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Decentralized Ambient System Identification of StructuresSadhu, Ayan 09 May 2013 (has links)
Many of the existing ambient modal identification methods based on vibration data process information centrally to calculate the modal properties. Such methods demand relatively large memory and processing capabilities to interrogate the data. With the recent advances in wireless sensor technology, it is now possible to process information on the sensor itself. The decentralized information so obtained from individual sensors can be combined to estimate the global modal information of the structure. The main objective of this thesis is to present a new class of decentralized algorithms that can address the limitations stated above.
The completed work in this regard involves casting the identification problem within the framework of underdetermined blind source separation (BSS). Time-frequency transformations of measurements are carried out, resulting in a sparse representation of the signals. Stationary wavelet packet transform (SWPT) is used as the primary means to obtain a sparse representation in the time-frequency domain. Several partial setups are used to obtain the partial modal information, which are then combined to obtain the global structural mode information.
Most BSS methods in the context of modal identification assume that the excitation is white and do not contain narrow band excitation frequencies. However, this assumption is not satisfied in many situations (e.g., pedestrian bridges) when the excitation is a superposition of narrow-band harmonic(s) and broad-band disturbance. Under such conditions, traditional BSS methods yield sources (modes) without any indication as to whether the identified source(s) is a system or an excitation harmonic. In this research, a novel under-determined BSS algorithm is developed involving statistical characterization of the sources which are used to delineate the sources corresponding to external disturbances versus intrinsic modes of the system. Moreover, the issue of computational burden involving an over-complete dictionary of sparse bases is alleviated through a new underdetermined BSS method based on a tensor algebra tool called PARAllel FACtor (PARAFAC) decomposition. At the core of this method, the wavelet packet decomposition coefficients are used to form a covariance tensor, followed by PARAFAC tensor decomposition to separate the modal responses. Finally, the proposed methods are validated using measurements obtained from both wired and wireless sensors on laboratory scale and full scale buildings and bridges.
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Σχεδιασμός και ανάπτυξη ενός γενικού περιβάλλοντος για υλοποίηση εφαρμογών σε ασύρματα δίκτυα αισθητήρων. / Design and development of a generic environment for developing applications in wireless sensor networks.Μυλωνάς, Γεώργιος 16 May 2007 (has links)
Τα ασύρματα δίκτυα αισθητήρων αποτελούν μια νέα κατηγορία δικτύων υπολογιστών. Αποτελούνται από ένα μεγάλο πλήθος υπολογιστικών κόμβων μικροσκοπικού μεγέθους, εφοδιασμένων με πλήθος αισθητήρων και μονάδων ελέγχου. Σκοπός τους είναι η επίτευξη μιας δύσκολης, για τα δεδομένα του κάθε κόμβου, αποστολής μέσω της συνεργασίας μεταξύ όλων των κόμβων του δικτύου. Τα δίκτυα αυτά αντιμετωπίζονται με μεγάλο ενδιαφέρον από την ερευνητική κοινότητα τα τελευταία χρόνια. Έτσι, έχει προταθεί πλήθος από πρωτόκολλα διάδοσης πληροφορίας, πιθανές εφαρμογές, έχει υλοποιηθεί πλήθος λογισμικού, κτλ. Υπάρχει όμως περιορισμός στα διαθέσιμα εργαλεία για την ανάπτυξη εφαρμογών σε τέτοια δίκτυα, το οποίο σημαίνει από τη μια περιορισμό των διαθέσιμων δυνατοτήτων στους χρήστες και από την άλλη αυξημένη δυσκολία υλοποίησης κάποιας εφαρμογής. Σκοπός της εργασίας αυτής είναι ο σχεδιασμός και η ανάπτυξη ενός γενικού περιβάλλοντος, το οποίο θα προσφέρει στους χρήστες τη δυνατότητα να υλοποιούν σε μικρό χρονικό διάστημα μια εφαρμογή σε ασύρματα δίκτυα αισθητήρων. Το περιβάλλον αυτό, το οποίο ονομάζουμε jWebDust , εκτείνεται σε όλα τα επίπεδα που μπορεί να περιλαμβάνει μια τέτοια εφαρμογή, και επιτρέπει στο χρήστη να αναπτύξει μια εφαρμογή χωρίς ο χρήστης να χρειάζεται να υλοποιήσει ο ίδιος τα επίπεδα αυτά. Η συνεισφορά της παρούσας εργασίας συνοψίζεται σε δύο συνιστώσες: · Το πρωτόκολλο VTRP, το οποίο προσπαθεί να αντιμετωπίσει το πρόβλημα του εντοπισμού και διάδοσης πολλαπλών γεγονότων στα ασύρματα δίκτυα αισθητήρων. Το πρόβλημα αυτό συνίσταται στον εντοπισμό μέσα στο δίκτυο ενός πλήθους από γεγονότα και της διάδοσης των αντίστοιχων αναφορών σε ένα κέντρο ελέγχου, με έναν αποδοτικό τρόπο όσον αφορά την κατανάλωση ενέργειας και την ανοχή σε σφάλματα μετάδοσης. · Το περιβάλλον jWebDust, το οποίο αποσκοπεί στο να βοηθήσει το χρήστη να υλοποιήσει μια εφαρμογή σε ένα ασύρματο δίκτυο αισθητήρων εύκολα και γρήγορα. Βιβλιογραφία: 1. A. Antoniou, I. Chatzigiannakis, G. Mylonas, S. Nikoletseas, A. Boukerche: A new energy efficient and fault tolerant protocol for data propagation in smart dust networks using varying transmission range. In the proceedings of the 37th Annual ACM – IEEE Simulation Symposium (ANSS ’04), April 2004. 2. I. Chatzigiannakis, G. Mylonas, S. Nikoletseas: jWebDust: A Java-based Generic Application Environment for Wireless Sensor Networks. In the proceedings of DCOSS ’05 (International Conference on Distributed Computing in Sensor Systems), Marina Del Rey, June 30 – July 1, 2005 . / Wireless sensor networks are comprised of a vast number of ultra-small fully autonomous computing, communication and sensing devices, with very restricted energy supplies and computing capabilities, which co-operate to accomplish a large sensing task. Such networks can be very useful in practice, i.e. in the local detection of remote crucial events and the propagation of data reporting their realization to a control center. It is expected that, in the future, the wide range of applications of sensor networks will make them an integral part of our lives. The interest of the research community in these networks has grown steadily in the recent years and a plethora of data propagation protocols and possible applications has been proposed, along with a growing number of software applications and real network deployments. There is, though, a lack of available tools for developing applications in sensor networks, which means that there is a lack of available options for the final users and also an increased difficulty in implementing an application for such a network. The aim of this dissertation is the design and development of a generic environment, which will offer the possibility of implementing quick and easy an application for wireless sensor networks. This environment is called jWebDust, and its implementation is based on existing technologies, like the TinyOS operating system for sensor networks, and is targeted towards hardware platforms that are supported by TinyOS. The contribution of this dissertation can be summarized as follows: 1. The VTRP protocol [2], designed to face the (multiple event detection and propagation) problem in wireless sensor networks, which is defined as follows: how can each node in the network via cooperation with the rest of the nodes propagate the information regarding some event to the control center of the network in an efficient and fault-tolerant way. What differentiates VTRP to the other existing protocols is the change of the transmission range of each node, when this is necessitated by the conditions inside the network field. 2. The jWebDust environment [3], which aims at providing a simple interface for creating quick and easy an application for wireless sensor networks. jWebDust provides a simple interface to the final user, through which a variety of actions for administering a wireless sensor network can be performed, and also collection of data from the network nodes can be automated. This dissertation is comprised of the following parts: 1. Current research in wireless sensor networks (chapter 1 - 3): In the first part of this thesis we provide an introduction to the basic concepts in wireless sensor networks and a short overview of their history so far. A presentation of the current research regarding the most important hardware platforms and software applications presented so far concludes this part. 2. The VTRP protocol (chapter 4): a detailed description of the protocol is provided in this chapter, along with results from extensive simulation experiments conducted with the simDust network simulator [1]. 3. The jWebDust environment (chapters 5-6): The overall architecture of jWebDust is presented along with a detailed description of the functional specifications of the system. Bibliography: [1] S. Nikoletseas, I. Chatzigiannakis, H. Euthimiou, A. Kinalis, T. Antoniou and G. Mylonas, Energy efficient protocols for sensing multiple events in smart dust networks, 37th Annual ACM/IEEE Simulation Symposium (ANSS 2004), 2004, pp. 15-24. [2] T. Antoniou, A. Boukerche, I. Chatzigiannakis, G. Mylonas and S. Nikoletseas, A new energy efficient and fault-tolerant protocol for data propagation in smart dust networks using varying transmission range, 37th Annual ACM/IEEE Simulation Symposium (ANSS 2004), 2004, pp. 43-52. [3] I. Chatzigiannakis, G. Mylonas and S. Nikoletseas, jWebDust: A Java-based generic application environment for wireless sensor networks, International Conference on Distributed Computing in Sensor Systems (DCOSS
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Decentralized Ambient System Identification of StructuresSadhu, Ayan 09 May 2013 (has links)
Many of the existing ambient modal identification methods based on vibration data process information centrally to calculate the modal properties. Such methods demand relatively large memory and processing capabilities to interrogate the data. With the recent advances in wireless sensor technology, it is now possible to process information on the sensor itself. The decentralized information so obtained from individual sensors can be combined to estimate the global modal information of the structure. The main objective of this thesis is to present a new class of decentralized algorithms that can address the limitations stated above.
The completed work in this regard involves casting the identification problem within the framework of underdetermined blind source separation (BSS). Time-frequency transformations of measurements are carried out, resulting in a sparse representation of the signals. Stationary wavelet packet transform (SWPT) is used as the primary means to obtain a sparse representation in the time-frequency domain. Several partial setups are used to obtain the partial modal information, which are then combined to obtain the global structural mode information.
Most BSS methods in the context of modal identification assume that the excitation is white and do not contain narrow band excitation frequencies. However, this assumption is not satisfied in many situations (e.g., pedestrian bridges) when the excitation is a superposition of narrow-band harmonic(s) and broad-band disturbance. Under such conditions, traditional BSS methods yield sources (modes) without any indication as to whether the identified source(s) is a system or an excitation harmonic. In this research, a novel under-determined BSS algorithm is developed involving statistical characterization of the sources which are used to delineate the sources corresponding to external disturbances versus intrinsic modes of the system. Moreover, the issue of computational burden involving an over-complete dictionary of sparse bases is alleviated through a new underdetermined BSS method based on a tensor algebra tool called PARAllel FACtor (PARAFAC) decomposition. At the core of this method, the wavelet packet decomposition coefficients are used to form a covariance tensor, followed by PARAFAC tensor decomposition to separate the modal responses. Finally, the proposed methods are validated using measurements obtained from both wired and wireless sensors on laboratory scale and full scale buildings and bridges.
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