Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

A longitudinal assessment of chronic wound fluid to detect biochemical indicators of healing

Chronic venous leg ulcers are a detrimental health issue plaguing our society, resulting in long term pain, immobility and decreased quality of life for a large proportion of sufferers. The frequency of these chronic wounds has led current research to focus on the wound environment to provide important information regarding the prolonged, fluctuated or static healing patterns of these wounds. Disruption to the normal wound healing process results in release of multiple factors in the wound environment that could correlate to wound chronicity. These biochemical factors can often be detected through non-invasively sampling chronic wound fluid (CWF) from the site of injury. Of note, whilst there are numerous studies comparing acute and chronic wound fluids, there have not been any reports in the literature employing a longitudinal study in order to track biochemical changes in wound fluid as patients transition from a non-healing to healed state. Initially the objective of this study was to identify biochemical changes in CWF associated with wound healing using a proteomic approach. The proteomic approach incorporated a multi-dimensional liquid chromatography fractionation technique coupled with mass spectrometry (MS) to enable identification of proteins present in lower concentrations in CWF. Not surprisingly, many of the proteins identified in wound fluid were acute phase proteins normally expressed during the inflammatory phase of healing. However, the number of proteins positively identified by MS was quite low. This was attributed to the diverse range in concentration of protein species in CWF making it challenging to detect the diagnostically relevant low molecular weight proteins. In view of this, SELDI-TOF MS was also explored as a means to target low molecular weight proteins in sequential patient CWF samples during the course of healing. Unfortunately, the results generated did not yield any peaks of interest that were altered as wounds transitioned to a healed state. During the course of proteomic assessment of CWF, it became evident that a fraction of non-proteinaceous compounds strongly absorbed at 280 nm. Subsequent analyses confirmed that most of these compounds were in fact part of the purine catabolic pathway, possessing distinctive aromatic rings and which results in high absorbance at 254 nm. The accumulation of these purinogenic compounds in CWF suggests that the wound bed is poorly oxygenated resulting in a switch to anaerobic metabolism and consequently ATP breakdown. In addition, the presence of the terminal purine catabolite, uric acid (UA), indicates that the enzyme xanthine oxidoreductase (XOR) catalyses the reaction of hypoxanthine to xanthine and finally to UA. More importantly, the studies provide evidence for the first time of the exogenous presence of XOR in CWF. XOR is the only enzyme in humans capable of catalysing the production of UA in conjunction with a burst of the highly reactive superoxide radical and other oxidants like H2O2. Excessive release of these free radicals in the wound environment can cause cellular damage disrupting the normal wound healing process. In view of this, a sensitive and specific assay was established for monitoring low concentrations of these catabolites in CWF. This procedure involved combining high performance liquid chromatography (HPLC) with tandem mass spectrometry and multiple reaction monitoring (MRM). This application was selective, using specific MRM transitions and HPLC separations for each analyte, making it ideal for the detection and quantitation of purine catabolites in CWF. The results demonstrated that elevated levels of UA were detected in wound fluid obtained from patients with clinically worse ulcers. This suggests that XOR is active in the wound site generating significant amounts of reactive oxygen species (ROS). In addition, analysis of the amount of purine precursors in wound fluid revealed elevated levels of purine precursors in wound fluid from patients with less severe ulcers. Taken together, the results generated in this thesis suggest that monitoring changes of purine catabolites in CWF is likely to provide valuable information regarding the healing patterns of chronic venous leg ulcers. XOR catalysis of purine precursors not only provides a method for monitoring the onset, prognosis and progress of chronic venous leg ulcers, but also provides a potential therapeutic target by inhibiting XOR, thus blocking UA and ROS production. Targeting a combination of these purinogenic compounds and XOR could lead to the development of novel point of care diagnostic tests. Therefore, further investigation of these processes during wound healing will be worthwhile and may assist in elucidating the pathogenesis of this disease state, which in turn may lead to the development of new diagnostics and therapies that target these processes.

Damage quantification techniques in acoustic emission monitoring

Acoustic emission (AE) analysis is one of the several diagnostic techniques available nowadays for structural health monitoring (SHM) of engineering structures. Some of its advantages over other techniques include high sensitivity to crack growth and capability of monitoring a structure in real time. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). In AE technique, these stress waves are recorded by means of suitable sensors placed on the surface of a structure. Recorded signals are subsequently analysed to gather information about the nature of the source. By enabling early detection of crack growth, AE technique helps in planning timely retrofitting or other maintenance jobs or even replacement of the structure if required. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. Large amount of data is generated during AE testing, hence effective data analysis is necessary, especially for long term monitoring uses. Appropriate analysis of AE data for quantification of damage level is an area that has received considerable attention. Various approaches available for damage quantification for severity assessment are discussed in this paper, with special focus on civil infrastructure such as bridges. One method called improved b-value analysis is used to analyse data collected from laboratory testing.

Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis

Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

Investigating the potential value of individual parameters of histological grading systems in a sheep model of cartilage damage : the modified Mankin method

A total histological grade does not necessarily distinguish between different manifestations of cartilage damage or degeneration. An accurate and reliable histological assessment method is required to separate normal and pathological tissue within a joint during treatment of degenerative joint conditions and to sub-classify the latter in meaningful ways. The Modified Mankin method may be adaptable for this purpose. We investigated how much detail may be lost by assigning one composite score/grade to represent different degenerative components of the osteoarthritic condition. We used four ovine injury models (sham surgery, anterior cruciate ligament/medial collateral ligament instability, simulated anatomic anterior cruciate ligament reconstruction and meniscal removal) to induce different degrees and potentially 'types' (mechanisms) of osteoarthritis. Articular cartilage was systematically harvested, prepared for histological examination and graded in a blinded fashion using a Modified Mankin grading method. Results showed that the possible permutations of cartilage damage were significant and far more varied than the current intended use that histological grading systems allow. Of 1352 cartilage specimens graded, 234 different manifestations of potential histological damage were observed across 23 potential individual grades of the Modified Mankin grading method. The results presented here show that current composite histological grading may contain additional information that could potentially discern different stages or mechanisms of cartilage damage and degeneration in a sheep model. This approach may be applicable to other grading systems.

Assessment of “change in flexibility method” in structural health monitoring systems

The modern structural diagnosis process is rely on vibration characteristics to assess safer serviceability level of the structure. This paper examines the potential of change in flexibility method to use in damage detection process and two main practical constraints associated with it. The first constraint addressed in this paper is reduction in number of data acquisition points due to limited number of sensors. Results conclude that accuracy of the change in flexibility method is influenced by the number of data acquisition points/sensor locations in real structures. Secondly, the effect of higher modes on damage detection process has been studied. This addresses the difficulty of extracting higher order modal data with available sensors. Four damage indices have been presented to identify their potential of damage detection with respect to different locations and severity of damage. A simply supported beam with two degrees of freedom at each node is considered only for a single damage cases throughout the paper.

When non-significance may be significant : lessons learned from a study of the development, implementation and evaluation of a fleet risk assessment tool

This paper reports on the development and implementation of a self-report risk assessment tool that was developed in an attempt to increase the efficacy of crash prediction within Australian fleet settings. This study forms a part of a broader program of research into work related road safety and identification of driving risk. The first phase of the study involved a series of focus groups being conducted with 217 professional drivers which revealed that the following factors were proposed to influence driving performance: Fatigue, Knowledge of risk, Mood, Impatience and frustration, Speed limits, Experience, Other road users, Passengers, Health, and Culture. The second phase of the study involved piloting the newly developed 38 item Driving Risk Assessment Scale - Work Version (DRAS-WV) with 546 professional drivers. Factor analytic techniques identified a 9 factor solution that was comprised of speeding, aggression, time pressure, distraction, casualness, awareness, maintenance, fatigue and minor damage. Speeding and aggressive driving manoeuvres were identified to be the most frequent aberrant driving behaviours engaged in by the sample. However, a series of logistic regression analyses undertaken to determine the DRAS-WV scale’s ability to predict self-reported crashes revealed limited predictive efficacy e.g., 10% of crashes. This paper outlines proposed reasons for this limited predictive ability of the DRAS-WV as well as provides suggestions regarding the future of research that aims to develop methods to identify “at risk” drivers.

Damage detection in slab-on-girder bridges using vibration characteristics

This paper develops and applies a multi-criteria procedure, incorporating changes in natural frequencies, modal flexibility and the modal strain energy, for damage detection in slab-on-girder bridges. The proposed procedure is first validated through experimental testing of a model bridge. Numerically simulated modal data obtained through finite element analyses are then used to evaluate the vibration parameters before and after damage and used as the indices for assessment of the state of structural health. The procedure is illustrated by its application to full scale slab-on-girder bridges under different damage scenarios involving single and multiple damages on the deck and girders.

Assessing the damage caused by deepwater horizon : not just another Exxon Valdez

In light of the high stakes of the deepwater horizon civil trial and the important precedent-setting role that the case will have on the assessment of future marine disasters, the methodologies underpinning the calculations of damage on both sides will be subjected to considerable scrutiny. Despite the importance of the case, however, there seems to be a pronounced lack of convergence about it in the academic literature. Contributions from scientific journals frequently make comparisons to the Ixtoc I oil spill off the coast of Mexico in 1979; the legal literature, by stark contrast, seems to be much more focused on the Exxon Valdez spill that occurred off the shores of Alaska in 1989. This paper accordingly calls for a more thorough consideration of other analogs beyond the Exxon Valdez spill—most notably, the Ixtoc I incident—in arriving at an assessment of the damage caused by the Deepwater Horizon disaster.

Cutaneous markers of photo-damage and risk of basal cell carcinoma of the skin : a meta-analysis

BACKGROUND: Epidemiologic research has demonstrated that cutaneous markers of photo-damage are associated with risk of basal cell carcinoma (BCC). However there has been no previous attempt to calculate pooled risk estimates. METHODS: We conducted a systematic review and meta-analysis after extracting relevant studies published up to January 2013 from five electronic databases. Eligible studies were those that permitted quantitative assessment of the association between histologically-confirmed BCC and actinic keratoses, solar elastosis, solar lentigines, or telangiectasia. RESULTS: Seven eligible studies were identified and summary odds ratios (OR) were calculated using both random and quality effects models. Having more than ten actinic keratoses was most strongly associated with BCC, conferring up to a 5-fold increase in risk (OR: 4.97; 95% CI: 3.26, 7.58). Other factors, including solar elastosis, solar lentigines, and telangiectasia had weaker but positive associations with BCC with ORs around 1.5. CONCLUSIONS: Markers of chronic photo-damage are positively associated with BCC. The presence of actinic keratoses was the most strongly associated with BCC of the markers examined. IMPACT: This work highlights the relatively modest association between markers of chronic ultraviolet exposure and BCC.

Assessment of damages for wrongful birth and consolidation in advance care directives

The recent decision of Waller v James involved a claim by the plaintiff parents for damages for wrongful birth against the defendant doctor, Dr James, a gynaecologist with a practice in infertility and IVF procedures, who had been consulted by the plaintiffs. The second plaintiff, Mr Waller suffered an inherited anti-thrombin deficiency (ATD), a condition which results in a propensity for the blood to clot, at least in adults. Dr James subsequently recommended IVF treatment. The first plaintiff, Mrs Waller became pregnant after the first cycle of IVF treatment. Her son Keeden was born on 10 August 2000 with a genetic anti-thrombin deficiency. Keeden was released from hospital on 14 August 2000. However, he was brought back to the hospital the next day with cerebral thrombosis (CSVT). As a result of the thrombosis, he suffered permanent brain damage, cerebral palsy and related disabilities. The plaintiffs alleged that the defendant was in breach of contract and his common law duty of care to the plaintiffs in failing to inform them, or cause them to be informed, of the hereditary aspects of ATD. They further alleged that, had they been properly informed, they would not have proceeded to conceive a child using the male plaintiff’s sperm and therefore avoided the harm that had befallen them. The plaintiffs claimed damages to compensate them for their losses, including psychiatric and physical injuries and the costs of having, raising and caring for Keeden. The defendant was held to be not liable in negligence by Justice Hislop of the Supreme Court of New South Wales because a finding was made on medical causation which was adverse to the plaintiffs claim.

Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.

Visual analog scale and pressure pain threshold for delayed onset muscle soreness assessment

Objectives: To investigate the relationship between two assessments to quantify delayed onset muscle soreness [DOMS]: visual analog scale [VAS] and pressure pain threshold [PPT]. Methods: Thirty-one healthy young men [25.8 ± 5.5 years] performed 10 sets of six maximal eccentric contractions of the elbow flexors with their non-dominant arm. Before and one to four days after the exercise, muscle pain perceived upon palpation of the biceps brachii at three sites [5, 9 and 13 cm above the elbow crease] was assessed by VAS with a 100 mm line [0 = no pain, 100 = extremely painful], and PPT of the same sites was determined by an algometer. Changes in VAS and PPT over time were compared amongst three sites by a two-way repeated measures analysis of variance, and the relationship between VAS and PPT was analyzed using a Pearson product-moment correlation. Results: The VAS increased one to four days after exercise and peaked two days post-exercise, while the PPT decreased most one day post-exercise and remained below baseline for four days following exercise [p < 0.05]. No significant difference among the three sites was found for VAS [p = 0.62] or PPT [p = 0.45]. The magnitude of change in VAS did not significantly correlate with that of PPT [r = −0.20, p = 0.28]. Conclusion: These results suggest that the level of muscle pain is not region-specific, at least among the three sites investigated in the study, and VAS and PPT provide different information about DOMS, indicating that VAS and PPT represent different aspects of pain.

Vulnerability and damage analysis of reinforced concrete framed buildings subjected to near field blast events

Terrorists usually target high occupancy iconic and public buildings using vehicle borne incendiary devices in order to claim a maximum number of lives and cause extensive damage to public property. While initial casualties are due to direct shock by the explosion, collapse of structural elements may extensively increase the total figure. Most of these buildings have been or are built without consideration of their vulnerability to such events. Therefore, the vulnerability and residual capacity assessment of buildings to deliberately exploded bombs is important to provide mitigation strategies to protect the buildings' occupants and the property. Explosive loads and their effects on a building have therefore attracted significant attention in the recent past. Comprehensive and economical design strategies must be developed for future construction. This research investigates the response and damage of reinforced concrete (RC) framed buildings together with their load bearing key structural components to a near field blast event. Finite element method (FEM) based analysis was used to investigate the structural framing system and components for global stability, followed by a rigorous analysis of key structural components for damage evaluation using the codes SAP2000 and LS DYNA respectively. The research involved four important areas in structural engineering. They are blast load determination, numerical modelling with FEM techniques, material performance under high strain rate and non-linear dynamic structural analysis. The response and damage of a RC framed building for different blast load scenarios were investigated. The blast influence region for a two dimensional RC frame was investigated for different load conditions and identified the critical region for each loading case. Two types of design methods are recommended for RC columns to provide superior residual capacities. They are RC columns detailing with multi-layer steel reinforcement cages and a composite columns including a central structural steel core. These are to provide post blast gravity load resisting capacity compared to typical RC column against a catastrophic collapse. Overall, this research broadens the current knowledge of blast and residual capacity analysis of RC framed structures and recommends methods to evaluate and mitigate blast impact on key elements of multi-storey buildings.