پایش سلامتی و تشخیص آسیب ستون تحت اثر بار محوری با استفاده از داده‌های دینامیکی مودال و روش تحلیلی موجک

همواره سازه‌‌ها تحت اثر عوامل طبیعی و یا غیر طبیعی متعددی همچون زلزله، انفجار و گودبرداری‌های غیر اصولی واقع‌اند که می‌تواند آسیب‌های موضعی موجود در آن‌ها را تشدید نموده و باعث انهدام آن‌ها و در نتیجه، ایجاد خسارت‌های جانی و مالی فراوانی شود؛ بنابراین، پایش سلامتی سازه‌ها و اعضای سازه‌ای بسیار مهم و حائز اهمیت است. در این نوشتار، پایش سلامت عضو سازه‌ای ستون با لحاظ نمودن اثر بار محوری بر پاسخ‌های دینامیکی مودال (فرکانس‌های طبیعی و شکل‌های مود ارتعاشی) انجام شد. نتایج بررسی‌ها نشان داد که فرکانس‌های طبیعی تمامی مودها در هر دو وضعیت سالم و آسیب با افزایش بار محوری به صورت نسبت‌هایی از بار بحرانی مبنا (بار بحرانی بدترین حالت آسیب) کاهش می‌یابد. همچنین، در بارگذاری‌های یکسان، همواره فرکانس نمونه سالم از فرکانس نمونه آسیب بیشتر است؛ به‌طوری‌که با افزایش شدت آسیب، اختلاف فرکانسی وضعیت‌های سالم و آسیب افزایش می‌یابد. با معرفی یک شاخص شناسایی آسیب (ddi) بر مبنای ضرایب موجک حاصل از جزئیات آنالیز موجک شکل‌های مود وضعیت‌های سالم و آسیب، محل‌های آسیب با دقت بالایی به صورت پرش و یا اغتشاش در ddi شناسایی گردید. همچنین، بررسی‌ها نشان داد که ddi محل‌های مختلف آسیب مستقل از هم بوده و تنها متاثر از شدت آسیب محل مورد نظر است و اثرات بار محوری بر ddi بسیار ناچیز و قابل چشم پوشی است. مستقل بودن ddi محل‌های مختلف آسیب نشان دهنده کارآمدی روش پیشنهادی در شناسایی محل‌های آسیب است؛ زیرا در غیر اینصورت، ممکن است عدم شناسایی یک محل آسیب بر شناسایی سایر محل‌های آسیب تاثیرگذار باشد.

health monitoring and damage assessment of a column under the effect of axial load using modal dynamic data and wavelet analytical method

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.