Design of a Random Decrement Method Based Structural Health Monitoring System

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.

An Identification Method for Damping Ratio of In Situ Building

Damping evaluation is of great importance in predicting the dynamic response of systems. To get the accurate damping ratios of a system, many identification methods have been proposed and developed. But only few of them achieved accurate results for in-situ buildings due to the fact that the responses are significantly influenced by noise. This paper proposes a new method to accurately identify the damping ratios of in-situ buildings. The method is based on ambient excitation technique which requires no artificial excitation applied to SSI system and to measure output-only. The damping ratio identification is then performed by combining the improved random decrement method and Ibrahim time domain method. To demonstrate the validity of the proposed approach, a case study is performed and the results are compared with the conventional peak-peaking method results. The results show the proposed method can effectively identify the modal parameter of either frequencies or damping ratios of in-situ buildings subjected to ambient excitation.

Nonlinear Roll Damping of Ship Motions in Waves

Nonlinear roll damping has a profound influence on ship motions and stability in ocean waves. In this study, an experimental investigation is conducted on the nonlinear roll damping of a ship in regular and irregular waves. The random decrement method, previously used in linear roll damping prediction, is extended to nonlinear roll damping estimation in the data process. The accuracy of the nonlinear roll damping obtained by using the random decrement method is found to be dependent on the values of the threshold and segment number.

Study on the Method of Modified Random Decrement for Transfer Function

This paper presents a modified random decrement method to obtain the steady-state response of vibration system. The expressions are deduced. Two numerical simulations and verification are given. The efficiencies of the modified method and the conventional process are compared. It is shown that the method is more efficient than the conventional process to diminish the influence of the initial excitation on the transfer function calculation of the vibration system.

Generalized Random Decrement Method for Analysis of Vibration Data

The Random Decrement method used in system identification for analysis of random vibration data is considered from a rigorous mathematical perspective. It is shown that the Random Decrement signature deviates from the system free vibration curve of an associated linear system, unless the corresponding input excitation is white. The error induced by approximating the system excitation by a white noise process is examined. Further, a generalized Random Decrement signature is introduced; it is used to estimate efficiently the auto-correlation function of an ergodic Gaussian random process. Several examples are discussed to elucidate the theoretical developments.