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The purpose of this paper is mainly the quantitative and the qualitative analysis of a reinforced concrete slab containing two types of delaminations: voids and honeycomb, with different sizes and depths.

In this paper the paper adopts the infra-red thermography as a sounding method. It is used as a tool to estimate the change in temperature or thermal contrast induced by the presence of a defect in specimen besides using numerical simulation based on FEM to develop the prediction of temperature development in concrete structure.

This study shows that the numerical methods can be used to evaluate and validate the experimental results. The coupling of the simulation and the experimentation can be of a great utility because it allows predicting the results before beginning the experimentation.

The paper finds that the use of FEM in the prediction of temperature evolution in concrete, and the validation of the numerical simulation with the results obtained by the experimental measurements have a key importance in the study of civil engineering structure.

The purpose of this paper is to discuss methodological guidelines and operation protocols for the assessment of historic buildings by radar techniques, as decision-making support within integrated investigation programs, where documentary records, direct survey and onsite measurements address accurate and effective diagnosis.

Radar methodologies and procedures are planned to support the pre-diagnosis hypotheses, based on preliminary information from historical sources, as well as from direct survey of geometry, materials, construction techniques and decay patterns. Thus, they are applied, in terms of acquisition and elaboration systems, taking into account the testing targets and surrounding conditions. Finally, they are correlated with complementary destructive and non-destructive techniques for data interpretation and validation.

The general approach is developed for some representative case studies, in order to point out the potentialities of radar techniques for traditional building components. In detail, masonry walls and vaults, as well as iron and reinforced concrete slabs are assessed, in terms of construction materials and techniques, morphology and stratigraphy of multi-layered components, inner voids and inclusions, previous reinforcement works.

The above-mentioned issues are particularly relevant in the assessment of historic buildings, where onsite non-destructive technologies are commonly applied, because they help identify the actual characteristics, residual performances and state of conservation, without interfering with structural stability and functional operability, and, thus, address low-intrusive and compatible interventions. Nevertheless, emerging technologies, such as radar scanning, still require guidelines and protocols, in order to achieve reliable and meaningful results and save time and resources, especially whenever technical data are limited, investigation conditions are challenging and different construction solutions are involved.

The objective of this paper is to provide a brief review of recent developments in the area of applications of ANN, Fuzzy Logic, and Wavelet Transform in fault diagnosis. The purpose of this work is to provide an approach for maintenance engineers for online fault diagnosis through the development of a machine condition‐monitoring system.

A detailed review of previous work carried out by several researchers and maintenance engineers in the area of machine‐fault signature‐analysis is performed. A hybrid expert system is developed using ANN, Fuzzy Logic and Wavelet Transform. A Knowledge Base (KB) is created with the help of fuzzy membership function. The triangular membership function is used for the generation of the knowledge base. The fuzzy‐BP approach is used successfully by using LR‐type fuzzy numbers of wavelet‐packet decomposition features.

The development of a hybrid system, with the use of LR‐type fuzzy numbers, ANN, Wavelets decomposition, and fuzzy logic is found. Results show that this approach can successfully diagnose the bearing condition and that accuracy is good compared with conventionally EBPNN‐based fault diagnosis.

The work presents a laboratory investigation carried out through an experimental set‐up for the study of mechanical faults, mainly related to the rolling element bearings.

The main contribution of the work has been the development of an expert system, which identifies the fault accurately online. The approaches can now be extended to the development of a fault diagnostics system for other mechanical faults such as gear fault, coupling fault, misalignment, looseness, and unbalance, etc.

The purpose of this paper is to propose an optimal predictive model for the short-term forecast of real-time non-stationary machine variables by combining time series prediction with adaptive algorithms to minimize the error and to improve the prediction accuracy.

The proposed model is applied for prediction of speed and controller set point of three-phase induction motor operating on closed loop speed control with AC drive and PI controller. At Stage 1, the trend of the machine variables has been extracted and added to auto-regressive moving average (ARMA) time series prediction. ARMA prediction has been carried out using different combinations of AR and MA methods in order to make prediction with less Mean Squared Error (MSE).

The prediction error indicates the inadequacy of the model to estimate the data characteristics, which has been resolved at the subsequent stage by cascading an adaptive least mean square finite impulse response filter to the time series model. The adaptive filter receives the predicted output including training data and iteratively adjusts its coefficients for zero error convergence.

The componentized data prediction based on time series and cascade adaptive filter algorithm decomposes the non-stationary data characteristics for predictive maintenance. Evaluation of the model with different combination of time series algorithms and parameter settings of adaptive filter has been carried out to illustrate the performance of the prediction model. This prediction accuracy is compared with existing linear adaptive filter prediction using MSE as comparison index. The wide margin in the MSE values substantiates the prediction efficiency of the proposed model for machine data.

This model predicts the dynamic machine data with component decomposition at high accuracy, which enables to interpret the system response under dynamic conditions efficiently.

In a high temperature tribometer, stationary carbon has been tested against different rotating ceramics (SiC, Si₃N₄, Al₂O₃, WC‐6Ni, MgO‐ZrO₂, (Ti, Mo)(C, N)) and stainless steel (DIN 1.4876). The rotating discs were grinded, polished and/or lapped. For most material combinations, the wear morphology is known from available literature. A transfer film with a typical wear pattern was found on the rotating disc. The combination of antimony graphite EK3245 against MgO‐ZrO₂ did not form carbonaceous transfer layer. Through advanced variation of the roughness up to R_pk=0.011 μm, the wear rate has been reduced to K_v ≈ 3.5×10⁻⁸ mm³/N m at a stable coefficient of friction in a “millirange” of μ∼0.008 for a sliding distance of 20.000 m.

Examines the problems connected with quality assurance in composite material components. Focuses on the quality implications of the product during the material selection and characterization phases and on the evaluation of allowables through statistical analysis. Defines the relationship between design and the structural reliability evaluation of the loaded material and motivates the necessity of accounting for the material′s behaviour patterns with pre‐existent distributed and operation‐induced damage.

The purpose of this study is to review the existing fatigue and vibration-based structural health monitoring techniques and highlight the advantages of combining both approaches.

Fatigue monitoring requires a fatigue model of the material, the stresses at specific points of the structure, a cycle counting technique and a fatigue damage criterion. Firstly, this paper reviews existing structural health monitoring (SHM) techniques, addresses their principal classifications and presents the main characteristics of each technique, with a particular emphasis on modal-based methodologies. Automated modal analysis, damage detection and localisation techniques are also reviewed. Fatigue monitoring is an SHM technique which evaluate the structural fatigue damage in real time. Stress estimation techniques and damage accumulation models based on the S-N field and the Miner rule are also reviewed in this paper.

A vast amount of research has been carried out in the field of SHM. The literature about fatigue calculation, fatigue testing, fatigue modelling and remaining fatigue life is also extensive. However, the number of publications related to monitor the fatigue process is scarce. A methodology to perform real-time structural fatigue monitoring, in both time and frequency domains, is presented.

Fatigue monitoring can be combined (applied simultaneously) with other vibration-based SHM techniques, which might significantly increase the reliability of the monitoring techniques.

The assessment of a deteriorating masonry structure should lead to an objective evaluation of condition. This process is, however, inevitably subjective owing to human interpretation. The condition of the substrate and the required repairs cannot be guaranteed and may vary from building inspector to inspector. For conservation works the determination of repairs is a function of condition but also directly relates to the underpinning framework of building conservation philosophy. These are also fundamentally subjective. The combination of both condition survey subjectivity and building conservation philosophy's nebulous nature creates the potential for project aesthetic and technical divergence. This paper aims to examine this issue.

The paper presents a literature review and hypothetical case studies.

It has been shown by various researchers that a visual survey is subjective and is therefore prone to differences in reporting. In addition, the application of building conservation philosophy is seen through the perspective of the professional specifying the repairs. The combination of these two factors leads to the potential for significant project outcomes.

Subjectivity of evaluation of condition for traditional masonry structures has been little studied by academics and practitioners alike, and it is generally assumed that these yield objective, rational data. This is not necessarily the case. The application of building conservation philosophy to determine repair strategies is also a subjective process. The combination of both may lead to significant project divergence. These combined factors have never previously been discussed.

The purpose of this paper is to experimentally investigate the capability of four non-destructive testing (NDT) techniques to detect the layer orientation in textile composite laminates. The aerospace industry has been the primary driving force in the use of textile composites.

Woven glass fiber composite samples were inspected using C-scan ultrasonic, vibration analyzer, X-ray micro-tomography and ultraviolet technique. In a complementary study, mechanical testing was carried out to investigate the effect of mid-layer orientation on in-plane tensile strength and their failure modes using microscopic imagining.

During C-scan ultrasonic, the high attenuation and scattering of ultrasonic waves caused by the textile fabric layers limited its application to only detect the first layer of samples. Frequency response tests of composite samples were also conducted to investigate the effect of mid-layer orientation on dynamic responses. The same trend was observed in the finite element modeling results with a clear effect of the fiber orientation defect seen in frequency response function response and higher mode shapes. Moreover, the results of micro computed tomography demonstrate that this technique could definitely detect the orientation of each layer; however, X-ray imaging at small scales introduced some challenges. Images obtained from ultraviolet technique did not reveal mid-layer orientation.

In this paper, the application of different NDT techniques along with finite element modeling to inspect two-dimensional textile composites was presented. Hopefully, the research results presented here will lead to much published papers in inspection of textile composites.