بهزاد دژکام

Health monitoring and damage detection in structures is important for maintaining the safety and health of individuals as well as for dealing with economic losses. This article compares primary and secondary modal information, including the frequency values and vibration mode shapes, for health monitoring and damage detection in beams. The impact of the damage is observed as a difference between primary and secondary frequency values, as well as a difference between the coefficients of the polynomial curves. Also, the Pearson's Correlation Coefficient (PCC) between the primary and secondary modes is calculated as values other than 1 and -1 that indicate the impact of damage on the relative displacement of degrees of freedom. However, damage locations cannot be identified by curve fitting, correlation, and comparison of natural frequencies; thus, comparison of primary and secondary shapes of vibration modes was made based on determination of central curvature. It was shown that the difference between the primary and secondary curvature graphs occurs as fractures created in damaged positions and in the curvature graph of the secondary situation; hence, the damaged locations are identifiable.

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.

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.

From the past until now, monitoring the health of structures and identifying different locations of damage to their elements have always been one of the basic requirements of maintaining structures and ensuring the safety of residents. Damage is defined as any modification to the shape or material characteristics of a structure that could impair its overall performance. Irreversible damages to structures can be avoided by promptly identifying, repairing, and replacing any damaged components in early stages. Damage to columns, one of the most vital elements of building structures and bridges, can pose serious concerns about the overall health of the structures compared to damage to other elements. This study proposes a detection index based on the slope and curvature of the mode and explores its usefulness in identifying distinct sites of column damage under axial load. The preliminary findings of this research revealed that as the axial load increases, the value of the natural frequency of all modes drops in both healthy and damaged conditions. Considering that the given columns may buckle and become unstable under the impact of axial load less than the design axial load due to damage, this underlines the necessity of addressing the problem of damage detection in columns under this load. The results also demonstrate that the frequency values of healthy and damaged conditions are different due to damage. Damage detection using the suggested index indicates that it is sensitive to the position of the damage, and that by establishing relative maxima in the damaged area, it is possible to recognize the location of the damage with an error less than one percent. In addition, the findings demonstrated that while the amount of axial load affects frequency values, it does not have any effect on the values of the damage detection index.

Numerous researchers focus on monitoring the health of structures to ensure safety and reduce maintenance costs. Beams and columns are the primary elements of structures in civil engineering, and designers expect beams and columns to be the last elements to experience damage. This paper identifies steel beam damage based on dynamic modal data. After a modal analysis was performed on the modeled beam using the ABAQUS finite element software, modal information was extracted, including the frequencies and shapes of healthy and damaged modes. Due to the presence of damage, differences in the frequency values of primary and secondary conditions were observed. In addition, modal assurance criteria (MAC) values below one were obtained, confirming the presence of damage. Using an analytical method based on wavelet analysis, MATLAB.R2021a processed healthy and damaged mode shape signals. In all modes, a comparison of the output signal diagrams of healthy and damaged modes revealed the difference in the damaged area, allowing the damage locations to be identified with an error of less than 2 percent using a simple examination.

Damage to structures is inevitable. Besides, the accumulation and spread of local damage can be a source of global damage; hence, the significance and necessity of monitoring the health of the structure. Wavelet analysis of structural responses is a method of damage detection with optimal performance in the time-frequency domain, which yields more information from the analyzed response of the structure in both time and frequency domains. As beams and columns are among the most fundamental structural elements and, expectably, the last elements to be damaged, it bears greater importance to identify damage in them than in other structural elements. This paper draws on modal analysis data of steel beams modeled in Abacus and a proposal of the wavelet analytical method to track different positions of damage along the beam, where the damages are defined as a decrease in the elastic modal. A decreasing shift in frequency values occurred in all modes due to damage. To detect the damage, the mode shape signal was defined as the damage mode shape and the differentiation between the healthy and the damage mode shapes as the wavelet transform input signal. The output signals from the wavelet analysis of the input signal indicated maximum and minimum relative fluctuations in different situations of damage so that the centers of damage were identified with zero error. The results also revealed that with increasing the severity of the damage, only the irregularity of the wavelet coefficients of that damage position increases.