Damage detection and structural health monitoring of ST-۳۷ plate using smart materials and signal processing by artificial neural networks
محل انتشار: فصلنامه مواد پیشرفته و فرآوری، دوره: 5، شماره: 3
سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 223
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شناسه ملی سند علمی:
JR_JMATPR-5-3_004
تاریخ نمایه سازی: 12 مهر 1400
چکیده مقاله:
Structural health monitoring (SHM) systems operate online and test different materials using ultrasonic guided waves and piezoelectric smart materials. These systems are permanently installed on the structures and display information on the monitor screen. The user informs the engineers of the existing damage after observing signal loss which appears after damage is caused. In this paper health monitoring is done for plate shaped structures made of ST-۳۷ steel. After conducting the experimental tests, the stored signals by the multi-layer artificial neural network algorithm is processed and the damage caused in the plate is detected. By analyzing the graphs, it becomes clear that after causing damage the signal amplitude decreases. In the experimental test two piezoelectric discs are used on a steel plate which have been installed using a strong adhesive. Using a strong adhesive improves wave, propagation in the structure. Developing innovative testing methods for the SHM system has caused better control in structures after assembly.
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نویسندگان
Hamid Reza Mirdamadi
Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Farshad Ghasemi
Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Javad Jafari
Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran