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In the case of machines, structures and assemblies, the crack generation and propagation is becoming a great concern, especially in airplane wings, turbine blades and such other applications. This is because these parts are very large in size and the crack size is very small, i.e. in microns. Hence, there is an important need to locate the crack and to find its severity before it starts to propagate and also to detect these parameters by on-site non-destructive testing methods. This paper aims to develop and test the methodology to locate an unknown single open crack in steel cantilever beam along with its severity.

This study covers analytical, numerical and experimental analysis for healthy and cracked beams. Vibration-based approach and finite element analysis (FEA) approach is used for analytical and numerical study respectively. Own designed and dedicated experimental set-up is used for testing purpose along with fast fourier transform analyzer. An anti-resonance technique is used to locate and to find the severity of unknown crack. The statistical approach helps to validate the results.

The comparison of the natural frequency of healthy and cracked steel cantilever beam shows that the crack in the beam reduces its natural frequency. The accuracy of results is achieved by finding actual density and Young's modulus of steel specimen under consideration. It is helpful to verify the health of the non-cracked beam by applying dye testing. The study of natural frequency and anti-resonance gives the location of crack and its depth also. The FEA approach proved to be an important tool for numerical analysis of cracked beam.

The research is limited to steel material and surface cracks only.

Practically, this study highlights how to locate a surface crack in steel beam along with its depth, i.e. severity with great accuracy. Identification of the factors such as location and depth of a crack provide the severity of damage in airplane wings, turbine blades, bridges and many more, and thereby, it helps in safety at working vicinity.

The identification and solutions of current research helps to predict the operational life of machine elements such as airplane wings, turbine blades, bridges and many more, and thereby, it helps in the safety of people in working vicinity of such structures.

The work presented, is based on original research and experimentation. This work is valued contribution in the field of methodologies applied for fault detection in structures and also determining its correctness by numerical and experimental work.

The purpose of this paper is to address the determination of crack location and depth of multiple transverse cracks by monitoring natural frequency and its prediction using Artificial Neural Networks (ANN). An alternative to the existing NDTs is suggested.

Modal analysis is performed to extract the natural frequency. Analysis is performed for two cases of cracks. In first case, both cracks are perpendicular to axis. In second case, both cracks are inclined to vertical plane and also inclined with each other. Finite element method (FEM) is performed using ANSYSTM software which is theoretical basis. Experimentation is performed using Fast Fourier Transform (FFT) analyzer on simply supported stepped rotor shaft and cantilever circular beam with two cracks each.

The results of FEM and experimentation are validated and are in good agreement. The error in crack detection by FEM is in the range of 3-15 percent while 5-20 percent by experimentation. The database obtained by modal analysis is used to train the network of ANN which predicts crack characteristics. Validity of method is investigated by comparing the predictions of ANN with FEM and experimentation. The results are in good agreement with error of 7-16 percent between ANN and FEM while 9-21 percent between ANN and experimental analysis.

It envisages that the method is capable. It is an effective as well as an alternate method of fault detection in beam/rotating element to the existing methods.

The purpose of this paper is to highlight that the need for improved system identification methods within the domain of modal analysis increases under the impulse of the broadening field of applications, e.g., damage detection and vibro-acoustics, and the increased complexity of today’s structures. Although significant research efforts during the last two decades have resulted in an extensive number of parametric identification algorithms, most of them are certainly not directly applicable for modal parameter extraction. So, based on this, the aim of the present work is to develop a technique for modal parameter extraction from the measured signal.

A survey and classification of the different modal analysis methods are made; however, the focus of this thesis is placed on modal parameter extraction from measured time signal. Some of the methods are examined in detail, including both single-degree-of-freedom and multi-degree-of-freedom approaches using single and global frequency-response analysis concepts. The theory behind each of these various analysis methods is presented in depth, together with the development of computer programs, theoretical and experimental examples and discussion, in order to evaluate the capabilities of those methods. The problem of identifying properties of structures that possess close modes is treated in particular detail, as this is a difficult situation to handle and yet a very common one in many structures. It is essential to obtain a good model for the behavior of the structure in order to pursue various applications of experimental modal analysis (EMA), namely: updating of finite element models, structural modification, subsystem-coupling and calculation of real modes from complex modes, to name a few. This last topic is particularly important for the validation of finite element models, and for this reason, a number of different methods to calculate real modes from complex modes are presented and discussed in this paper.

In this paper, Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been developed based on frequency domain decomposition (FDD) technique to check the accuracy of the results as obtained from ARTeMiS. It is observed that the frequency domain-based algorithm shows good agreement with the extracted results. Hence the following conclusion may be drawn: among several frequency domain-based algorithms for modal parameter extraction, the FDD technique is more reliable and it shows a very good agreement with the experimental results.

In the case of extraction techniques using measured data in the frequency domain, it is reported that the model using derivatives of modal parameters performed better in many situations. Lack of accurate and repeatable dynamic response measurements on complex structures in a real-life situation is a challenging problem to analyze exact modal parameters.

During the last two decades, there has been a growing interest in the domain of modal analysis. Evolved from a simple technique for troubleshooting, modal analysis has become an established technique to analyze the dynamical behavior of complex mechanical structures. Important examples are found in the automotive (cars, trucks, motorcycles), railway, maritime, aerospace (aircrafts, satellites, space shuttle), civil (bridges, buildings, offshore platforms) and heavy equipment industry.

Presently structural health monitoring has become a significantly important issue in the area of structural engineering particularly in the context of safety and future usefulness of a structure. A lot of research is being carried out in this area incorporating the modern sophisticated instrumentations and efficient numerical techniques. The dynamic approach is mostly employed to detect structural damage, due to its inherent advantage of having global and location-independent responses. EMA has been attempted by many researchers in a controlled laboratory environment. However, measuring input excitation force(s) seems to be very expensive and difficult for the health assessment of an existing real-life structure. So Ambient Vibration Analysis is a good alternative to overcome those difficulties associated with the measurement of input excitation force.

Three single bay two storey frame structure has been chosen for the experiment. The frame has been divided into six small elements. An algorithm has been developed to determine the natural frequency of those frame structures of which one is undamaged and the rest two damages in single element and double element, respectively. The experimental results from ARTeMIS and from developed algorithm have been compared to verify the effectiveness of the developed algorithm. Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been programmed in MATLAB based on the FDD technique to check the accuracy of the results as obtained from ARTeMiS. Using singular value decomposition, the power Spectral density function matrix is decomposed using the MATLAB program. It is observed that the frequency domain-based algorithm shows good consistency with the extracted results.

The purpose of this paper is to propose an identification method of acquiring aircraft mode characteristics based on fast Fourier transform and half-power bandwidth method, aiming at the common oscillation met in flight test.

The feasibility of this method is demonstrated through derivation; the robustness analysis is conducted through three examples, and finally the method was applied on a set of sideslip angle record from flight test.

The derivation and numerical analysis both show that the presented method can have high accuracy and good robustness under coupled mode and noise condition.

The method proposed is of robustness, and it is concise and easy to apply on flight data record.

This paper demonstrates the feasibility of half power bandwidth to be applied on oscillation mode characteristics identification from flight data record, which is different from other method applied.

This paper proposes a simple technique for assessing the effect of gear transmission errors in a six‐axis industrial serial robot, as these errors can vitally affect the industrial robot's positioning accuracy.

The experimental procedure is developed using a laser interferometer system to measure bidirectional linear position errors for an ABB IRB 1600 industrial robot. A simple technique based on fast Fourier transformation (FFT) analysis is devised and implemented for the characterization, evaluation, and quantification of gear transmission errors. Structural deformation and backlash error are also discussed.

The authors found that the major sources of error affecting the performance of the robot come from joints two and three. They also found that eccentricity errors, structural deformations, and backlash are the most important sources of error affecting the accuracy and the repeatability of the industrial robot studied. Additional tests show that the robot's first joint has relatively poor bidirectional repeatability.

The usefulness of a laser tracker (or any other large range portable 3D measurement system) is questionable for assessing – let alone analyzing in depth – the gear transmission errors of some of today's industrial robots. The authors demonstrate in this paper that a laser interferometer system can successfully measure gear transmission errors very accurately. The proposed methodology is simple, efficient, and easy to use for the characterization and quantification of the errors.

This work is the first to detail the use of the laser interferometer system for the characterization of the gear transmission errors of an industrial robot. A methodology has been developed and implemented for very accurately quantifying the effects of gear transmission errors, structural deformations, and backlash. The proposed methodology greatly simplifies the measurement set‐up and accelerates error quantification.

The need for structural health monitoring systems is continuously growing to maintain existing civil infrastructure. For the purpose of assuring seismic safety, it is necessary to monitor the damage for its occurrence, its location and the extent of damage. Information on the damage may be utilized to make decisions on maintenance and structural safety of existing buildings, rapid evaluation of condition of damaged structure after future earthquakes, estimation of residual life of structures, feasibility of repair and retrofitting of structures, partial replacement or demolition of structure and financial planning for renovation and rehabilitation. The purpose of this paper is to present a four‐level scheme of damage detection.

In the first stage of the four‐level scheme, finite element model has been developed and dynamic parameters are calculated. In the second stage, change in the dynamic properties of farmed reinforced concrete building model is identified from vibration measurements under different level of controlled damage. In the third stage, search for the damaged stories containing the damaged components is carried out of the damaged model by making use of the change in modal properties. Finally, the extent of damage is evaluated by using its frequency response function (FRF).

The magnitude of FRF decreases with the increase in the level of damage in the RCC building model. The damage index for different levels of damage as calculated from the FRF magnitude indicates that damage index increases with increase in damage. The magnitude of FRF varies with the level of damage in the storey.

Three storey RCC building model without infill wall have been considered. Damage has been induced in the building model by applying static horizontal load at the roof level.

The paper contains only unpublished Information derived from other publications is strictly referenced. Therefore, most of the concepts and experiences presented are new.

This paper describes the results for magnetic damping in torsional mode (TEAM problem 16). A total of six solutions are presented and compared with experimental results. The problem is treated as a coupled electromagnetomechanical one. In general numerical predictions agree well with experiment.

Electroless plating treatment is one surface modification technique. An added effect due to electroless plating is expected, and the vibration damping capacity of the structures may be improved by this technique. In the present study, the vibration damping capacity of such electroless plated structures is measured experimentally. Damping capacity can be improved regardless of the plated film materials. Improvement efficiency with an electroless plating film with dispersed foreign particles such as SiC ceramics is higher than with a uniform electroless plating film.

This paper seeks to present a new solution algorithm for updating of finite element models in structural dynamics. A random search method is applied to improving the correlation between the numerical simulation and the measured experimental data.

Dynamic finite element model updating may be considered as an optimization process. It is solved using modified accelerated random search (MARS) algorithm. The effectiveness of the approach is first tested on benchmark problems. Next, several objective function formulations for dynamic model updating in modal and frequency domains are investigated for numerically simulated vibrating beam. Finally, the algorithm is applied to a real beam‐like structure using measured modal data.

The MARS algorithm is able to provide very good results in a reduced time even for hard optimization problems. It behaves very well also for the FE dynamic model updating, highly coupled problems. The efficient updating criterion has been proposed and the approach has been validated experimentally.

The method is supposed to be time consuming for large size or complicated objective function problems but the choice of optimization parameters can accelerate the convergence.

The MARS algorithm can be applied to model updating in civil and mechanical engineering.

This paper is the first to apply the MARS algorithm to the problem of FE model updating in dynamics and enables one to obtain very good results. Efficient criteria for model updating have been proposed.