Composite materials impact damage detection using neural networks

This thesis considers two basic aspects of impact damage in composite materials, namely damage severity discrimination and impact damage location by using Acoustic Emissions (AE) and Artificial Neural Networks (ANNs). The experimental work embodies a study of such factors as the application of AE as Non-destructive Damage Testing (NDT), and the evaluation of ANNs modelling. ANNs, however, played an important role in modelling implementation. In the first aspect of the study, different impact energies were used to produce different level of damage in two composite materials (T300/914 and T800/5245). The impacts were detected by their acoustic emissions (AE). The AE waveform signals were analysed and modelled using a Back Propagation (BP) neural network model. The Mean Square Error (MSE) from the output was then used as a damage indicator in the damage severity discrimination study. To evaluate the ANN model, a comparison was made of the correlation coefficients of different parameters, such as MSE, AE energy, AE counts, etc. MSE produced an outstanding result based on the best performance of correlation. In the second aspect, a new artificial neural network model was developed to provide impact damage location on a quasi-isotropic composite panel. It was successfully trained to locate impact sites by correlating the relationship between arriving time differences of AE signals at transducers located on the panel and the impact site coordinates. The performance of the ANN model, which was evaluated by calculating the distance deviation between model output and real location coordinates, supports the application of ANN as an impact damage location identifier. In the study, the accuracy of location prediction decreased when approaching the central area of the panel. Further investigation indicated that this is due to the small arrival time differences, which defect the performance of ANN prediction. This research suggested increasing the number of processing neurons in the ANNs as a practical solution.

The uncertainty of identity toolset:analysing digital traces for user profiling

People manage a spectrum of identities in cyber domains. Profiling individuals and assigning them to distinct groups or classes have potential applications in targeted services, online fraud detection, extensive social sorting, and cyber-security. This paper presents the Uncertainty of Identity Toolset, a framework for the identification and profiling of users from their social media accounts and e-mail addresses. More specifically, in this paper we discuss the design and implementation of two tools of the framework. The Twitter Geographic Profiler tool builds a map of the ethno-cultural communities of a person's friends on Twitter social media service. The E-mail Address Profiler tool identifies the probable identities of individuals from their e-mail addresses and maps their geographical distribution across the UK. To this end, this paper presents a framework for profiling the digital traces of individuals.

Immunochemical detection of UV-induced DNA damage and repair

The application of an antiserum to ultraviolet radiation (UVR)-damaged DNA is presented. A novel experimental system was employed to ascertain the limits of detection for this antiserum. Using a DNA standard containing a known amount of dimer, the limits of detection were found to be 0.9 fmol of dimer. This was compared to a limit of 20-50 fmol dimer using gas chromatography-mass spectrometry (GC-MS). Induction of thymine dimers in DNA following UVR exposure, as assessed using this antiserum in an enzyme-linked immunosorbent assay (ELISA), was compared with GC-MS measurements. The ELISA method successfully demonstrated the induction of lesions in DNA irradiated either with UVC or UVB, although despite high sensitivity, no discernible binding was seen to UVA-irradiated DNA. The antiserum was also shown to be applicable to immunocytochemistry, localising damage in the nuclei of UVR exposed keratinocytes in culture. The ability of the antiserum to detect DNA damage in skin biopsies of individuals exposed to sub-erythemal doses of UVR was also demonstrated. Moreover, the subsequent removal of this damage, as evidenced by a reduction in antiserum staining, was noted in sections of biopsies taken in the hours following irradiation. © 2003 Elsevier B.V. All rights reserved.

Immunochemical detection of glyoxal DNA damage

The relevance of reactive oxygen species (ROS) in the pathogenesis of inflammatory diseases is widely documented. Immunochemical detection of ROS DNA adducts has been developed, however, recognition of glyoxal-DNA adducts has not previously been described. We have generated a polyclonal antibody that has shown increased antibody binding to ROS-modified DNA in comparison to native DNA. In addition, dose-dependent antibody binding to DNA modified with ascorbate alone was shown, with significant inhibition by desferrioxamine, catalase, and ethanol. Minimal inhibition was observed with uric acid, 1,10-phenanthroline and DMSO. However, antibody binding in the presence of EDTA increased 3500-fold. The involvement of hydrogen peroxide and hydroxyl radical in ascorbate-mediated DNA damage is consistent with ascorbate acting as a reducing agent for DNA-bound metal ions. Glyoxal is known to be formed during oxidation of ascorbate. Glyoxylated DNA, that previously had been proposed as a marker of oxidative damage, was recognised in a dose dependent manner using the antibody. We describe the potential use of our anti-ROS DNA antibody, that detects predominantly Fenton-type mediated damage to DNA and report on its specificity for the recognition of glyoxal-DNA adducts.

Online trendy topics detection in microblogs with selective user monitoring under cost constraints

As microblog services such as Twitter become a fast and convenient communication approach, identification of trendy topics in microblog services has great academic and business value. However detecting trendy topics is very challenging due to huge number of users and short-text posts in microblog diffusion networks. In this paper we introduce a trendy topics detection system under computation and communication resource constraints. In stark contrast to retrieving and processing the whole microblog contents, we develop an idea of selecting a small set of microblog users and processing their posts to achieve an overall acceptable trendy topic coverage, without exceeding resource budget for detection. We formulate the selection operation of these subset users as mixed-integer optimization problems, and develop heuristic algorithms to compute their approximate solutions. The proposed system is evaluated with real-time test data retrieved from Sina Weibo, the dominant microblog service provider in China. It's shown that by monitoring 500 out of 1.6 million microblog users and tracking their microposts (about 15,000 daily) with our system, nearly 65% trendy topics can be detected, while on average 5 hours earlier before they appear in Sina Weibo official trends.

Cost-effective node monitoring for online hot event detection in sina weibo microblogging

We propose a cost-effective hot event detection system over Sina Weibo platform, currently the dominant microblogging service provider in China. The problem of finding a proper subset of microbloggers under resource constraints is formulated as a mixed-integer problem for which heuristic algorithms are developed to compute approximate solution. Preliminary results show that by tracking about 500 out of 1.6 million candidate microbloggers and processing 15,000 microposts daily, 62% of the hot events can be detected five hours on average earlier than they are published by Weibo.

Damage analysis of bridge structures using vibrational techniques

Much research is currently centred on the detection of damage in structures using vibrational data. The work presented here examined several areas of interest in support of a practical technique for identifying and locating damage within bridge structures using apparent changes in their vibrational response to known excitation. The proposed goals of such a technique included the need for the measurement system to be operated on site by a minimum number of staff and that the procedure should be as non-invasive to the bridge traffic-flow as possible. Initially the research investigated changes in the vibrational bending characteristics of two series of large-scale model bridge-beams in the laboratory and these included ordinary-reinforced and post-tensioned, prestressed designs. Each beam was progressively damaged at predetermined positions and its vibrational response to impact excitation was analysed. For the load-regime utilised the results suggested that the infuced damage manifested itself as a function of the span of a beam rather than a localised area. A power-law relating apparent damage with the applied loading and prestress levels was then proposed, together with a qualitative vibrational measure of structural damage. In parallel with the laboratory experiments a series of tests were undertaken at the sites of a number of highway bridges. The bridges selected had differing types of construction and geometric design including composite-concrete, concrete slab-and-beam, concrete-slab with supporting steel-troughing constructions together with regular-rectangular, skewed and heavily-skewed geometries. Initial investigations were made of the feasibility and reliability of various methods of structure excitation including traffic and impulse methods. It was found that localised impact using a sledge-hammer was ideal for the purposes of this work and that a cartridge `bolt-gun' could be used in some specific cases.

Protein oxidative modifications:new mass spectrometry approaches to detection in biological samples

In inflammatory diseases, release of oxidants leads to oxidative damage to proteins. The precise nature of oxidative damage to individual proteins depends on the oxidant involved. Chlorination and nitration are markers of modification by the myeloperoxidase-H2O2-Cl- system and nitric oxide-derived oxidants, respectively. Although these modifications can be detected by western blotting, currently no reliable method exists to identify the specific sites damage to individual proteins in complex mixtures such as clinical samples. We are developing novel LCMS2 and precursor ion scanning methods to address this. LC-MS2 allows separation of peptides and detection of mass changes in oxidized residues on fragmentation of the peptides. We have identified indicative fragment ions for chlorotyrosine, nitrotyrosine, hydroxytyrosine and hydroxytryptophan. A nano-LC/MS3 method involving the dissociation of immonium ions to give specific fragments for the oxidized residues has been developed to overcome the problem of false positives from ions isobaric to these immonium ions that exist in unmodified peptides. The approach has proved able to identify precise protein modifications in individual proteins and mixtures of proteins. An alternative methodology involves multiple reaction monitoring for precursors and fragment ions are specific to oxidized and chlorinated proteins, and this has been tested with human serum albumin. Our ultimate aim is to apply this methodology to the detection of oxidative post-translational modifications in clinical samples for disease diagnosis, monitoring the outcomes of therapy, and improved understanding of disease biochemistry.

Detection of phospholipid oxidation in oxidatively stressed cells by reversed-phase HPLC coupled with positive-ionization electrospray MS

Measurement of lipid peroxidation is a commonly used method of detecting oxidative damage to biological tissues, but the most frequently used methods, including MS, measure breakdown products and are therefore indirect. We have coupled reversed-phase HPLC with positive-ionization electrospray MS (LC-MS) to provide a method for separating and detecting intact oxidized phospholipids in oxidatively stressed mammalian cells without extensive sample preparation. The elution profile of phospholipid hydroperoxides and chlorohydrins was first characterized using individual phospholipids or a defined phospholipid mixture as a model system. The facility of detection of the oxidized species in complex mixtures was greatly improved compared with direct-injection MS analysis, as they eluted earlier than the native lipids, owing to the decrease in hydrophobicity. In U937 and HL60 cells treated in vitro with t-butylhydroperoxide plus Fe2+, lipid oxidation could not be observed by direct injection, but LC-MS allowed the detection of monohydroperoxides of palmitoyl-linoleoyl and stearoyl-linoleoyl phosphatidylcholines. The levels of hydroperoxides observed in U937 cells were found to depend on the duration and severity of the oxidative stress. In cells treated with HOCl, chlorohydrins of palmitoyloleoyl phosphatidylcholine were observed by LC-MS. The method was able to detect very small amounts of oxidized lipids compared with the levels of native lipids present. The membrane-lipid profiles of these cells were found to be quite resistant to damage until high concentrations of oxidants were used. This is the first report of direct detection by LC-MS of intact oxidized phospholipids induced in cultured cells subjected to oxidative stress.

Graphene-based D-shaped polymer FBG for highly sensitive erythrocyte detection

Graphene-based silica fiber-optic sensors, with high sensitivity, fast response, and low cost, have shown great promise for gas sensing applications. In this letter, by covering a monolayer of p-doped graphene on a D-shaped microstructured polymer fiber Bragg grating (FBG), we propose and demonstrate a novel biochemical probe sensor, the graphene-based D-shaped polymer FBG (GDPFBG). Due to the graphene-based surface evanescent field enhancement, this sensor shows high sensitivity to detect surrounding biochemical parameters. By monitoring the Bragg peak locations of the GDPFBG online, human erythrocyte (red blood cell) solutions with different cellular concentrations ranging from 0 to 104 ppm were detected precisely, with the maximum resolution of sub-ppm. Such a sensor is structurally compact, is clinically acceptable, and provides good recoverability, offering a state-of-the-art polymer-fiber-based sensing platform for highly sensitive in situ and in vivo cell detection applications.

Interpretation of the Superpave IDT strength test using a viscoelastic-damage constitutive model

This paper presents a new interpretation for the Superpave IDT strength test based on a viscoelastic-damage framework. The framework is based on continuum damage mechanics and the thermodynamics of irreversible processes with an anisotropic damage representation. The new approach introduces considerations for the viscoelastic effects and the damage accumulation that accompanies the fracture process in the interpretation of the Superpave IDT strength test for the identification of the Dissipated Creep Strain Energy (DCSE) limit from the test result. The viscoelastic model is implemented in a Finite Element Method (FEM) program for the simulation of the Superpave IDT strength test. The DCSE values obtained using the new approach is compared with the values obtained using the conventional approach to evaluate the validity of the assumptions made in the conventional interpretation of the test results. The result shows that the conventional approach over-estimates the DCSE value with increasing estimation error at higher deformation rates.

Online sensorless position estimation for switched reluctance motors using one current sensor

This paper proposes an online sensorless rotor position estimation technique for switched reluctance motors (SRMs) using just one current sensor. It is achieved by first decoupling the excitation current from the bus current. Two phase-shifted pulse width modulation signals are injected into the relevant lower transistors in the asymmetrical half-bridge converter for short intervals during each current fundamental cycle. Analog-to-digital converters are triggered in the pause middles of the dual pulse to separate the bus current for excitation current recognition. Next, the rotor position is estimated from the excitation current, by a current-rise-time method in the current-chopping-control mode in a low-speed operation and a current-gradient method in the voltage-pulse-control mode in a high-speed operation. The proposed scheme requires only a bus current sensor and a minor change to the converter circuit, without a need for individual phase current sensors or additional detection devices, achieving a more compact and cost-effective drive. The performance of the sensorless SRM drive is fully investigated. The simulation and experiments on a 750-W three-phase 12/8-pole SRM are carried out to verify the effectiveness of the proposed scheme.

Fault diagnosis scheme for open-circuit faults in switched reluctance motor drives using fast Fourier transform algorithm with bus current detection

Reliability of power converters is of crucial importance in switched reluctance motor drives used for safety-critical applications. Open-circuit faults in power converters will cause the motor to run in unbalanced states, and if left untreated, they will lead to damage to the motor and power modules, and even cause a catastrophic failure of the whole drive system. This study is focused on using a single current sensor to detect open-circuit faults accurately. An asymmetrical half-bridge converter is considered in this study and the faults of single-phase open and two-phase open are analysed. Three different bus positions are defined. On the basis of a fast Fourier transform algorithm with Blackman window interpolation, the bus current spectrums before and after open-circuit faults are analysed in details. Their fault characteristics are extracted accurately by the normalisations of the phase fundamental frequency component and double phase fundamental frequency component, and the fault characteristics of the three bus detection schemes are also compared. The open-circuit faults can be located by finding the relationship between the bus current and rotor position. The effectiveness of the proposed diagnosis method is validated by the simulation results and experimental tests.

Optimisation of chromatographic separation of oxidised phospholipids and detection with targeted approaches provides greater coverage of the oxidised lipidome

Phospholipid oxidation by adventitious damage generates a wide variety of products with potentially novel biological activities that can modulate inflammatory processes associated with various diseases. To understand the biological importance of oxidised phospholipids (OxPL) and their potential role as disease biomarkers requires precise information about the abundance of these compounds in cells and tissues. There are many chemiluminescence and spectrophotometric assays available for detecting oxidised phospholipids, but they all have some limitations. Mass spectrometry coupled with liquid chromatography is a powerful and sensitive approach that can provide detailed information about the oxidative lipidome, but challenges still remain. The aim of this work is to develop improved methods for detection of OxPLs by optimisation of chromatographic separation through testing several reverse phase columns and solvent systems, and using targeted mass spectrometry approaches. Initial experiments were carried out using oxidation products generated in vitro to optimise the chromatography separation parameters and mass spectrometry parameters. We have evaluated the chromatographic separation of oxidised phosphatidylcholines (OxPCs) and oxidised phosphatidylethanolamines (OXPEs) using C8, C18 and C30 reverse phase, polystyrene – divinylbenzene based monolithic and mixed – mode hydrophilic interaction (HILIC) columns, interfaced with mass spectrometry. Our results suggest that the monolithic column was best able to separate short chain OxPCs and OxPEs from long chain oxidised and native PCs and PEs. However, variation in charge of polar head groups and extreme diversity of oxidised species make analysis of several classes of OxPLs within one analytical run impractical. We evaluated and optimised the chromatographic separation of OxPLs by serially coupling two columns: HILIC and monolith column that provided us the larger coverage of OxPL species in a single analytical run.