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Rotating machines in particular induction electrical machines are important industry instruments. In manufacturing, electrical motors are exposed to many damages, and this causes stators and rotors not to work correctly. In this paper we addressed modal analysis and an intelligent method to detect motor load condition and also the stator faults such as turn-to-turn and coil-to-coil faults using motor vibration analysis. A three-phase induction motor with a special winding was used to create the faults artificially. The vibration signal of motor in different states such as working without fault, with various faults and with various loads was acquired. Some spectral analysis was done using the spectrum and the spectrograph of vibration signals and differences due to different states of motor were observed. Suitable features such as Linear Prediction Cepstral Coefficients and Fourier Transform Filter Bank Coefficients were extracted from vibration signals and were then applied to non-supervised (SOM) and supervised (LVQ) neural networks in order to classify motor faults and its load condition. Many experiments were conducted to evaluate the effect of neural network type, type and length of feature vector, length of training signal etc. In brief, using SOM and LVQ neural networks, 20 element Filter Bank feature vectors, and 600ms of the training data, performance of 93.6% and 94.2% were obtained for load and fault detection respectively.

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In this paper, the effect of the crack on the vibration behavior of a thick-walled cracked pipe conveying fluid is investigated. The presence of a crack on the pipe introduces considerable local flexibility at the crack location. This flexibility is modeled by the fracture mechanics approach. The accuracy of the model is validated through the experimental data reported in the literature. Then, by using the mentioned model, the vibration analysis of the cracked pipe conveying fluid has been accomplished. Moreover, in order to solve the equation governing the vibration of the cracked pipe conveying fluid, a new analytical technique based on the power series method is proposed. Then, by applying the boundary conditions and the compatibility conditions at the crack location, the frequency equation is obtained. The results are presented by appropriate curves showing the variation of the natural frequency of the cracked pipe conveying fluid in terms of the crack depth and the fluid flow velocity. Also, the results show that for a cracked pipe with a given depth and location for the crack, by increasing the fluid flow velocity, the natural frequencies of the pipe decrease. Also, as the fluid velocity approaches to a certain value, the fundamental natural frequency approaches zero and instability occurs.

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The main objective of this research is to study the nonlinear vibrations of a single walled carbon nanotube. For this purpose, the lattice structure of carbon nanotube is replaced with a continuum structure using nanoscale continuum mechanics. Firstly, each carbon-carbon bond is replaced with an equivalent beam element and then the whole discrete structure of carbon nanotube is replaced with a virtual continuum medium representing hollow cylinder. Then, governing equations for vibrations is obtained taking into account geometric nonlinearity arisen from stretching of a mid-plane due to bending. Perturbation technique is used to analyze the nonlinear vibrations of carbon nanotubes. Frequency responses of carbon nanotubes for free vibrations and force vibrations in both primary and secondary resonance cases are studied. Obtained results are in a very good agreement with numerical integration technique. The results imply on hardening behavior of carbon nanotube. Moreover, nonlinear bifurcation and nonlinear jump phenomena are observed.

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In this paper, free vibration analysis of functionally graded carbon nanotube reinforced composite (FG-CNTRC) cylindrical shells surrounded by elastic foundation and subjected to uniform temperature rise loading is investigated. The material properties of FG-CNTRC are assumed to be graded through the thickness direction. Two kinds of carbon nanotube reinforced composites including uniformly distributed (UD) and functionally graded (FG) are considered. The elastic foundation is modeled by two-parameter Pasternak model, which is obtained by adding a shear layer to the Winkler model. The effect of thermal loading is considered as a initial stress. Applying the Hamilton’s principle based on first-order shear deformation theory and considering Sanders and Donnell strain-displacement relation, the governing equations are obtained. Using the generalized differential quadrature method in axial direction and periodic differential matrix operators in circumferential direction, the equilibrium equations are discretized. The results are compared with those presented in literature. In addition, the effect of various parameters such as thermal loading, boundary conditions, elastic foundation and different geometrical conditions are studied. The results show that increase in the elastic foundation coefficients and initial thermal loading increase and decrease the non-dimensional fundamental frequency, respectively.

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In this paper, a new inverse method has been presented for identifying the distribution of material properties and volume fraction index of rectangular functionally graded (FG) material plates. This method benefits from vibration analysis of FG plates accompanied by a novel and efficient meta-heuristic optimization algorithm called Drops Contact Optimization (DCO) algorithm, being proposed for the first time in this article. The presented algorithm relies on the initial population and mimics the behavior of water drops in different level of contacting successively with a fluid surface. Through using the second shear deformation theory and applying the Hamilton principle, the motion equations are derived and, subsequently, the natural frequencies of the considered FG plates are obtained. The outcomes relevant to considered different material phases and various length to thickness ratios are achieved and compared with those available in the literature. Making a comparative study of the obtained results with five well-known optimization algorithms confirms that the proposed DCO algorithm produces better performance in convergent speed and accurate characterization of FG materials.

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In this paper, cracking in the first mode (opening) is modelled for reinforced concrete beams with FRP sheets based on presenting a new method by using the principles and relations of fracture mechanics and finite element method. In this method, for modelling the relationships of determining the stress intensity factor is developed for reinforcement sheet. In the proposed method, elements of the beam are divided into two categories, including elements with and without the crack. In the elements without the crack, the relationships, equation, stiffness and mass matrices of the beam are established with considering the changes in the moment of inertia due to the reinforced FRP sheet. In the elements with the crack, a change in the cross-section of the reinforced concrete due to the crack and a discontinuity in the crack point leads to an improvement in the standard governing relationships. So that the reduction of the stiffness of the cracked element is equivalent to the change in the size of the discontinuity. Here, the variation of the stiffness of the cracked element is calculated and presented as a function of the stress intensity factor. In this approach, the simulation of the crack is done by dividing the element to two sub-elements into the two sides of the rotational spring. In which, The stiffness and mass matrices of the two sub-elements and the improved stiffness and mass matrix of the element are derived by satisfying the continuity equation at the crack point. This method is developed from a vibrating analysis. The effects of crack depth and location and the effect of crack expansion on the static and vibrational behaviour of a concrete beam are investigated. To ensure the accuracy of the proposed method, all analysis performed in Abacus software is implemented. Comparing the results of the proposed model with the results of comprehensive modelling in Abacus software is applied to verify. The comparison of the results shows that the proposed methods are suitable for the analysis of reinforced concrete structures resistant to cracking. So that it can be generalised and optimally desirable for other models. In this paper, cracking in the first mode (opening) is modelled for reinforced concrete beams with FRP sheets based on presenting a new method by using the principles and relations of fracture mechanics and finite element method. In this method, for modelling the relationships of determining the stress intensity factor is developed for reinforcement sheet. In the proposed method, elements of the beam are divided into two categories, including elements with and without the crack. In the elements without the crack, the relationships, equation, stiffness and mass matrices of the beam are established with considering the changes in the moment of inertia due to the reinforced FRP sheet. In the elements with the crack, a change in the cross-section of the reinforced concrete due to the crack and a discontinuity in the crack point leads to an improvement in the standard governing relationships. So that the reduction of the stiffness of the cracked element is equivalent to the change in the size of the discontinuity. Here, the variation of the stiffness of the cracked element is calculated and presented as a function of the stress intensity factor. In this approach, the simulation of the crack is done by dividing the element to two sub-elements into the two sides of the rotational spring.

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In this study, an example of the results obtained from the combination of the vibration monitoring program and the root cause analysis approach for the electromotor roller element bearings of the cement factory’s mill fan has been presented and examined. By registering the inspectors' reports on the release of abnormal sound from the bearings, the vibration data recorded in the monitoring program were equipped and, by carefully checking the vibration trends of the machine, sensible increase in the bearing condition index (BC) have seen. By matching the fault frequency with the frequency elements of the roller bearing, predicted is failure in the bearing' cage, which will be verified by visited and reviewed. The detect of the root cause of the failure is on the agenda for this purpose, paid investigated the causes of failure in the bearings and due to the inspection history, finally specified the use of the bearing is not suitable due to the velocity factor, as well as the factors of the lubrication interval and the amount of lubrication charged can be explained by the reasons for failure in the machine.

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Fualts in rolling bearings are one of the main reasons for the failure of rotating machinery. faults detection rolling bearing has played an essential role in the reliable performance of production units. In addition, condition monitoring of machinery using vibration analysis is one of the most powerful tools in measuring the health of mechanical systems. This research proposes an intelligent system for detecting defects in rolling bearings based on vibration analysis. In the intelligent faults detection system, the extracted features of the vibration signals in the time domain and the radial basis function neural network are used. The train and test datasets are presented to the radial basis function neural network intelligent system. The results of neural network learning show the very successful performance of the intelligent fault diagnosis system in detecting the health state and triple fault states of rolling bearings