Regional field measurement of soil moisture content with neutron probe

The neutron logging method has been widely used for field measurement of soil moisture content. This non-destructive method permitted the measurement of in-situ soil moisture content at various depths without the need for burying any sensor. Twenty-three sites located around regional Melbourne have been selected for long term monitoring of soil moisture content using neutron probe. Soil samples collected during the installation are used for site characterisation and neutron probe calibration purposes. A linear relationship is obtained between the corrected neutron probe reading and moisture content for both the individual and combined data from seven sites. It is observed that the liner relationship, developed using combined data, can be used for all sites with an average accuracy of about 80%. Monitoring of the variation of soil moisture content with depth in six months for two sites is presented in this paper.

Cytochrome p450 isozyme protein verified in the skin of southern hemisphere humpback whales (megaptera novaeangliae) : implications for biochemical biomarker assessment

Large mysticete whales represent a unique challenge for chemical risk assessment. Few epidemiological investigations are possible due to the low incidence of adult stranding events. Similarly their often extreme life-history adaptations of prolonged migration and fasting challenge exposure assumptions. Molecular biomarkers offer the potential to complement information yielded through tissue chemical analysis, as well as providing evidence of a molecular response to chemical exposure. In this study we confirm the presence of cytochrome P450 reductase (CPR) and cytochrome P450 isoenzyme 1A1 (CYP1A1) in epidermal tissue of southern hemisphere humpback whales (Megaptera novaeangliae). The detection of CYP1A1 in the integument of the humpback whale affords the opportunity for further quantitative non-destructive investigations of enzyme activity as a function of chemical stress.

Use of acoustic emission technique for structural health monitoring of bridges

Bridges are valuable assets of every nation. They deteriorate with age and often are subjected to additional loads or different load patterns than originally designed for. These changes in loads can cause localized distress and may result in bridge failure if not corrected in time. Early detection of damage and appropriate retrofitting will aid in preventing bridge failures. Large amounts of money are spent in bridge maintenance all around the world. A need exists for a reliable technology capable of monitoring the structural health of bridges, thereby ensuring they operate safely and efficiently during the whole intended lives. Monitoring of bridges has been traditionally done by means of visual inspection. Visual inspection alone is not capable of locating and identifying all signs of damage, hence a variety of structural health monitoring (SHM) techniques is used regularly nowadays to monitor performance and to assess condition of bridges for early damage detection. Acoustic emission (AE) is one technique that is finding an increasing use in SHM applications of bridges all around the world. The chapter starts with a brief introduction to structural health monitoring and techniques commonly used for monitoring purposes. Acoustic emission technique, wave nature of AE phenomenon, previous applications and limitations and challenges in the use as a SHM technique are also discussed. Scope of the project and work carried out will be explained, followed by some recommendations of work planned in future.

Review: acoustic emission technique - opportunities, challenges and current work at QUT

Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. AE is one of the several non-destructive testing (NDT) techniques currently used for structural health monitoring (SHM) of civil, mechanical and aerospace structures. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. Despite these advantages, several challenges still exist in successful application of AE monitoring. Accurate localization of AE sources, discrimination between genuine AE sources and spurious noise sources and damage quantification for severity assessment are some of the important issues in AE testing and will be discussed in this paper. Various data analysis and processing approaches will be applied to manage those issues.

Damage detection in truss bridges using vibration based multi-criteria approach

This paper uses dynamic computer simulation techniques to develop and apply a multi-criteria procedure using non-destructive vibration-based parameters for damage assessment in truss bridges. In addition to changes in natural frequencies, this procedure incorporates two parameters, namely the modal flexibility and the modal strain energy. Using the numerically simulated modal data obtained through finite element analysis of the healthy and damaged bridge models, algorithms based on modal flexibility and modal strain energy changes before and after damage are obtained and used as the indices for the assessment of structural health state. The application of the two proposed parameters to truss-type structures is limited in the literature. The proposed multi-criteria based damage assessment procedure is therefore developed and applied to truss bridges. The application of the approach is demonstrated through numerical simulation studies of a single-span simply supported truss bridge with eight damage scenarios corresponding to different types of deck and truss damage. Results show that the proposed multi-criteria method is effective in damage assessment in this type of bridge superstructure.

Design and development of automatic visual inspection system for PCB manufacturing

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. This paper proposes two inspection modules for an automatic solder joint classification system. The “front-end” inspection system includes illumination normalisation, localisation and segmentation. The “back-end” inspection involves the classification of solder joints using the Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. The Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. This system could contribute to the development of automated non-contact, non-destructive and low cost solder joint quality inspection systems.

Characterizing the signal pattern of a four-cylinder diesel engine using acoustic emission and vibration analysis

Condition monitoring of diesel engines can prevent unpredicted engine failures and the associated consequence. This paper presents an experimental study of the signal characteristics of a 4-cylinder diesel engine under various loading conditions. Acoustic emission, vibration and in-cylinder pressure signals were employed to study the effectiveness of these techniques for condition monitoring and identifying symptoms of incipient failures. An event driven synchronous averaging technique was employed to average the quasi-periodic diesel engine signal in the time domain to eliminate or minimize the effect of engine speed and amplitude variations on the analysis of condition monitoring signal. It was shown that acoustic emission (AE) is a better technique than vibration method for condition monitor of diesel engines due to its ability to produce high quality signals (i.e., excellent signal to noise ratio) in a noisy diesel engine environment. It was found that the peak amplitude of AE RMS signals correlating to the impact-like combustion related events decreases in general due to a more stable mechanical process of the engine as the loading increases. A small shift in the exhaust valve closing time was observed as the engine load increases which indicates a prolong combustion process in the cylinder (to produce more power). On the contrary, peak amplitudes of the AE RMS attributing to fuel injection increase as the loading increases. This can be explained by the increase fuel friction caused by the increase volume flow rate during the injection. Multiple AE pulses during the combustion process were identified in the study, which were generated by the piston rocking motion and the interaction between the piston and the cylinder wall. The piston rocking motion is caused by the non-uniform pressure distribution acting on the piston head as a result of the non-linear combustion process of the engine. The rocking motion ceased when the pressure in the cylinder chamber stabilized.

Photochemistry and chemometrics : an overview

Photochemistry has made significant contributions to our understanding of many important natural processes as well as the scientific discoveries of the man-made world. The measurements from such studies are often complex and may require advanced data interpretation with the use of multivariate or chemometrics methods. In general, such methods have been applied successfully for data display, classification, multivariate curve resolution and prediction in analytical chemistry, environmental chemistry, engineering, medical research and industry. However, in photochemistry, by comparison, applications of such multivariate approaches were found to be less frequent although a variety of methods have been used, especially with spectroscopic photochemical applications. The methods include Principal Component Analysis (PCA; data display), Partial Least Squares (PLS; prediction), Artificial Neural Networks (ANN; prediction) and several models for multivariate curve resolution related to Parallel Factor Analysis (PARAFAC; decomposition of complex responses). Applications of such methods are discussed in this overview and typical examples include photodegradation of herbicides, prediction of antibiotics in human fluids (fluorescence spectroscopy), non-destructive in- and on-line monitoring (near infrared spectroscopy) and fast-time resolution of spectroscopic signals from photochemical reactions. It is also quite clear from the literature that the scope of spectroscopic photochemistry was enhanced by the application of chemometrics. To highlight and encourage further applications of chemometrics in photochemistry, several additional chemometrics approaches are discussed using data collected by the authors. The use of a PCA biplot is illustrated with an analysis of a matrix containing data on the performance of photocatalysts developed for water splitting and hydrogen production. In addition, the applications of the Multi-Criteria Decision Making (MCDM) ranking methods and Fuzzy Clustering are demonstrated with an analysis of water quality data matrix. Other examples of topics include the application of simultaneous kinetic spectroscopic methods for prediction of pesticides, and the use of response fingerprinting approach for classification of medicinal preparations. In general, the overview endeavours to emphasise the advantages of chemometrics' interpretation of multivariate photochemical data, and an Appendix of references and summaries of common and less usual chemometrics methods noted in this work, is provided. Crown Copyright © 2010.

Infrared and Raman spectroscopic studies of archaeological materials

The use of vibrational spectroscopic techniques to characterise historical artefacts and art works continues to grow and to provide the archaeologist and art historian with significant information with which to understand the nature and activities of previous peoples and civilizations. In addition, conservators can gain knowledge of the composition of artworks or historical objects and so are better equipped to ensure their preservation. Both infrared and Raman have been widely used. Microspectroscopy is the preferred sampling technique as it requires only a very small sample, which often can be recovered. The use of synchrotron radiation in conjunction with IR microspectroscopy is increasing because of the substantial benefits in terms of improved spatial resolution and signal-to-noise ratio. The key trend for the future is the growth in the use of portable instruments, both IR and Raman, which are becoming important because they allow non-destructive measurements to be made in situ, for example at an archaeological site or at a museum.

Simulation of AE wave propagation in thin plate for source identification

In most materials, short stress waves are generated during the process of plastic deformation, phase transformation, crack formation and crack growth. These phenomena are applied in acoustic emission (AE) for the detection of material defects in wide spectrum areas, ranging from non-destructive testing for the detection of materials defects to monitoring of microeismical activity. AE technique is also used for defect source identification and for failure detection. AE waves consist of P waves (primary/longitudinal waves), S waves (shear/transverse waves) and Rayleight (surface) waves as well as reflected and diffracted waves. The propagation of AE waves in various modes has made the determination of source location difficult. In order to use the acoustic emission technique for accurate identification of source location, an understanding of wave propagation of the AE signals at various locations in a plate structure is essential. Furthermore, an understanding of wave propagation can also assist in sensor location for optimum detection of AE signals. In real life, as the AE signals radiate from the source it will result in stress waves. Unless the type of stress wave is known, it is very difficult to locate the source when using the classical propagation velocity equations. This paper describes the simulation of AE waves to identify the source location in steel plate as well as the wave modes. The finite element analysis (FEA) is used for the numerical simulation of wave propagation in thin plate. By knowing the type of wave generated, it is possible to apply the appropriate wave equations to determine the location of the source. For a single plate structure, the results show that the simulation algorithm is effective to simulate different stress waves.

Effective discrimination of acoustic emission source signals for structural health monitoring

Acoustic emission (AE) is the phenomenon where stress waves are generated due to rapid release of energy within a material caused by sources such as crack initiation or growth. AE technique involves recording the stress waves by means of sensors and subsequent analysis of the recorded signals to gather information about the nature of the source. Though AE technique is one of the popular non destructive evaluation (NDE) techniques for structural health monitoring of mechanical, aerospace and civil structures; several challenges still exist in successful application of this technique. Presence of spurious noise signals can mask genuine damage‐related AE signals; hence a major challenge identified is finding ways to discriminate signals from different sources. Analysis of parameters of recorded AE signals, comparison of amplitudes of AE wave modes and investigation of uniqueness of recorded AE signals have been mentioned as possible criteria for source differentiation. This paper reviews common approaches currently in use for source discrimination, particularly focusing on structural health monitoring of civil engineering structural components such as beams; and further investigates the applications of some of these methods by analyzing AE data from laboratory tests.

Near Infrared Spectroscopy Evaluation of Articular Cartilage : Decision-Making in Arthroplasty : Real-Time Assessment of Articular Cartilage

Current diagnostic methods for assessing the severity of articular cartilage degenerative conditions, such as osteoarthritis, are inadequate. There is also a lack of techniques that can be used for real-time evaluation of the tissue during surgery to inform treatment decision and eliminate subjectivity. This book, derived from Dr Afara’s doctoral research, presents a scientific framework that is based on near infrared (NIR) spectroscopy for facilitating the non-destructive evaluation of articular cartilage health relative to its structural, functional, and mechanical properties. This development is a component of the ongoing research on advanced endoscopic diagnostic techniques in the Articular Cartilage Biomechanics Research Laboratory of Professor Adekunle Oloyede at Queensland University of Technology (QUT), Brisbane Australia.

Damage assessment in reinforced concrete flexural members using modal strain energy based method

Damage assessment (damage detection, localization and quantification) in structures and appropriate retrofitting will enable the safe and efficient function of the structures. In this context, many Vibration Based Damage Identification Techniques (VBDIT) have emerged with potential for accurate damage assessment. VBDITs have achieved significant research interest in recent years, mainly due to their non-destructive nature and ability to assess inaccessible and invisible damage locations. Damage Index (DI) methods are also vibration based, but they are not based on the structural model. DI methods are fast and inexpensive compared to the model-based methods and have the ability to automate the damage detection process. DI method analyses the change in vibration response of the structure between two states so that the damage can be identified. Extensive research has been carried out to apply the DI method to assess damage in steel structures. Comparatively, there has been very little research interest in the use of DI methods to assess damage in Reinforced Concrete (RC) structures due to the complexity of simulating the predominant damage type, the flexural crack. Flexural cracks in RC beams distribute non- linearly and propagate along all directions. Secondary cracks extend more rapidly along the longitudinal and transverse directions of a RC structure than propagation of existing cracks in the depth direction due to stress distribution caused by the tensile reinforcement. Simplified damage simulation techniques (such as reductions in the modulus or section depth or use of rotational spring elements) that have been extensively used with research on steel structures, cannot be applied to simulate flexural cracks in RC elements. This highlights a big gap in knowledge and as a consequence VBDITs have not been successfully applied to damage assessment in RC structures. This research will address the above gap in knowledge and will develop and apply a modal strain energy based DI method to assess damage in RC flexural members. Firstly, this research evaluated different damage simulation techniques and recommended an appropriate technique to simulate the post cracking behaviour of RC structures. The ABAQUS finite element package was used throughout the study with properly validated material models. The damaged plasticity model was recommended as the method which can correctly simulate the post cracking behaviour of RC structures and was used in the rest of this study. Four different forms of Modal Strain Energy based Damage Indices (MSEDIs) were proposed to improve the damage assessment capability by minimising the numbers and intensities of false alarms. The developed MSEDIs were then used to automate the damage detection process by incorporating programmable algorithms. The developed algorithms have the ability to identify common issues associated with the vibration properties such as mode shifting and phase change. To minimise the effect of noise on the DI calculation process, this research proposed a sequential order of curve fitting technique. Finally, a statistical based damage assessment scheme was proposed to enhance the reliability of the damage assessment results. The proposed techniques were applied to locate damage in RC beams and slabs on girder bridge model to demonstrate their accuracy and efficiency. The outcomes of this research will make a significant contribution to the technical knowledge of VBDIT and will enhance the accuracy of damage assessment in RC structures. The application of the research findings to RC flexural members will enable their safe and efficient performance.

Distribution of conjunctival ultraviolet autoflourescence in a population-based study : the Norfolk Island Eye Study

OBJECTIVE: The objective of this study was to describe the distribution of conjunctival ultraviolet autofluorescence (UVAF) in an adult population. METHODS: We conducted a cross-sectional, population-based study in the genetic isolate of Norfolk Island, South Pacific Ocean. In all, 641 people, aged 15 to 89 years, were recruited. UVAF and standard (control) photographs were taken of the nasal and temporal interpalpebral regions bilaterally. Differences between the groups for non-normally distributed continuous variables were assessed using the Wilcoxon-Mann-Whitney ranksum test. Trends across categories were assessed using Cuzick's non-parametric test for trend or Kendall's rank correlation τ. RESULTS: Conjunctival UVAF is a non-parametric trait with a positively skewed distribution. Median amount of conjunctival UVAF per person (sum of four measurements; right nasal/temporal and left nasal/temporal) was 28.2 mm(2) (interquartile range 14.5-48.2). There was an inverse, linear relationship between UVAF and advancing age (P<0.001). Males had a higher sum of UVAF compared with females (34.4 mm(2) vs 23.2 mm(2), P<0.0001). There were no statistically significant differences in area of UVAF between right and left eyes or between nasal and temporal regions. CONCLUSION: We have provided the first quantifiable estimates of conjunctival UVAF in an adult population. Further data are required to provide information about the natural history of UVAF and to characterise other potential disease associations with UVAF. UVR protective strategies should be emphasised at an early age to prevent the long-term adverse effects on health associated with excess UVR.

Application of near infrared (NIR) spectroscopy for determining the thickness of articular cartilage

The determination of the characteristics of articular cartilage such as thickness, stiffness and swelling, especially in the form that can facilitate real-time decisions and diagnostics is still a matter for research and development. This paper correlates near infrared spectroscopy with mechanically measured cartilage thickness to establish a fast, non-destructive, repeatable and precise protocol for determining this tissue property. Statistical correlation was conducted between the thickness of bovine cartilage specimens (n = 97) and regions of their near infrared spectra. Nine regions were established along the full absorption spectrum of each sample and were correlated with the thickness using partial least squares (PLS) regression multivariate analysis. The coefficient of determination (R2) varied between 53 and 93%, with the most predictive region (R2 = 93.1%, p < 0.0001) for cartilage thickness lying in the region (wavenumber) 5350–8850 cm−1. Our results demonstrate that the thickness of articular cartilage can be measured spectroscopically using NIR light. This protocol is potentially beneficial to clinical practice and surgical procedures in the treatment of joint disease such as osteoarthritis.