Providing structural modules with self-integrity monitoring

With the advent of complex space structures (i.e., U.S. Space Station), the need for methods for remotely detecting structural damage will become greater. Some of these structures will have hundreds of individual structural elements (i.e., strut members). Should some of them become damaged, it could be virtually impossible to detect it using visual or similar inspection techniques. The damage of only a few individual members may or may not be a serious problem. However, should a significant number of the members be damaged, a significant problem could be created. The implementation of an appropriate remote damage detection scheme would greatly reduce the likelihood of a serious problem related to structural damage ever occurring. This report presents the results of the research conducted on remote structural damage detection approaches and the related mathematical algorithms. The research was conducted for the Small Business Innovation and Research (SBIR) Phase 2 National Aeronautics and Space Administration (NASA) Contract NAS7-961

Operativna modalna analiza za određivanje svojstava povijesnih građevina

Assessing and reducing the seismic risks associated with historical structures require an appropriate knowledge of structural behaviour and characteristics, as suggested by recent national and international guidelines concerning cultural heritage. However, historical structures are characterised by a high level of uncertainty, which affects material properties and structural schemes and is related to deterioration processes or previous interventions and structural modifications. The level of knowledge can be increased by experimentally evaluating a structure’s dynamic properties, and the resultant data can be used to refine and update numerical models that are representative of the real structural behaviour. Moreover, the periodic monitoring of relevant parameters can help identify eventual deterioration phenomena. Thus, dynamic tests, in conjunction with model updating, are becoming reliable tools for non-destructively assessing historical structures. In this article, a brief discussion of the basic principles of dynamic identification under operational conditions is presented. Two tests with historical structures are then presented, and the main results are reported. The high performance of operational modal analysis techniques and the interesting opportunities these techniques provide for the structural assessment of historical structures are discussed.Ocjena i smanjenje seizmičkog rizika kod povijesnih građevina, zahtijevaju odgovarajuće poznavanje značajki ponašanja takvih konstrukcija, kako to sugeriraju nedavno objavljene nacionalne i međunarodne smjernice za građevine koje spadaju u kulturnu baštinu. Doduše, povijesne građevine su velika nepoznanica što se tiče svojstava materijala i konstrukcijskih sustava, a usto su podložne izmjenama, propadanju te promjenama tipa konstrukcije. Bolji uvid se može dobiti s procjenom dinamičkih svojstava modela konstrukcije, a dobiveni rezultati mogu se upotrijebiti za povećanje preciznosti i kvalitete numeričkih modela za realne konstrukcije. Štoviše, povremeno opažanje relevantnih parametara može pomoći identifikaciji možebitnih procesa propadanja. Zbog toga, dinamički pokusi, povezani s proračunskim modelima, postaju pouzdan alat kao nerazorne metode procjena stanja povijesnih građevina. U članku se razmatraju osnovna načela dinamičke identifikacije u uvjetima upotrebe konstrukcije. Opisana su dva pokusa na modelima povijesnih građevina, a prikazani su i najvažniji rezultati. Raspravlja se o velikoj djelotvornosti tehnike operativne modalne analize te o interesantnim mogućnostima koje ta tehnika pruža za procjenu povijesnih građevina

Design and Implementation of a MIMO Integral Resonant Control for Active Vibration Control of Pedestrian Structures

Peer reviewe

Data Mining Technology for Structural Control Systems: Concept, Development, and Comparison

Structural control systems are classified into four categories, that is, passive, active, semi-active, and hybrid systems. These systems must be designed in the best way to control harmonic motions imposed to structures. Therefore, a precise powerful computer-based technology is required to increase the damping characteristics of structures. In this direction, data mining has provided numerous solutions to structural damped system problems as an all-inclusive technology due to its computational ability. This chapter provides a broad, yet in-depth, overview in data mining including knowledge view (i.e., concept, functions, and techniques) as well as application view in damped systems, shock absorbers, and harmonic oscillators. To aid the aim, various data mining techniques are classified in three groups, that is, classification-, prediction-, and optimization-based data mining methods, in order to present the development of this technology. According to this categorization, the applications of statistical, machine learning, and artificial intelligence techniques with respect to vibration control system research area are compared. Then, some related examples are detailed in order to indicate the efficiency of data mining algorithms. Last but not least, capabilities and limitations of the most applicable data mining-based methods in structural control systems are presented. To the best of our knowledge, the current research is the first attempt to illustrate the data mining applications in this domain

Health monitoring of civil infrastructures by subspace system identification method: an overview

Structural health monitoring (SHM) is the main contributor of the future's smart city to deal with the need for safety, lower maintenance costs, and reliable condition assessment of structures. Among the algorithms used for SHM to identify the system parameters of structures, subspace system identification (SSI) is a reliable method in the time-domain that takes advantages of using extended observability matrices. Considerable numbers of studies have specifically concentrated on practical applications of SSI in recent years. To the best of author's knowledge, no study has been undertaken to review and investigate the application of SSI in the monitoring of civil engineering structures. This paper aims to review studies that have used the SSI algorithm for the damage identification and modal analysis of structures. The fundamental focus is on data-driven and covariance-driven SSI algorithms. In this review, we consider the subspace algorithm to resolve the problem of a real-world application for SHM. With regard to performance, a comparison between SSI and other methods is provided in order to investigate its advantages and disadvantages. The applied methods of SHM in civil engineering structures are categorized into three classes, from simple one-dimensional (1D) to very complex structures, and the detectability of the SSI for different damage scenarios are reported. Finally, the available software incorporating SSI as their system identification technique are investigated

Opportunities and Challenges in Health Monitoring of Constructed Systems by Modal Analysis

Dynamic testing of constructed systems was initiated in the 1960’s by civil engineers interested in earthquake hazards mitigation research. During the 1970’s, mechanical engineers interested in experimental structural dynamics developed the art of modal analysis. More recently in the 1990’s, engineers from different disciplines have embarked on an exploration of health monitoring as a research area. The senior writer started research on dynamic testing of buildings and bridges during the 1970’s, and in the 1980’s collaborated with colleagues in mechanical engineering who were leading modal analysis research to transform and adapt modal analysis tools for structural identification of constructed systems. In the 1990’s the writer and his associates participated in the applications of the health monitoring concept to constructed systems. In this paper, the writers are interested in sharing their experiences in dynamic testing of large constructed systems, namely, MIMO impact testing as well as output-only modal analysis, in conjunction with associated laboratory studies. The writers will try to contribute to answering some questions that have been discussed in the modal analysis and health monitoring community for more than a decade: (a) What is the reliability of results from dynamic testing of constructed systems, (b) Can these tests serve for health monitoring of constructed systems? (c) Are there any additional benefits that may be expected from dynamic testing of constructed systems? (d) Best practices, constraints and future developments needed for a reliable implementation of MIMO testing and output-only modal analysis of constructed systems for health monitoring and other reasons