An indirect bridge inspection method incorporating a wavelet-based damage indicator and pattern recognition

In recent years, there has been a move towards the development of indirect structural health monitoring (SHM)techniques for bridges; the low-cost vibration-based method presented in this paper is such an approach. It consists of the use of a moving vehicle fitted with accelerometers on its axles and incorporates wavelet analysis and statistical pattern recognition. The aim of the approach is to both detect and locate damage in bridges while reducing the need for direct instrumentation of the bridge. In theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach in detecting damage in a bridge from vehicle accelerations. For this purpose, the accelerations are processed using a continuous wavelet transform as when the axle passes over a damaged section, any discontinuity in the signal would affect the wavelet coefficients. Based on these coefficients, a damage indicator is formulated which can distinguish between different damage levels. However, it is found to be difficult to quantify damage of varying levels when the vehicle’s transverse position is varied between bridge crossings. In a real bridge field experiment, damage was applied artificially to a steel truss bridge to test the effectiveness of the indirect approach in practice; for this purpose a two-axle van was driven across the bridge at constant speed. Both bridge and vehicle acceleration measurements were recorded. The dynamic properties of the test vehicle were identified initially via free vibration tests. It was found that the resulting damage indicators for the bridge and vehicle showed similar patterns, however, it was difficult to distinguish between different artificial damage scenarios.

Mapping neutral, ion and electron number densities within laser ablated plasma plumes

Spatially and temporally varying neutral, ion and electron number densities have been mapped out within laser ablated plasma plumes expanding into vacuum. Ablation of a magnesium target was performed using a KrF laser, 30 ns pulse duration and 248 nm wavelength. During the initial stage of plasma expansion (t <EQ 100 ns) interferometry has been used to obtain line averaged electron number densities, for laser power densities on target in the range 1.3 - 3.0 X 108 W/cm2. Later in the plasma expansion (t equals 1 microsecond(s) ) simultaneous absorption and laser induced fluorescence spectroscopy has been used to determine 3D neutral and ion number densities, for a power density equal to 6.7 X 107 W/cm2. Two distinct regions within the plume were identified. One is a fast component (approximately 106 cm-1) consisting of ions and neutrals with maximum number densities observed to be approximately 30 and 4 X 1012 cm-3 respectively, and the second consists of slow moving neutral material at a number density of up to 1015 cm-3. Additionally a Langmuir probe has been used to obtain ion and electron number densities at very late times in the plasma expansion (1 microsecond(s) <EQ t <EQ 15 microsecond(s) ). A copper target was ablated using a Nd:YAG laser, 7.5 ns duration and 532 nm (2 (omega) ) wavelength, with a power density on target equal to 6 X 108 W/cm2. Two regions within the plume with different velocities were observed. Within a fast component (approximately 3 X 106 cms-1) electron and ion number densities of the order 5 X 1012 cm-3 were observed and within the second slower component (approximately 106 cms-1) electron and ion number densities of the order 1 - 2 X 1013 cm-3 were determined.

Massive stars exploding in a He-rich circumstellar medium - IV. Transitional Type Ibn supernovae

We present ultraviolet, optical and near-infrared data of the Type Ibn supernovae (SNe) 2010al and 2011hw. SN 2010al reaches an absolute magnitude at peak of M-R = -18.86 +/- 0.21. Its early light curve shows similarities with normal SNe Ib, with a rise to maximum slower than most SNe Ibn. The spectra are dominated by a blue continuum at early stages, with narrow P-Cygni He I lines indicating the presence of a slow-moving, He-rich circumstellar medium. At later epochs, the spectra well match those of the prototypical SN Ibn 2006jc, although the broader lines suggest that a significant amount of He was still present in the stellar envelope at the time of the explosion. SN 2011hw is somewhat different. It was discovered after the first maximum, but the light curve shows a double peak. The absolute magnitude at discovery is similar to that of the second peak (M-R = -18.59 +/- 0.25), and slightly fainter than the average of SNe Ibn. Though the spectra of SN 2011hw are similar to those of SN 2006jc, coronal lines and narrow Balmer lines are clearly detected. This indicates substantial interaction of the SN ejecta with He-rich, but not H-free, circumstellar material. The spectra of SN 2011hw suggest that it is a transitional SN Ibn/IIn event similar to SN 2005la. While for SN 2010al the spectrophotometric evolution favours a H-deprived Wolf-Rayet progenitor (of WN-type), we agree with the conclusion of Smith et al. that the precursor of SN 2011hw was likely in transition from a luminous blue variable to an early Wolf-Rayet (Ofpe/WN9) stage.

Identification of damping in a bridge using a moving instrumented vehicle

In recent years, there has been a significant increase in the number of bridges which are being instrumented and monitored on an ongoing basis. This is in part due to the introduction of bridge management systems designed to provide a high level of protection to the public and early warning if the bridge becomes unsafe. This paper investigates a novel alternative; a low-cost method consisting of the use of a vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the damping ratio of the bridge. The method is tested for a range of bridge spans and vehicle velocities using theoretical simulations and the influences of road roughness, initial vibratory condition of the vehicle, signal noise, modelling errors and frequency matching on the accuracy of the results are investigated.

Modal Extraction for Wind Turbines using Moving Window Subspace Identification

This paper proposes a method for wind turbine mode identification using the multivariable output error statespace (MOESP) identification algorithm. The paper incorporates a fast moving window QR decomposition and propagator method from array signal processing, yielding a moving window subspace identification algorithm. The algorithm assumes that the system order is known as a priori and remains constant during identification. For the purpose of extracting modal information for turbines modelled as a linear parameter varying (LPV) system, the algorithm is applicable since a nonlinear system can be approximated as a piecewise time invariant system in consecutive data windows. The algorithm is exemplified using numerical simulations which show that the moving window algorithm can track the modal information. The paper also demonstrates that the low computational burden of the algorithm, compared to conventional batch subspace identification, has significant implications for online implementation.

Identification of Road Irregularities via Vehicle Accelerations

A periodic monitoring of the pavement condition facilitates a cost-effective distribution of the resources available for maintenance of the road infrastructure network. The task can be accurately carried out using profilometers, but such an approach is generally expensive. This paper presents a method to collect information on the road profile via accelerometers mounted in a fleet of non-specialist vehicles, such as police cars, that are in use for other purposes. It proposes an optimisation algorithm, based on Cross Entropy theory, to predict road irregularities. The Cross Entropy algorithm estimates the height of the road irregularities from vehicle accelerations at each point in time. To test the algorithm, the crossing of a half-car roll model is simulated over a range of road profiles to obtain accelerations of the vehicle sprung and unsprung masses. Then, the simulated vehicle accelerations are used as input in an iterative procedure that searches for the best solution to the inverse problem of finding road irregularities. In each iteration, a sample of road profiles is generated and an objective function defined as the sum of squares of differences between the ‘measured’ and predicted accelerations is minimized until convergence is reached. The reconstructed profile is classified according to ISO and IRI recommendations and compared to its original class. Results demonstrate that the approach is feasible and that a good estimate of the short-wavelength features of the road profile can be detected, despite the variability between the vehicles used to collect the data.

The design of a navigation guidance and control system for an unmanned surface vehicle for environmental monitoring

Maintaining the ecosystem is one of the main concerns in this modern age. With the fear of ever-increasing global warming, the UK is one of the key players to participate actively in taking measures to slow down at least its phenomenal rate. As an ingredient to this process, the Springer vehicle was designed and developed for environmental monitoring and pollutant tracking. This special issue paper highlighted the Springer hardware and software architecture including various navigational sensors, a speed controller, and an environmental monitoring unit. In addition, details regarding the modelling of the vessel were outlined based mainly on experimental data. The formulation of a fault tolerant multi-sensor data fusion technique was also presented. Moreover, control strategy based on a linear quadratic Gaussian controller was developed and simulated on the Springer model.
Gaussian controller is developed and simulated on the Springer model.

Development of a novel PCR assay for the identification of the black yeast, Exophiala (Wangiella) dermatitidis from adult patients with cystic fibrosis (CF)

Cystic fibrosis (CF) patients may suffer increased morbidity and mortality through colonisation, allergy and invasive infection from fungi. The black yeast, Exophiala dermatitidis (synonym Wangiella dermatitidis) has been found with increasing frequency in sputum specimens of CF patients, with reported isolation rates ranging from 1.1 to 15.7%. At present, no diagnostic PCR exists to aid with the clinical laboratory detection and identification of this organism. A novel species-specific PCR-based assay was developed for the detection of E. dermatitidis, based on employment of rDNA operons and interspacer (ITS) regions between these rDNA operons. Two novel primers, (designated ExdF & ExdR) were designed in silico with the aid of computer-aided alignment software and with the alignment of multiple species of Exophiala, as well as with other commonly described yeasts and filamentous fungi within CF sputum, including Candida. Aspergillus and Scedosporium. An amplicon of approximately 455 by was generated, spanning the partial ITS I region - the complete 5.8S rDNA region - partial ITS2 region, employing ExdF (forward primer [16-mer], 5'-CCG CCT ATT CAG GTC C-3' and ExdR (reverse primer [16-mer], 5'-TCT CTC CCA CTC CCG C-3', was employed and optimised on extracted genomic DNA from a well characterised culture of E. dermatitidis, as well as with high quality genomic DNA template from a further 16 unrelated fungi, including Candida albicans, C. dubliniensis, C. parapsilosis, C. glabrata, Scedosporium apiospermum, Penicillium sp., Aspergillus fumigatus, Aspergillus versicolor, Pichia guilliermondii, Rhodotorula sp., Trichosporon sp., Aureobasidium pullulans, Fusarium sp., Mucor hiemalis, Bionectria ochroleuca, Gibberella pulicaris. Results demonstrated that only DNA from E. dermatitidis gave an amplification product of the expected sire, whilst none of the other fungi were amplifiable. Subsequent employment of this primer pair detected this yeast from mycological cultures from 2/50 (4%) adult CF patients. These two patients were the only patients who were previously shown to have a cultural history of E. dermatitidis from their sputum. E. dermatitidis is a slow-growing fungus, which usually takes up to two weeks to culture in the microbiology laboratory and therefore is slow to detect conventionally, with the risk of bacterial overgrowth from common co-habiting pan- and multiresistant bacterial pathogens from sputum. namely Pseudomonas aeruginosa and Burkholderia cepacia complex organisms, hence this species-specific PCR assay may help detect this organism from CF sputum more specifically and rapidly. Overall, employment of this novel assay nay help in the understanding of the occurrence. aetiology and epidemiology of E. dermatitidis, as an emerging fungal agent in patients with CF. (C) 2008 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

A wavelet-based damage detection algorithm based on bridge acceleration response to a vehicle

Previous research based on theoretical simulations has shown the potential of the wavelet transform to detect damage in a beam by analysing the time-deflection response due to a constant moving load. However, its application to identify damage from the response of a bridge to a vehicle raises a number of questions. Firstly, it may be difficult to record the difference in the deflection signal between a healthy and a slightly damaged structure to the required level of accuracy and high scanning frequencies in the field. Secondly, the bridge is going to have a road profile and it will be loaded by a sprung vehicle and time-varying forces rather than a constant load. Therefore, an algorithm based on a plot of wavelet coefficients versus time to detect damage (a singularity in the plot) appears to be very sensitive to noise. This paper addresses these questions by: (a) using the acceleration signal, instead of the deflection signal, (b) employing a vehicle-bridge finite element interaction model, and (c) developing a novel wavelet-based approach using wavelet energy content at each bridge section which proves to be more sensitive to damage than a wavelet coefficient line plot at a given scale as employed by others.

'Someone Big and Important': Identification and Affect in an International Development Organization

Psychoanalysis has been widely used to develop our understanding of power in organizations. In this paper, I draw on a case study of a non-profit organization in the field of international development, in order to explore in depth how people engage with powerful discourses at play in this context. I use an ethnographic approach to do so, and find Lacan's ideas on identification and affect to be useful in the analysis of the case. I show how, at first glance, people appeared to readily alter their activities and goals in response to the wishes of an important donor. However, moving deeper to examine identifications on the part of people themselves reveals complex forms of recognition that were inscribed by affective relations. I discuss the implications of these findings for the study of organizations, including the contribution of the concept of affect for studies of identification and subjection in organizations, and the value of ethnographic research approaches that draw upon Lacan's work on recognition.

An investigation into the acceleration response of a damaged beam-type structure to a moving force

In recent years there have been a growing number of publications on procedures for damage detection in beams from analysing their dynamic response to the passage of a moving force. Most of this research demonstrates their effectiveness by showing that a singularity that did not appear in the healthy structure is present in the response of the damaged structure. This paper elucidates from first principles how the acceleration response can be assumed to consist of ‘static’ and ‘dynamic’ components, and where the beam has experienced a localised loss in stiffness, an additional ‘damage’ component. The combination of these components establishes how the damage singularity will appear in the total response. For a given damage severity, the amplitude of the ‘damage’ component will depend on how close the damage location is to the sensor, and its frequency content will increase with higher velocities of the moving force. The latter has implications for damage detection because if the frequency content of the ‘damage’ component includes bridge and/or vehicle frequencies, it becomes more difficult to identify damage. The paper illustrates how a thorough understanding of the relationship between the ‘static‘ and ‘damage’ components contributes to establish if damage has occurred and to provide an estimation of its location and severity. The findings are corroborated using accelerations from a planar finite element simulation model where the effects of force velocity and bridge span are examined.