The objective of the current work is to show the effectiveness of using wavelet transform for detection and localization of small DAMAGEs. The spatial data used here are the rotational mode shapes of the DAMAGEd and unDAMAGEd plate-like structures. The continuous wavelet transform using complex Gaussian wavelet is used to get the spatially distributed wavelet coefficients so as to identify the DAMAGE position on a square plate. The rotational mode shape data of the square plate with DAMAGE of different sizes are obtained using ANSYS 9.0. DAMAGE IDENTIFICATION for different boundary conditions is studied.

In this paper, a method to determine the material parameters of the Lemaitre DAMAGE model from the knowledge of the Gurson model parameters is proposed. As for porosity DAMAGE, the Gurson model neglects the coupling of elasticity with DAMAGE, allowing to use the stress softening effect to make a link between both theories up to a fast IDENTIFICATION procedure (based on the expressions of the yield surfaces of the DAMAGEd material). An experimental procedure to identify the Gurson DAMAGE parameters has been established for A533B alloy steel under stress triaxiality condition. This method is evaluated in the experimental results of A533B steel. The comparisons indicate good agreements between the result obtained by the proposed method and those of experiments.

In DAMAGE detection the number of elements is generally more than the number of measured frequencies. Consequently, the corresponding DAMAGE detection equation is undetermined and thus has infinite solutions. Since in the DAMAGEd structures most of their elements remain healthy, the sparsest solution for the DAMAGE detection equation is mostly the actual DAMAGE. In the proposed method, the DAMAGE equation is first linearized in various ways using random finite difference increments. The sparsest solutions for created linear system of equations are derived using basis pursuit. These solutions are considered as the first population for a continuous genetic algorithm to obtain the DAMAGE solution. For investigation of the proposed method three case studies are considered. Simulation results confirm the efficiency of the proposed method compared to those found in the literature.

The paper focuses on detecting, locating and quantifying the DAMAGE occurring in three different forms, namely (a) a beam with only a dominant crack, (b) a uniformly degraded beam, and (c) a uniformly degraded beam with a dominant crack. Generalised methodologies have been proposed to solve the three DAMAGE cases. Fixed beams have been considered to demonstrate the effectiveness of the generalised method for DAMAGE IDENTIFICATION. The beam is loaded with a point load. The static deflection has been used as the response to perform continuous wavelet transform (CWT). The continuous wavelet transform coefficients are used to compute the Holder exponent and an Intensity factor. The intensity factor is used to relate the DAMAGE (crack DAMAGE and/or degradation) characteristics to the magnitude of the wavelet coefficients. The proposed generalised method can be used to solve the DAMAGE IDENTIFICATION problem for all fixed beams, irrespective of changes in the magnitude of load applied, geometrical and material properties. The effectiveness of the proposed method is demonstrated by validating with several numerical examples available in the literature.

In this study, DAMAGE detection methods of cable stayed bridges were investigated. Cable stayed bridges are flexible structures; meanwhile they are sensitive to vibrations due to their complicated and multiple vibrations modes; therefore, DAMAGE detection methods based on vibration data in cable-stayed bridges has become a challenging issue. In the present study, finite element model of Bill Emerson, Missouri cable stayed bridge was simulated in order to achieve a precise finite element model to simulate the DAMAGE scenarios in bridge and the study of them. General process includes four DAMAGE detection indices based on the modal data (mode shapes and natural frequencies) achieved by modelling structure and simulated DAMAGEs and in each case the results of DAMAGE detection were presented by indices. These methods are: Enhanced Coordinate Modal Assurance Criterion (ECOMAC), Mode Shape Curvature (MSC), Modal Flexibility Index (MFI), DAMAGE Index (DI). Some of the methods were applied in DAMAGE detection of the pervious structures and bridges. In this paper, correlative study of these methods were performed based on different DAMAGE scenarios as well as study of challenges such as different levels of random noise in the input data, incomplete modal data and low DAMAGE intensity in detection of DAMAGE in cable-stayed bridge and then, performance of the methods were assessed.

In this paper, an alternative approach in operational modal analysis is presented, utilizing image processing technique and transmissibility functions. Imaging sensors do not impose additional mass on the structure due to their non-contact nature, while transmissibility functions, independent of excitation type, can directly extract mode shapes. The innovation of this research lies in combining these two techniques to record dynamic responses and identify modal properties. To capture the temporal response history from video signals, the block-matching method with sub-pixel accuracy was employed. Validation was conducted by recording the response of the tip of a cantilevered steel beam subjected to impact excitation, using a high-speed camera and a laser vibrometer, simultaneously. The RMSE plots in the time domain and the PSD in the frequency domain indicate high accuracy of this method. Using this approach, the displacement time histories of various points on the structure were extracted from the video signals, and the modal properties, including natural frequencies, damping ratios, and mode shapes, were identified using the transmissibility matrix method. The results obtained from the proposed method were compared with the stochastic subspace IDENTIFICATION (SSI) method and analytical solutions. The findings reveal the accuracy of the modal IDENTIFICATION approach introduced in this article. The highest relative error in estimating the natural frequencies of the first and second modes, compared to the values from the laser method, are 0.19% and 0.13%, respectively, and in comparison to the analytical values, they are 0.34% and 1.5%, respectively.

Currently there are just a few papers about fault detection of tubes and cylindrical shells. Recently, methods based on modal curvatures have gained great attention due to their sensitivity to defects. But the methods require dense number of data extraction points which limits their industrial application. In this research a new method for DAMAGE IDENTIFICATION of cylindrical shells has been introduced. The method does not need intact structure's data and in contrast to other methods requires a few data extraction points. By transferring the modal information of the structure to the ANN, output of the network is exact position of the defect on the structure and the method does not need skilled technician to interpret the data. Performance of the network is validated by unfamiliar data for the network and 0. 97 regression is obtained.

Identifying the constraining factors of production and yield gap is very important. Therefore; this research was performed to identify the production constraining factors of local rice cultivars. All management practices from nursery preparation to harvesting stages for 100 paddy fields of local rice cultivars were recorded through field studies, in Sari, from 2015-2016. In the CPA, the actual and calculated potential yield were 4495 and 5703 kg/ha, respectively and the gap was 1221 kg/ha. The yield gap caused by number of top-dressing variables was 324 kg/ha, equal to 27% of the total yield gap. The yield gap related to previous year of legumes cultivation was 218 kg ha-1, equal to 18% of the total yield variation. Among the 10 variables entered in the CPA model, the effects of top-dress fertilizer application and its application frequency and foliar application were remarkable, which could compensate a significant part of the yield gap (444 kg/ha, 37% of total) in the farmers’ fields by managing these variables. According to boundary line analysis (BLA) finding, actual yield mean on the basis of optimal limit related to 12 variables under study was 5369 kg/ha, with 881 kg/ha yield gap . Mean relative yield and relative yield gap for 12 variables (transplanting date, seedling age, number of seedlings per hill, planting density, nitrogen and phosphorous per hectare, nitrogen before transplanting, harvesting date, lodging problem, pest problem, diseases problem and weeds problem) were 83.64 and 16.35 kg/ha, respectively. Based on the finding, it can be stated that the model precision is appropriate and can be applied for both estimation of the quantity of yield gap and determining the portion of each restricting yield variables.

Vibrating Particles System (VPS) optimization is a recently developed metaheuristic algorithm for optimization. This algorithm is inspired by the free vibration of freedom systems' single degree with viscous damping. In this method, each answer is modeled as a particle that moves to its equilibrium position; new positions of the vibrating particle system are updated according to a historically best position. Enhanced Vibrating Particles System (EVPS) uses new approaches to improve the performance of the VPS algorithm. In this study, a dynamic method and modal based approach consisting of natural frequencies and mode shapes are used in the objective function formulation. To demonstrate the performance of the VPS and EVPS, di erent truss structures including several multiple elements scenarios with noise and without noise in modal data are considered for detecting DAMAGE problems. Additionally, all scenarios are studied with signi cant mutations. Results show that the EVPS algorithm has reached better answer than the VPS algorithm for DAMAGE detection problems.