately after natural hazards and man-made disasters both economically and socially, thus it is becoming increasingly important.

Abstract: The difficulty in predicting the long term load capacity of concrete elements is well documented. Time dependent effects such as creep and shrinkage coupled with varying loading events, particularly during construction, can all have an adverse effect on the long term performance of a concrete structure. This paper proposes a method that utilises in-situ instrumentation to predict the load carrying capacity of concrete members. During the construction of the Engineering building at the National University of Ireland, Galway over 260 sensors were embedded in a number of key concrete elements. The sensors are being continually monitored with the use of automatic datalogging equipment and the data is being used to monitor changes in geometric and material properties along with the subsequent time dependent deterioration of the elements. The paper will illustrate how the in-situ data from the demonstrator building can be used to estimate the real time behaviour of the concrete elements and how these elements might respond to future changes in use and potential retrofitting. A cost analysis will show how such a monitoring system can be used to reduce the uncertainty levels involved when retrofitting concrete buildings.

Abstract: A novel structural health monitoring system to detect damages in structures under varying operational and environmental conditions is presented in this paper. A noncontact, full-field measurement using a high speed camera offers a convenient and less expensive measurement procedure, enabling the measuring of responses in elevated temperatures and in conditions where contact sensors are unable to be used. In this paper, a combination of Decay lines of the Wavelet Transform Modulus Maxima (WTMM) and Holder Exponent (HE) are used to distinguish changes on the time response of a vibrating structure due to the operational and environmental variations to changes due to the presence of damage, thus minimising the possibility of false alarm. The proposed methodology is demonstrated using a 3-DOF system under conditions of varying and constant temperatures with the presence of damage, as well as using an experimental setup of a cantilever beam under intact and damaged conditions.

Abstract: The aim of the present paper is to provide a state-of-the-art outline of structural health monitoring (SHM) techniques, utilizing temperature, noise and vibration, for wind turbine blades, and subsequently perform a typology on the basis of the typical 4 damage identification levels in SHM. Before presenting the state-of-the-art outline, descriptions of structural damages typically occurring in wind turbine blades are provided along with a brief description of the 4 damage identification levels.

Abstract: Photogrammetric techniques have demonstrated their suitability for monitoring static structural tests. Advantages include scalability, reduced cost, and three dimensional monitoring of very high numbers of points without direct contact with the test element. Commercial measuring instruments now exist which use this approach. Dynamic testing is becoming a convenient approach for long-term structural health monitoring. If image based methods could be applied to the dynamic case, then the above advantages could prove beneficial. Past work has been successful where the vibration has either large amplitude or low frequency, as even specialist imaging sensors are limited by an inherent compromise between image resolution and imaging frequency. Judgement in sensor selection is therefore critical. Monitoring of structures in real-time is possible only at a reduced resolution, and although imaging and computer processing hardware continuously improves, so the accuracy demands of researchers and engineers increase. A new approach to measuring vibration is introduced here, whereby a long-exposure photograph is used to capture a blurred image of the vibrating structure. The high resolution blurred image showing the whole vibration interval is measured with no need for high-speed imaging. Results are presented for a series of small-scale laboratory models, as well as a larger scale test, which demonstrate the flexibility of the proposed technique. Different image processing strategies are presented and compared, as well as the effects of exposure, aperture and sensitivity selection. Image processing time appears much faster, increasing suitability for real-time monitoring.

Abstract: Damage Detection problem in Structural Health Monitoring (SHM) is widely studied by many researchers, therefore lots of damage detection algorithms can be found in the literature. Feature Selection / Extraction methods are essential in the accuracy of these algorithms, they provide the suitable data to be used. The main goal of this work is to improve the input data to be the most representative for the damage detection problem. This is done using different Feature Selection / Extraction methods (PCA, UmRMR, and a combination of both). After taking the representative features, the results are tested using a damage detection method; the NullSpace in this case. The data has been collected from a Laboratory Offshore tower model. The different results are compared (different preprocessing vs Raw data) and these show how the correct preselection of the data can improve damage detection.

Abstract: This paper investigates the potential use of PolyVinyliDene Fluoride (PVDF) for the purposes of damage detection for infrastructural elements, primarily for bridge elements. PVDF based sensors have been created and characterised in the laboratory in this regard. Finite element analysis of vehicle-bridge interactions with varying damage are carried out. The energy harvesting signatures of realistic trains are assessed and quantified for the modelled bridge. The effect of localized damage on the finite element model and its subsequent relationship with energy harvesting from the calibrated PVDF based sensors are investigated using the harvesting signatures of realistic trains. This approach is useful in terms of designing new generation smart bridge structures and for possible retrofit of existing structures. The use of train-bridge interaction ensures that the damage detection is carried out while the bridge is under operational conditions. Consequently, there is minimal to no impact on the existing operation of the bridge or the transport network during damage detection. The paper is expected to be useful for practicing engineers and researchers in the field of application of new materials in the next generation of bridge structures.

Abstract: Signals received by piezoelectric transducers (PZT) network can be influenced by many factors. Apart from environmental conditions, whose variability should be compensated, significant difference in a signal can be also caused by relative geometry changes of a designed sensors node, e.g. the damage localization and its orientation with respect to sensors location in the node. In the adopted approach a set of damage indices (DIs), carrying marginal signal information content and correlated with the total energy received by a given sensor are proposed. These are sensitive to the two main modes of guided wave interaction with a fatigue crack, i.e. its transmission and reflection from a damage. Detailed description of DIs detection capabilities are delivered in the paper. Two dimensional reduction techniques: Principal Component Analysis and Fishers Linear Discriminant are compared. The results of the data collected from specimen fatigue test are used to compare several classification models based on the emerged effective damage indices.

Abstract: RFID is a rapidly developing technology of wireless communication and identification mostly used in supply chain systems, logistic and access control. Nowadays attempts to transfer this technology to other applications are carried out. This paper presents review of global researches performed last years, on application of RFID technology to tasks connected with wireless passive sensing in Structural Health Monitoring, with additional overview of works conducted in this subject by the authors. Sensors based on this technology require neither battery nor wire. It could be interrogated from distance, its lifetime is almost unlimited. Investigations, focused both on using RFID transponder as a sensing element, as well as, using antenna as a energy harvesting part that could power the sensor circuit, are mentioned. Performed studies show, that despite problems connected with using high frequencies, described wireless sensors should be useful for SHM tasks.

Abstract: This paper presents an application of Lamb-wave-based damage detection under varying temperature conditions. The method used is based on the cointegration technique and wavelet analysis that are partially built on the analysis of non-stationary behaviour and multi-resolution decomposition of time series, respectively. Instead of directly using Lamb wave data for damage detection, two approaches are used: (1) analysis of cointegrating residuals obtained from the cointegration process of Lamb wave responses and (2) analysis of stationary characteristics of the multi-level wavelet decomposed cointegrating residuals. These two approaches are tested on undamaged and damaged aluminium plates exposed to temperature variations. The experimental results show that the method can isolate damage-sensitive features from the temperature effect and reliably detect damage.