162 C. Rainieri and G. Fabbrocino 15.2 Teaching Methodology and Objectives The basic background statement, supported by the experience, is that effective teaching and learning can come only from a genuine passion. Lectures, discussions, experiments are fundamental means to convey ideas and concepts but they can be ineffective if they do not reach the hearth and mind of students. For this reason, the main objective of the teaching activity is to raise passion for the subject in students, so creating an inspirational environment. However, raising passion towards certain topics, such as structural dynamics and OMA, can be difficult in the absence of a careful reflection about the teaching method and, above all, of a genuine passion of the teacher. In the Authors’ opinion this circumstance can occur whenever a strong connection between research and teaching activities in a given domain exists. The possibility to carry out research as well as teaching activities in the field of structural dynamics makes possible the presentation of structural dynamics from different perspectives (direct/numerical and inverse/experimental). This, together with the presentation of a number of applications that connect the classroom to the real world outside, is the most appreciated aspect of the proposed course. The main difficulties in approaching the study of OMA are usually related to the heavy mathematical formulations and derivation of mathematical models and equations. Thus, a more practical approach to teaching and learning is advisable with no penalty for theoretical derivations. For this reason, first the students receive the basic notions of LabView programming. Then, class applications and homework are assigned throughout the course to stimulate the students, who are motivated to develop their own software. The presentation of the results of applications compels them to review and analyze also the basic mathematical derivations. This approach fosters the development of problem solving skills and encourages the students to work collaboratively, reducing at the same time the math anxiety. Illustrating the fundamentals of LabView programming gives the students the opportunity to develop simple data acquisition and processing systems and do practical modal identification experiments. The development of collaborative projects like this promotes the interaction among classmates with different background. The definition of different roles when cooperating in a project enhances the teamwork abilities. Public presentations of the completed exercises at the middle and the end of the course support the review of the main concepts of the course and an open discussion among the students, who can share ideas, make proposals to improve the work of the colleagues and focus on less investigated aspects. However, a course cannot be effective and reach the hearth and mind of students if it is based only on technicalities and theoretical derivations. Thus, a continuous effort is made to give the students the big picture and not only the individual notions. Real applications coming from our research experience are often illustrated and discussed, pointing out the advantages of OMA for practical applications and eventual weaknesses related to specific case studies. Lectures usually follow a path based on three key points. In fact, memorization is simplified if no more than three messages/concepts are presented. A recursive approach is also used, repeating the three key points and providing more and more details and illustrative examples during the lecture. The Authors finally try to be mentors for students, in the sense that an open door policy is operated whenever possible, encouraging students to ask for clarifications about specific aspects of the class even outside the scheduled office hours. 15.3 Organization of the Course The course is organized in five parts: 1. Basic principles of OMA and fundamental tools for signal analysis; 2. Test planning; 3. Data acquisition and pre-treatment; 4. Modal parameter estimation; 5. Validation and post-processing of modal identification results. In each moment, applications are proposed to foster the understanding of the theoretical notions and gain sufficient experience to carry out OMA tests independently. In the first part of the course, after having presented the LabView environment [3] and having become familiar with it, the basic principles of OMA and the fundamental mathematical tools for signal analysis are presented. The first critical aspect to explain is how the modal properties can be identified without controlling the input. In this perspective, the roles of sensor layout and unmeasured sources of excitation are critically analyzed.
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