Damage Identification of Simply Supported Beam Bridge Based on Time Series Analysis

2012 ◽  
Vol 236-237 ◽  
pp. 617-621
Author(s):  
Han Bing Liu ◽  
Yan Jun Song ◽  
Guo Jin Tan ◽  
Yan Yi Sun
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Dynamic Response ◽  
Time Domain ◽  
Damage Identification ◽  
Simply Supported Beam ◽  
Simply Supported ◽  
Series Analysis ◽  
Wide Range ◽  
Beam Bridge

Presently, the study on damage identification of bridges is very popular and it has a wide range of applications. Also the related theory and technology are constantly developing and mature. The researches based on the dynamic response of bridge in frequency domain is more, but the dynamics theory is complex and difficult for the engineering personnel to grasp. On the opposite, although the damage identification method based on the dynamic response of bridge in time domain is easy to understand, it is difficulty for applications. The Auto Regressive Moving Average model (ARMA) of time series analysis can be used to settle this problem. It is a not very abstruse theory and it is already apply for the system identification of some Structures. In this paper, we use time series analysis for the damage identification of simply supported beam bridge combined with its own dynamic response in time domain.

Time series analysis of Holocene climate data

1990 ◽  
Vol 330 (1615) ◽  
pp. 601-616 ◽  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Time Domain ◽  
Small Sample ◽  
Climate Data ◽  
Holocene Climate ◽  
Series Analysis ◽  
Window Method ◽  
Band Limited ◽  
Periodic Components

Holocene climate records are imperfect proxies for processes containing complicated mixtures of periodic and random signals. I summarize time series analysis methods for such data with emphasis on the multiple-data-window technique. This method differs from conventional approaches to time series analysis in that a set of data tapers is applied to the data in the time domain before Fourier transforming. The tapers, or data windows, are discrete prolate spheroidal sequences characterized as being the most nearly band-limited functions possible among functions defined on a finite time domain. The multiple-window method is a small-sample theory and essentially an inverse method applied to the finite Fourier transform. For climate data it has the major advantage of providing a narrowband F -test for the presence and significance of periodic components and of being able to separate them from the non-deterministic part of the process. Confidence intervals for the estimated quantities are found by jackknifing across windows. Applied to 14 C records, this method confirms the presence of the ‘Suess wiggles’ and give an estimated period of 208.2 years. Analysis of the thickness variations of bristlecone pine growth rings shows a general absence of direct periodic components but a variation in the structure of the time series with a 2360-year period.

scholarly journals Prediction Methods for Routine Maintenance Costs of a Reinforced Concrete Beam Bridge Based on Panel Data

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaoli Shi ◽  
Bingbing Zhao ◽  
Yuling Yao ◽  
Feng Wang
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Concrete Beam ◽  
Reinforced Concrete Beam ◽  
Maintenance Cost ◽  
Analysis Method ◽  
Series Analysis ◽  
The Cost ◽  
Beam Bridge ◽  
Physical Engineering

In order to make informed decisions on routine maintenance of bridges of expressways, the hierarchical regression analysis method was used to quantify factors influencing routine maintenance cost. Two calculation models for routine maintenance cost based on linear regression and time-series analysis were proposed. The results indicate that the logarithm of the historical routine maintenance cost is the dependent variable and the bridge age is the independent variable. The linear regression analysis was used to obtain a cost prediction model for routine maintenance of a beam bridge, which was combined with the quantity and price, and verified by a physical engineering example. In order to cope with the cost changes and future demands brought about by the emergence of new maintenance technologies, the time-series analysis method was used to obtain a model to predict the engineering quantities for the routine maintenance of a bridge based on standardized minor repair engineering quantities. Taking into account the actual cost of the minor repair project as well as the time-series analysis’ sample size demands, the annual engineering quantity was randomly decomposed into four quarterly data quantities, and the time-series analysis result was verified by physical engineering. These results can improve the calculation accuracy of the routine maintenance costs of reinforced concrete beam bridges. Furthermore, it can have a certain application value for improving the cost measurement module of bridge maintenance management systems.

Damage identification using time series analysis and sparse regularization

2020 ◽  
Vol 27 (9) ◽  
Author(s):  
Hongping Zhu ◽  
Hong Yu ◽  
Fei Gao ◽  
Shun Weng ◽  
Yuan Sun ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Damage Identification ◽  
Sparse Regularization ◽  
Series Analysis

scholarly journals Interactive Education for Time-Domain Time Series Analysis using ITTSAE

2015 ◽  
Vol 48 (28) ◽  
pp. 751-756
Author(s):  
J.M. DÍaz ◽  
S. Dormido ◽  
D.E. Rivera
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Time Domain ◽  
Series Analysis ◽  
Interactive Education

A New Method of Time Series Analysis and its Application to Identifying Modal Parameters

1991 ◽  
Author(s):  
Yusheng He ◽  
Zhaoxiang Deng
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Time Domain ◽  
New Method ◽  
Modal Parameters ◽  
Frequency Domain Method ◽  
Identification Algorithm ◽  
Series Analysis ◽  
The Time Domain ◽  
Modeling Strategy

Abstract In the paper, the attention concentrates on the time domain modal analysis. A new method of time series analysis, which is formed mainly by an ideal modeling strategy and a new COR-IV method, is developed. In addition, an interesting parameter called as modal energy ratio, which is available for design reference, is defined and its identification algorithm is given. The new method presented in this paper and Frequency Domain Method (FDM) are performed on a frame of SG120 vehicle. It is shown by comparison between these two methods that the new method of time series analysis is practical.

Damage Identification Method of Simply Supported Beam Bridge with Multiple Girders

2013 ◽  
Vol 437 ◽  
pp. 377-381
Author(s):  
Ping Yi Sun ◽  
Yan Hua Wang ◽  
Yan Feng Niu ◽  
Han Bing Liu ◽  
Guo Jin Tan
Keyword(s):  
Numerical Simulation ◽  
Damage Identification ◽  
Identification Algorithm ◽  
Damage State ◽  
Simply Supported Beam ◽  
Simply Supported ◽  
Svm Algorithm ◽  
Damage Extent ◽  
Beam Bridge ◽  
T Beam

Considering the complexity of the simply supported beam with multiple girders, a two-step damage identification algorithm for this kind of bridge is presented. This algorithm first locates the damage by means of curvature of flexibility change, and then utilizes the PSO-SVM algorithm to identify the damage extent. At last, a numerical simulation calculation is conducted to identify the damage state of a simply supported T-beam bridge with five girders. The numerical simulation results show that the algorithm proposed is valid, reliable and with high recognition precision.

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