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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/2784

Title: Sensor placement method for effective monitoring of structural elements
Authors: Iu, Chi-kin Jerry
Subjects: Structural engineering.
Hong Kong Polytechnic University -- Dissertations
Issue Date: 2000
Publisher: The Hong Kong Polytechnic University
Abstract: A large civil engineering structure consists of a huge sum of components or elements with great variation of stiffness, and a damage identification algorithm for such a structure seems to be difficult with limited number of sensors. A question on how to place the sensors to monitor this large civil structure effectively has to be answered. This sensor placement problem can be based on the sensitivity, as presented by the Cobb and Liebst (1997), and the sensor locations according to this Co-linearity Matrix Method are fundamentally based on the high eigenvector sensitivities at the degrees-of-freedom. Also this sensor locations may localize on some highly sensitive elements, when the sensor selection is based on the high eigenvector sensitivity. As a result, these selected sensor locations are impossible to monitor all elements effectively. On the other hand, in the proposed method, the selection of the sensor locations is based on the eigenvector sensitivities according to the particular group of elements. These sensor locations therefore depend on the different elements which are chosen to be monitored. According to the different elements chosen for monitoring, the sensors are allocated around these elements. And the sensors are therefore not placed around some highly sensitive elements. Moreover the reliable damage information emitting from the elements chosen for monitoring is also a criterion for sensor selection in the proposed method, Hence the selected sensor locations enable the collection of adequate damage information from the elements for effective health monitoring.
The sensors according to the proposed method can collect relatively large damage information emitted from the elements by comparing with different sensor placement methods, such as co-linearity Matrix Method and Effective Index Method. This damage information is an indicator of the effectiveness of health monitoring. It means that the selected elements are more effectively monitored by the given sensors configuration according to the proposed method. For the analysis of the damage assessment, the damage localization and quantification for the damages is evaluated basing on the corresponding sensor locations from the different sensor placement methods as previously mentioned. This damage assessment is mainly based on the MDLAC method, The results for the proposed method indicate that the effectiveness of damage assessment is relatively better than those in accordance with other methods, but the accuracy of the damage assessment by using MDLAC method is a little bit poor. According to the same basis for comparison, this analysis of damage assessment for the different sensor placement methods is fairly comparable to be accepted at this stage. As an example application, the sensor placement methods, including the proposed method and the Co-linearity Matrix Method, are applied to the Tsing Ma Bridge. According to the results of this analysis, the sensor locations basing on the Co-linearity Matrix Method concentrate on some highly sensitive elements. On the other hand, the sensor locations from the proposed method are scattered around the different structural components of the bridge according to which elements need to be monitored. Intuitively, the structural health monitoring for this kind of large civil structure is relatively effective by means of the proposed method.
Degree: M.Phil., Dept. of Civil and Structural Engineering, The Hong Kong Polytechnic University, 2000.
Description: viii, 162, [5] leaves : ill. ; 30 cm.
PolyU Library Call No.: [THS] LG51 .H577M CSE 2000 Iu
Rights: All rights reserved.
Type: Thesis
URI: http://hdl.handle.net/10397/2784
Appears in Collections:PolyU Electronic Theses
CEE Theses

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