مطالعه تجربي عملكرد روش هاي مختلف آناليز مودال محيطي با تحريك همزمان تصادفي و هارمونيك

Experimental evaluation of various Operational Modal Analysis methods in the presence of simultaneous random and harmonic force excitation

در اين تحقيق عمل­كرد روش­هاي مختلف آناليز مودال محيطي در حضور نيروهاي تحريك هارمونيك مطالعه شده است. يك تير تحت آزمون مودال تجربي قرار گرفته و پارامترهاي مودال آن استخراج شده است. سپس آزمون­هاي آناليز مودال محيطي بر روي تير تحت تحريك­هاي هم­زمان تصادفي و هارمونيك انجام گرديده است. استخراج پارامترهاي مودال به روش­هاي مختلف آناليز مودال محيطي انجام شده و نتايج با پارامترهاي حاصل از آناليز مودال كلاسيك مقايسه شده است. در اين تحليل­ها سعي شده اثر تحريك هارمونيك بر نتايج حذف گردد. نتايج اين بررسي تجربي نشان مي­دهد كه روش زير فضاي اتفاقي در مقايسه با روش­هاي تجزيه حوزه فركانس و تجزيه حوزه فركانس بهبود يافته از دقت بالاتري برخوردار است. زماني كه ميرايي سيستم در يكي از مودها كم باشد، روش­هاي تجزيه حوزه فركانس تخمين بهتري را ارائه مي­كند.

In the present research, performance of harmonic components identification and elimination techniques in practical operational modal data is investigated. Firstly, classical modal testing has been carried out on a cantilever steel beam and modal data are extracted. Four bending modes were available in the frequency band of interest. Afterwards, the same structure underwent operational modal tests with simultaneous random and harmonic excitation forces. In OMA, measurement data obtained from the operational responses are used to estimate the parameters of models that describe the system behavior. Extracted modal parameters from these data compared with baseline parameters. Extraction of modal parameters from operational data was fulfilled through different common OMA techniques. Each set of obtained results was evaluated in comparison with reference results. Accuracy and capability of each method in eliminating spurious modes caused by harmonic input components have been studied. For data analysis, in addition to developed MATLAB codes, commercial software of PULSE has been utilized in parallel as a tool for verification. The results of this survey demonstrate that the accuracy of the Stochastic Subspace Identification method is higher compared to Frequency Domain Decomposition and Enhanced Frequency Domain Decomposition methods. However, when the system has low modal damping, Frequency Domain Decomposition methods provide better estimates.