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فهرست مطالب نویسنده:

mohammad javad khosraviani

  • محمدجواد خسرویانی، امید بهار*، سید هومن قاسمی

    تشخیص آسیب یکی از ابزارهای مهم پایش سلامت سازه برای ارزیابی بهتر سازه ها در طول عمر آنها می باشد. بسیاری از مطالعات به ارایه روش هایی برای تعیین محل آسیب با استفاده از مدل های تحلیلی و آزمایشگاهی مانند مدل های شاخص پرداخته اند. هدف اصلی این مقاله ارایه روش جدید تشخیص محل آسیب ترکیبی برای شناسایی مکان های آسیب با استفاده هم زمان از شاخص های آسیب پذیری انرژی و جابه جایی می باشد. در بخش اول از طریق شاخص انرژی فرکانس آنی EDI و پاسخ های شتاب سازه به تعیین الگوهای آسیب پرداخته شده است. در بخش دوم به منظور ارزیابی روش اول و همچنین ارایه روشی سریع برای ارزیابی آسیب از طریق شاخص آسیب جابه جایی که متشکل از شاخص قابلیت اعتماد خطا β و شاخص تابع چگالی احتمال نرمال  G(x)با استفاده از پاسخ های نسبی جابه جایی سازه ASCE ارایه گردیده است. نوآوری این روش استفاده هم زمان از پاسخ شتاب- جابه جایی در طی یک فرایند است که در ارزیابی سریع الگوهای آسیب موثرتر است. برای صحت سنجی روش های ارایه شده، علاوه بر الگوهای آسیب موجود در مسئله شاخص، آسیب جدید دیگر مورد بررسی قرار گرفته است. تجزیه وتحلیل گسترده نشان می دهد که روش پیشنهادی، محل دقیق آسیب وارده به سازه را با دقت کافی و سرعت مناسب تعیین می نماید.

    کلید واژگان: تشخیص آسیب، پایش سلامت سازه، شاخص انرژی فرکانس آنی
    MohammadJavad Khosraviani, Omid Bahar *, Seyed Hooman Ghasemi

    Identification of the modal parameters of the damaged structure by signal processing of vibration based on changes in dynamic properties such as frequency, stiffness, and mode shape of structures. Some of these approaches fail when applied to civill engineering structures, the main reasons are the low sensitivity of the structural response to the damage location, or the low accuracy of structural response obtained by installed sensors. However, due to the rigorous evaluation and low cost of signal processing methods, this method has made a great progress. Signal processing methods have been extensively employed to examine the measured system responses and determine system variations. These methods include Fourier analysis, wavelet transform and Hilbert-Huang transform.During the last decades, the number of vibration-based damage detection methods has been greatly developed and has influenced much of the research. The purpose of these methods is to determine the resulting changes in the modal characteristics of the structure including its natural frequency, mode shape, and damping ratio. For example, the basis of the Fourier transform method is to determine the structural modal parameters from the random vibration data in the frequency range. However, time-frequency analysis is introduced to overcome the limitations of the Fourier method, the most important of which is not providing a frequency-time range of a signal. The first case of frequency-time analysis was the short-time Fourier transform method based on the Fourier transform of the data divided by the time window function. According to this method, the interaction between time and frequency is difficult due to the existence of the time window function. If the windows are smaller in the time segment, its accuracy increases, and in the frequency domain it becomes less accurate.Several damage detection methods have been proposed based on the vibration signal of structures. In most of them, a damage index has been described as the difference between damage and undamaged structure. This paper intends to propose a damage detection method based on the amplitude coefficient correlation of damaged and undamaged responses of structures, while a signal decomposes to IMFs and the changes appear in the first IMF. Therefore, every change on the original signal can be revealed on IMFs, since the original signal depends on IMFs. Also, these changes have an effect on the analytical signal and the Hilbert transform. The instantaneous frequency is measured joints on the structure is calculated by the Hilbert transform of the first IMF of response. Then, by introducing the instantaneous frequency energy (EDI), the location of damages are detected. To assess the feasibility and reliability of the proposed method, the ASCE benchmark problem has been used. To consider the robustness of the proposed method, contamination of signals during the data acquisition process is investigated. The ASCE benchmark study is carried out by the International Association (IASC) ASCE Structural Health Monitoring Task Group. The dynamic responses of the structure have been obtained by numerical analysis under random vibration loading. To evaluate the HHT method, it is required to attain the damaged responses of the ASCE benchmark. The first five damage patterns of the ASCE benchmark building is used. Then the damage on the structure is detected with a comparison of damage and undamaged dynamic responses. According to the measured noise levels, dynamic responses to noise values have been contaminated and the results have been evaluated. According to the results, this method can trace the location of the damage by the energy of instantaneous frequency. Therefore, the locations of damages in different scenarios were located with the EDI index and velocity vector. The results show that the proposed method determined the location of damage with the acceptable accuracy for low and moderate damage in damage scenarios.

    Keywords: damage detection, Structural health monitoring, HHT method, Instantaneous Frequency Energy Index
  • محمدجواد خسرویانی، امید بهار*، سید هومن قاسمی

    تشخیص بهنگام آسیب پل ها یکی از دغدغه های همیشگی مهندسین بوده است. در این مقاله تلاش شده با ارایه ی روش جدیدی براساس پاسخ های شتاب سازه و دامنه های آنی آنها، محل آسیب در عرشه ی پل ها تشخیص داده شود. برای این منظور، ابتدا براساس پاسخ های شتاب، مقادیر دامنه آنی پاسخ های سازه ی سالم و آسیب دیده از طریق تبدیل هیلبرت-هوآنگ HHT محاسبه شده است. در ادامه، با معرفی شاخص جدید آسیب همبستگی متقابل (DICC) به تعیین محل های آسیب در حالت های کلی(Global) و موضعی (Local) پرداخته شده است. برای ارزیابی امکان پذیر بودن، و تخمین قابلیت اعتماد روش های پیشنهادی در تشخیص آسیب در دو سطح کلی و موضعی، از چند مدل تحلیلی پل بتنی یک تا سه دهانه، و همچنین یک مدل آزمایشگاهی تیر دو سر ساده فلزی استفاده شده است. از طرف دیگر، به منظور درنظرگرفتن اغتشاشات محیطی در هنگام برداشت داده ها، مقدار نوفه مشخصی به پاسخ های تحلیلی اضافه شده است. به این ترتیب شرایط برداشت داده های حقیقی در محل مشابه سازی شده است. نتایج ارزیابی ها در مدل های تحلیلی و آزمایشگاهی نشان دادند که روش پیشنهادی، می تواند برای سناریوهای مختلف آسیب، محل های آسیب را با دقت کافی تعیین نمایند. همچنین نتایج روش شاخص آسیب همبستگی متقابل DICC برای تمامی مدل های تحلیلی و آزمایشگاهی، بیانگر این نکته است که با ارزیابی سریع تر توانست است نتایج دقیق تری را ارایه دهد.

    کلید واژگان: تشخیص آسیب، پایش سلامت سازه، دامنه آنی، شاخص همبستگی متقابل، اثر اغتشاش محیطی
    Mohammad Javad Khosraviani, Omid Bahar *, Seyed Hooman Ghasemi

    The damage detection (DD) of the bridge has always been major concerns for engineers. This paper attempts to detect damage in the continuous deck bridges by providing a new method based on acceleration responses and their instantaneous amplitudes. The DD in this paper has two steps: firstly, determining the vicinity of damage in global DD. Secondly, determining the location of damage in local DD. Then by acceleration signals, the instantaneous amplitude values of healthy and damaged structural responses extracted via HHT. Further, for accurate evaluation of the proposed method, damage locations are determined by the cross-correlation damage index (DICC). To assess the feasibility and reliability of proposed methods, several analytical models of concrete bridges of one to three-spans, as well as experimental model a simply supported steel beam, have been used. In order to consider noise pollution during data acquisition, a certain amount of noise is added to the response. The results in the analytical and experimental models showed that the proposed methods can determine the damage locations with appropriate accuracy for different damage scenarios and it could provide more exact results with a rapid estimation.

    Keywords: damage detection, Structural health monitoring, Instantaneous amplitude, Cross-correlation, ambient noise
  • محمدجواد خسرویانی، مجید قاسمی*

    در این مقاله یک روش جدید تشخیص خرابی بر اساس تبدیل هیلبرت- هوانگ پاسخ های اندازه گیری شده سازه تیر ارایه شده است. توابع مودی ذاتی پاسخ های دینامیکی سازه با استفاده از تجزیه مودی تجربی در نقاط مشخص محاسبه شده و تبدیل هیلبرت برای محاسبه دامنه آنی بر روی هر تابع مودی ذاتی به کار برده شده است. ضریب همبستگی و تابع همبستگی متقابل دامنه آنی پاسخ های سالم و خراب سازه محاسبه شده اند. محل خرابی از طریق تعریف پارامتر شاخص خرابی و مقایسه نمودار آنها در حالت های سالم و خراب به دست آمده اند. برای ارزیابی و دقت روش یک مدل المان محدود سازه تیر بتنی دو دهانه مدل شده است. پاسخ های دینامیکی تیر با استفاده از تحلیل عددی تحت بارگذاری مثلثی مشخص به دست آمده اند. با توجه به نوفه های اندازه گیری، به پاسخ های دینامیکی مقادیر نوفه اضافه شده و نتایج مورد بررسی قرار گرفته است. نتایج حاصل نشان دادند که روش ارایه شده محل خرابی را با دقت خوبی تشخیص می دهد.

    کلید واژگان: تشخیص خرابی، تبدیل هیلبرت هوانگ، تجزیه مودی تجربی، ضریب همبستگی
    Mohammad Javad Khosraviani, Majid Ghasemi *

    One of the main concerns for structures and infrastructures is to evaluate their reliability and functionality as they can suffer long-term damage due to gradual deterioration over time, or they can be imposed to natural or manmade hazards and overloading during their lifetime. Thus, Structural Health Monitoring (SHM) has been a hot research topic in order to introduce efficient methods and feasible techniques for evaluating, monitoring and improving structural reliability and life cycle management. The SHM process typically includes three stages: a) data acquisition: measurement of the structural responses using an array of sensors; b) extraction of damage-sensitive features; and c) analysis of extracted features to develop statistical models and estimate structure health condition. During the last decades, vibration-based damage detection methods have been greatly developed. The purpose of these methods is to determine the resulting changes in structural properties including stiffness, natural frequency, mode shape and damping ratio of the structure. For example, the basis of the Fourier Transform (FT) method is to determine the structural modal parameters from the random vibration data in the frequency range. Since local damages mostly impact higher frequency modes which are hard to excite and detect, most of FT based methods are unable to detect local or light damages accurately. Therefore, time-frequency analysis is introduced to overcome the limitations of the Fourier method, the most important of which is not providing a frequency-time range of a signal. The first case of frequency-time analysis was the short-time Fourier transform method based on the Fourier transform of the data divided by the time window function. According to this method, the interaction between time and frequency is difficult due to the existence of the time window function. If the windows are smaller in the time segment, its accuracy increases and in the frequency domain it becomes less accurate. The signal processing techniques such as wavelet transform and the Hilbert-Huang transform are playing an increasingly important role in structural health monitoring. Hilbert-Huang transform (HHT) is a novel signal-processing technique for analysing nonstationary and nonlinear signals. HHT method consists of empirical mode decomposition (EMD) and Hilbert transform (HT). According to this theory, the primary signals can be decomposed into different basic time-dependent intrinsic mode functions (IMFs) through the empirical mode decomposition (EMD). Afterward, instantaneous frequency and amplitude of each IMF can be obtained as Hilbert–Huang spectrum. The application of HHT based approaches in structural health monitoring has been widely studied through the numerical and experimental researches. This paper proposes a damage detection method based on the amplitude coefficient correlation of responses of damaged and undamaged structures using Hilbert–Huang transform (HHT). Structural responses have been decomposed to intrinsic mode functions (IMFs) through the empirical mode decomposition (EMD) method and the changes appear in the first IMF. Therefore, every change on the original signal can be revealed on IMFs, since the original signal depends on IMFs. Also, these changes have an effect on the analytical signal and the Hilbert transform. The instantaneous amplitude in measured joints on the structure is calculated using the Hilbert transform of the first IMF of response. The coefficient correlation matrix of the damaged and undamaged elements is demonstrated by graphical diagram in order to estimate the location of the damage. In this research, the accuracy of proposed damage detection method has been verified by applying the method on a finite element model of two-span continuous concrete beam structure. The concrete beam is 80 m long with two equal 40 m span bays covered by a concrete deck with 0.5 m thickness. The dynamic responses of the beam at all sensors have been obtained by numerical analysis of finite element model under triangular pulse loading. The responses were also contaminated with 2% random noise to consider measurement uncertainties. The damage has been modelled as stiffness reduction in a 1.25 m long segment of finite element model of beam. To evaluate the efficiency of the proposed method, different damage scenarios are studied. IMFs of all responses at sensor locations were obtained by combination of EMD and HT, and the instantaneous frequency and amplitude of Hilbert were derived. Auto correlation of instantaneous amplitude of undamaged and damaged structures were calculated and introduced as Damage Index Correlation. According to the results, this method is able to trace the location of the damage by the comparison of the correlation coefficients. Therefore, the locations of damages in different scenarios were located with a variety of coefficients correlation in sensors. The results show that the proposed method can determine the location of the damage with an acceptable accuracy for low and moderate damage intensities in all damage scenarios.

    Keywords: Hilbert-Huang Transformation, Structural Health Monitoring, Empirical Mode Decomposition, Correlation Coefficient, Damage Detection
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