2,845 research outputs found

    State of the art of control schemes for smart systems featuring magneto-rheological materials

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    This review presents various control strategies for application systems utilizing smart magneto-rheological fluid (MRF) and magneto-rheological elastomers (MRE). It is well known that both MRF and MRE are actively studied and applied to many practical systems such as vehicle dampers. The mandatory requirements for successful applications of MRF and MRE include several factors: advanced material properties, optimal mechanisms, suitable modeling, and appropriate control schemes. Among these requirements, the use of an appropriate control scheme is a crucial factor since it is the final action stage of the application systems to achieve the desired output responses. There are numerous different control strategies which have been applied to many different application systems of MRF and MRE, summarized in this review. In the literature review, advantages and disadvantages of each control scheme are discussed so that potential researchers can develop more effective strategies to achieve higher control performance of many application systems utilizing magneto-rheological materials

    Modeling of Magnetorheological Dampers under Various Impact Loads

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    Bridge damage detection using an intelligent engineering system

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    This thesis concerns the design of an algorithm that is capable to detect structural damage in civil infrastructure bridges. The algorithm, which will be dubbed Damage Diagnostics System throughout the thesis, is the software component of a broader Bridge Health Monitoring System. This broader system integrates software and hardware,such as sensors and data acquisition components...The rationale for the Structural Damage Diagnosis is based on the principle of the structural vibration testing. The Health Monitoring System captures the vibration signals, as the bridge responds to excitation from various sources. The purpose of the Diagnostic System is to extract information from the vibration signals concerning the damage condition of the bridge. This system will identify and quantify the damage, by examining the shifts in the vibration signature. This can be performed with a comparison between the actual vibration signal and the vibration behavior of the undamaged bridge --Introduction, page 1

    Recent advances in intelligent-based structural health monitoring of civil structures

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    This survey paper deals with the structural health monitoring systems on the basis of methodologies involving intelligent techniques. The intelligent techniques are the most popular tools for damage identification in terms of high accuracy, reliable nature and the involvement of low cost. In this critical survey, a thorough analysis of various intelligent techniques is carried out considering the cases involved in civil structures. The importance and utilization of various intelligent tools to be mention as the concept of fuzzy logic, the technique of genetic algorithm, the methodology of neural network techniques, as well as the approaches of hybrid methods for the monitoring of the structural health of civil structures are illustrated in a sequential manner

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

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    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

    Review of prognostic problem in condition-based maintenance.

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    International audienceprognostic is nowadays recognized as a key feature in maintenance strategies as it should allow avoiding inopportune maintenance spending. Real prognostic systems are however scarce in industry. That can be explained from different aspects, on of them being the difficulty of choosing an efficient technology ; many approaches to support the prognostic process exist, whose applicability is highly dependent on industrial constraints. Thus, the general purpose of the paper is to explore the way of performing failure prognostics so that manager can act consequently. Diffent aspects of prognostic are discussed. The prognostic process is (re)defined and an overview of prognostic metrics is given. Following that, the "prognostic approaches" are described. The whole aims at giving an overview of the prognostic area, both from the academic and industrial points of views
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