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Detection & Classification of power quality (PQ) disturbances are the most important problems in distribution systems. In this paper, a new approach for the detection and classification of single and combined PQ disturbances is proposed which utilizes fuzzy logic and particle swarm optimization (PSO) algorithms. In this approach, first suitable features of the waveform of PQ disturbances are extracted. Extraction of these specifications is done based on the Fourier and Wavelet transforms. Then, the proposed Fuzzy systems make decision about the type of each of the PQ disturbances by employing these specifications. The PSO algorithm is used for accurate determination of each parameter of the membership functions of the systems. To test the proposed approach, the waveform of PQ disturbances was assumed to be in a sampled form from single and combined categories. Impulse, interruption, swell, sag, notch, transient, harmonic, and flicker phenomena are considered as single disturbances for voltage signal. More over, harmonic with swell, swell with harmonic, swell with transient, harmonic with sag, sag with harmonic and sag with transient are considered as combined disturbances for the voltage signal. Simulation results denote capability of the proposed approach for identification of single and combined disturbances with about 99% accuracy.

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In this paper, crack detection possibility in an arch dam structure is investigated by wavelet transform analysis. An arch dam is a solid concrete dam, curved upstream in plan. In addition to resisting part of the pressure of the reservoir by its own weight, it obtains a large measure of stability by transmitting the remainder of the water pressure and other loads by arch action into the canyon walls. The complete necessity of high safety, economical design, complex of designing and its application increase the importance of concrete arch dams. Successful arch action is dependent on a unified monolithic structure, and special care must be taken in the construction of an arch dam to ensure that no structural discontinuities such as open joints or cracks exist at the time the structure assumes its water load. According to the principles of theory of structures, there is a relationship between the dynamic and static responses and, consequently, the stiffness. Any sudden change in stiffness leads to dynamic and static response variation. This condition will help to estimate the damage and to investigate the structural response before and after the failure. Wavelet analysis has recently been considered for damage detection and structural health monitoring (SHM). It provides a powerful tool to characterize local features of a signal. The basis function in wavelet analysis is defined by two parameters: scale and translation. This property leads to a multi-resolution representation for stationary signals. It has high ability in analysis of static and dynamic response signals. Staionary wavelet transform (SWT) can show the location of frequency changes. That these locations are the points that they have been damaged. The case study is the concrete curvature arch of KAROON-1 (Shahid Abbaspour) dam with the height of 200 m. This dam is considered as one of the most complex dams because of different external and internal radia and angles, as well as asymmetrical center of the external and internal archs in different levels. Using the geometrical dimensions of the above-mentioned dam- from respective design sheetsand its mechanical and physical properties, the dam with and without crack was modeled by the ABAQUS FE software package. After frequency analysis of the dam by ABAQUS for both safe and cracked models in the same frequency mode, displacement responses at the cracked level (crest) were extracted along the reservoir’s longitudinal axis. Afterwards, the responses were used for the wavelet analysis by the wavelet toolbar of the MATLAB software and the detection of crack in the dam structure was investigated with SWT. The results of wavelet analysis showed that the graphs have considerable rise at or around the crack location. But there was no noise or any harmony in the graphs of the safe dam. Hence, detecting the location of crack in dam structures is possible with wavelet transform.

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Drilling of composite materials is one of the major processes in the manufacturing and assembly of sub-component. However, drilling of composite laminates can cause several damages such as degradation in residual tensile strength. In this study, effects of cutting speed, feed rate and drill angle on residual tensile strength of drilled laminates has been investigated. For this purpose, the Taguchi method was employed for three factors at three levels. Acoustic emission signals and wavelet analysis are used to monitor residual tensile strength. The experimental results indicated that the feed rate has the most significant effect. Based on time-frequency analysis of AE signals, it was found that AE signals with frequency ranges of (62.5-125), (250-312.5) and (312.5-375) KHz were generated from matrix cracking, fiber slipping and fiber breakage respectively.

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Structures get local damages by passing time during the service period under environmental conditions and loads, although insignificant. It is essential and important to maintain the health, durability and proper performance of structures and their various parts and lack of proper recognition of the behavior of structures may cause spontaneity damages and consequently, high social and economic costs may occur. According to the proper performance of CFST columns, using this type of columns in high-rise buildings and bridge structures has expanded especially in seismic areas. Steel and concrete can cover each otherchr('39')s weaknesses by simultaneously using concrete and steel in CFST columns. The weakness of concrete against tensile and the weakness of steel against pressure has compensated by the combination of steel and concrete in this type of columns. Also these columns may be damaged during construction or after experiencing load periods (earthquake, wind, etc.), because getting structures damage is inevitable. One of the primary goals of Structural Health Monitoring (SHM) is damages detection of the structure in the early stages of formation. If the damage locations in the structure can be determined and its gradual course can be observed, the damaged members can be repaired or replaced before reaching the critical condition and occurring complete breakdown. Among the methods of damage detection, many researchers consider the methods based on signal processing. One of the methods of signal processing is the mathematical method of wavelet analysis. By using wavelet analysis, more information can be obtained from the intended signal based on its ability to localize the signal in both time and frequency domains. One of the most probable damages in CFST columns is the debonding of the concrete core from the steel tube. In this paper, the CFST column element was modeled and frequency analyzed in ABAQUS finite element software in two conditions including damage and no-damage. The effect of the debonding was considered by decreasing the modulus of elasticity of the concrete in the damage places with depth of 3 mm. The results of the analysis have shown that the information of the mode shapes of the damage and no-damage conditions (angle between the mode shape vectors and the frequency values) changes due to the effect of the damage. In order to identify the debonding damage locations, in the Continuous Wavelet Transform (CWT) detection algorithm, the input signal was defined as the sum or difference of the mode shape of the damage condition and the mode shape of the no-damage condition based on the angle between the damaged and no-damaged mode shape vectors. The results showed that the output signals obtaining from the details of input signal wavelet analysis have useful information to identify the debonding locations of the concrete core from the steel tube and at high scales, the locations of the debonding damage identify easily, and at low scales, more convergence of wavelet coefficients is observed in the locations of the damage. According to the results, the proposed method was introduced as an effective detection method of debonding damage in CFST columns.

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The health of structures, provision of safety, and the sense of security are among constant requirements and perpetual challenges of engineering and managers in the field of crisis management. Erosion and occurrence of minor local damage to structures and structural members in the early stages of construction or during operation, especially in critical structures such as power plants, tall buildings, stairs, dams, airports, and hospitals, have always been among major problems. As time passes, Structures are affected by a variety of natural and non-natural destructive factors such as earthquakes, non-systematic excavations, dynamic vibrations resulting from explosions and heavy vehicle traffic. In addition, factors such as serviceability expectation beyond the design capacity of structural elements and failure to meet the latest expectations imposed by regulations, use of poor-quality materials and execution problems will reduce efficiency and, consequently the service life of structures. Also, the spread of local damages in structures can impair the overall health of the structure. Undoubtedly, knowledge of structural health and safety is of vital importance and structural health monitoring is recognized as one of the most important subjects that has received a lot of attention from researchers. Plates are one of the most important structural elements that can, when damaged, progressively transfer damages to other elements and lead to overall structural damage incurring irreparable social and economic costs. Due to the increasing applications of steel plates, especially in building structures (as steel plate shear walls) in the present study attempts were made to focus on damage detection and localization as one of the most important steps of health monitoring using modal dynamic data (natural frequencies and mode shapes) and a proposed diagnostic method based on two-dimensional discrete wavelet analysis. To this end, the modeled steel plate was subjected to frequency analysis in ABAQUS finite element analysis software and the modal data associated with damaged and non-damaged states were extracted. The results showed differences between the frequencies and lack of correlation between primary and secondary vibration mode shapes based on the modal assurance criterion (MAC) and the angle between the primary and secondary mode shape vectors. Using a propoed damage localization index (DLI) based on the wavelet coefficients obtained from the diameter details of the two-dimensional wavelet analysis of the primary and secondary vibration mode shapes, the damage zones were detected by creating a maximum relative jumps in the DLI diagram. Studies showed that DLI values are sensitive to the damage severity of the damage zone and with increasing the damage severity, these values increase in fixed spatial coordinates in the damaged zone. Also, the DLI of one damaged zone is independent of the damage severity of the other damaged zones, and this is a positive advantage in the damage determination process. Otherwise, failure to detect one damaged zone may affect the detection of other damaged zones, and consequently pose problems in the process of damage detection and localization in cases where we are dealing with multiple damage zones. According to the results of the present study, DLI can be proposed as an efficient and effective index in detection and localization of damages in steel plate elements.

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The health of structures, provision of safety, and the sense of security are among constant requirements and perpetual challenges of engineering and managers in the field of crisis management. Erosion and occurrence of minor local damage to structures and structural members in the early stages of construction or during operation, especially in critical structures such as power plants, tall buildings, stairs, dams, airports, and hospitals, among others, have always been among major problems. In case the damage sites are not identified timely and decisions are not made appropriately, substantial irreparable damage is expectable. Structures are always affected by various natural or unnatural factors such as earthquakes, explosions, and unprincipled excavations, which can aggravate the local damage in them and lead to their destruction, hence substantial human and financial losses. Therefore, it is highly crucial to monitor the health of structures and structural members. Therefore, health monitoring in structures and structural members is highly important. The column is one of the most significant members of engineering structures, especially in building structures and bridges, so that the instability of one of these members can lead to instability and destruction of the structure. Hence, design engineers expect columns to be the last members of structures to be damaged. In this paper, the health monitoring of the column as a structural member was performed by considering the effect of axial load on modal dynamic responses (i.e., natural frequencies and mode shapes). The results showed that the natural frequencies of all modes in both healthy and damaged states decreased with increasing axial load in proportions of the base critical load (the worst-case limit load). Also, at the same loads, the frequency of the healthy sample was always higher than that of the damaged sample so that the frequency difference between healthy and damaged states increased with greater severity of the damage. By introducing a Damage Detection Index (DDI) based on the wavelet coefficients obtained from the details of wavelet analyses of damaged and undamaged modes, the damage sites could be identified with a simple check and high accuracy by observing vibrations in DDI. Also, studies have shown that the DDIs of different damaged sites are independent of each other and are only affected by the severity of the damage and that the effects of axial load on DDI are very small and negligible. The independence of the DDIs of different damaged sites indicates the effectiveness of the proposed method in identifying damaged sites. Otherwise, failure to identify one damaged site may affect the identification of other damaged sites. The damage detection capability using the proposed DDI was investigated in columns with different support sections and conditions, and successful troubleshooting results were obtained. Moreover, investigations were performed with other wavelet functions, and the damage site was successfully identified. The proposed damage detection indicator is an efficient index in the column structures under the effect of axial load with axial buckling-prone support conditions and is proposed as a reliable method in identifying column damage sites in practical health monitoring of structures.