جستجوی مقالات مرتبط با کلیدواژه « انرژی کرنشی مودال » در نشریات گروه « عمران »

Damage to the structure during operation has always been possible, and therefore the issue of monitoring the health of important structures in order to control and manage safe operation has received attention in recent years. The process of extracting the parameters involved in identification the inherent characteristics of the target structural systems in order to monitor and detect damages is possible with different methods which have been introduced and investigated under the title of environmental modal analysis, which have been developed both in the time domain and in the frequency domain. Among the time domain methods, we can mention the stochastic subspace identification (SSI) method. The stochastic subspace identification method is one of the Output Only Modal Analysis (OOMA) methods that has been taken into consideration assuming the existence of uncertainty in modeling as well as noise in data observation and measurement, and system parameters are identification by applying statistical relationships to the output data. Due to the high accuracy of the covariance-drived stochastic subspace (SSI-cov) method which performs data monitoring by constructing the covariance function related to the recorded output data, therefore this sub-method has been used. Due to the limitation in the number of sensors that can be installed in real structures, the use of the Reference-based covariance-drived stochastic subspace identification (SSI-cov-ref) method will make it possible to identification the structure under investigation with a limited number of sensors and if there is damage, Its location can be recognized. The efficiency of the reference-based covariance-drived stochastic subspace identification method with a more limited number of sensors can also be presented. In order to damage detecting in the structure, the method of measuring changes in the modal strain energy of the members in healthy and damaged states has been used, and an index called modal strain energy has been defined and presented But in the case of damage in the structure, the undamaged members will also have strain energy due to the strain effect of the damaged members. Therefore, by using the probabilities approach, it will be possible to provide an index of the probability of structural member damage under a specific failure scenario using different information sources based on the mode shapes. In the following, using the genetic algorithm in the form of an optimization problem, the installation location for the available sensors for the target structure is optimized and presented. During the current research, after finite element modeling in MATLAB software and dynamic analysis of several samples of structure with the assumption of installing a limited number of sensors ,and the results obtained from the output of the reference-based covariance-drived stochastic subspace identification method using the changes in the modal strain energy of the members And the Bayesian strategy has been used in the damage detection in the affected members, and the efficiency of the proposed method has been discussed in the framework of the mentioned process. Based on the results obtained from the output of the proposed process, the affected members will be identified and distinguishable.
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One way to diagnose damage in structures is to use their modal strain energy change index. Since occurrence of damage in parts of a structure, in addition to changing the modal strain energy of the damaged parts, also changes the modal strain energy of the healthy parts, in the vicinity of the main damaged elements, false damaged elements will appear, which makes it difficult to identify the main damaged elements. To solve this problem, in the present work a two-step method has been used to determine the location of the damage on the deck of a concrete bridge. In the first step, by finite element modelling and performing the modal analysis, the initial damage index of different parts of the bridge deck is determined based on modal strain energy changes, using a few vibration mode shapes. In the second step, using weight coefficients, the modified damage index for each element is calculated separately, minimizing the number of false damaged elements. The proposed method for calculating weight coefficients is simple and at the same time accurate. The efficiency of this method was investigated in several damage scenarios with an intensity of only 5% in different parts of the deck of bridge. The results showed that, while the initial damage index could not distinguish even 3 damaged elements in the bridge deck from the healthy elements, the modified damage index was able to identify up to 7 damaged elements in different parts of the bridge deck with good accuracy using only 2 mode shapes.

Changes in modal strain energy of elements before and after damage is a robust damage detection index. However, in structures like double layer grids which have large number of elements, this method has some problems. First, In large structures this method needs more mode shapes to detect damage through modal strain energy method which in practice is difficult to determine. Second, this method introduce some healthy elements as damaged element. To overcome these problems, in this paper a two stage damage detection technique based on modal strain energy method is presented for detecting damage in double layer grids. First, the Modal Strain Energy Based Index (MSEBI) for each mode shape is determined. Then a data fusion technique based on Bayesian theory is used to combine MSEBI values obtained from each mode shape to find damaged elements. Then Charged System Search (CSS) optimization method which is a powerful optimization method is employed to optimize an objective function based on natural frequency to determine damage severity of damaged elements. To demonstrate the performance of the proposed method, a large double layer grid with 1536 elements and different single and multiple damage cases is considered. Numerical results show that the proposed method can successfully find damaged elements and their severities using only few first numbers of mode shapes and frequencies.