System identification towards diagnosis to prognosis
Başlık çevirisi mevcut değil.
- Tez No: 401356
- Danışmanlar: PROF. FABIO CASCIATI
- Tez Türü: Doktora
- Konular: İnşaat Mühendisliği, Civil Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2014
- Dil: İngilizce
- Üniversite: Unıversıta Deglı Studı Dı Pavıa (unıversıty Of Pavıa)
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: Belirtilmemiş.
Özet
Özet yok.
Özet (Çeviri)
The civil engineering structural systems maintenance and failures have increased after tremendous disasters such as earthquakes, floods or due to problems of load-resistance capacity, fatigue, corrosion, etc., respectively. These problems result in the assessment necessity of these engineering systems before the catastrophic failures. Structural health monitoring (SHM) discipline and its tools have emerged over the past decade in order to ensure safety by the engineers. This interdisciplinary research field is dealing with the development and implementation of data processing and non-destructive sensing methods aimed to perform condition assessment and damage detection of structural systems (e.g., aircraft, ships, machines and finally civil structures and infrastructures). Recently, the non-linear situation, the on-line and the real-time SHM have witnessed extensive developments. But, some technological problems still remain. High costs and laborious installations of monitoring systems hinder their widespread usage. For instance, wireless sensors have the potential to reduce the cost of monitoring systems while offering onboard data processing capabilities in any sink node of sensor networks. Moreover, there exists a lack of generalized data processing algorithms that extract information from sensed data. This important issue is one of the major concerning parts of system identification field. With the emergence of SHM, system identification has played a significant role since an estimated mathematical model reflecting the system dynamics can be used for diagnosis and prognosis issues. The mentioned chapters herein are an expository contribution on the subject of structural system identification, measured signal processing (data compression) and their applications to structural control, model-based structural health/damage detection (e.g., black-box system identification algorithm), system realizations (e.g., Eigen system realization), parameter estimations and prognosis (reliability) of the various case studies. The study focuses on the state-space oriented system identification theory as specialized to structural dynamics governing equations of motion, various input–output combinations for single-input and single-output or multi-output problems, and robust ways of identifying proportional damping, stiffness, frequency parameters, and the use of identification tools for damage detection from measured response data. The materials covered in this study are largely extracted from the experimental data from laboratory tests carried out at Pavia University, at Civil Engineering Department, and its collaborations from the different institutes and companies under the past and present frameworks of European Union (EU) funded projects.
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