Open AccessDesign of a Random Decrement Method Based Structural Health Monitoring System
Author(s) -
H. Buff,
A. Friedmann,
M. Koch,
Torsten Bartel,
Michael Kauba
Publication year - 2012
Publication title -
shock and vibration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 45
eISSN - 1875-9203
pISSN - 1070-9622
DOI - 10.1155/2012/718985
Subject(s) - rdm , structural health monitoring , modal , controllability , computer science , reliability engineering , smoothing , reduction (mathematics) , modal analysis , engineering , real time computing , finite element method , mathematics , structural engineering , computer network , chemistry , geometry , polymer chemistry , computer vision
Structural Health Monitoring (SHM) has reached a high importance in numerous fields of civil and mechanical engineering. Promising damage detection approaches like the Damage Index Method, Gapped Smoothing Technique and Modal Strain Energy Method require the structure's mode shapes [1]. Long term modal data acquisition on real life structures requires a computational efficient system based on a measuring method that can easily be installed. Systems using the Random Decrement Method (RDM) are composed of a decentralized network of smart acceleration sensors applied for both, triggering and pure measuring. They allow the reduction of cabling effort and computational costs to a minimum. In order to design a RDM measuring network efficiently, an approved procedure for defining hardware as well as measuring settings is required. In addition, optimal sensor positions have to be defined. However, today those decisions are mostly based on expert's knowledge. In this paper a systematic and analytical procedure for defining the hardware requirements and measuring settings as well as optimal sensor positions is presented. The proposed routine uses the outcome of an Experimental Modal Analysis (EMA). Due to different requirements for triggering and non-triggering sensors in the RDM network a combination of two approaches for sensor placement has to be used in order to find the best distribution of measurement points over the structure. A controllability based technique is used for placing triggering sensors, whereas the Effective Independence (EI) is utilized for the placement of non-triggering sensors. The combination of these two techniques selects the best set of measuring points for a given number of sensors out of all possible sensor positions. Damage detection itself is not considered within the scope of this paper.