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Bridge structure safety monitoring data prediction method

A bridge structure and safety monitoring technology, applied in forecasting, data processing applications, electrical digital data processing, etc., can solve the problems of complex, random and sudden interference sources, and accurate signal prediction is not easy.

Active Publication Date: 2015-01-07
重庆物康科技有限公司
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Problems solved by technology

However, despite the continuous progress of modern technical means, the signals obtained by long-term monitoring often contain the joint effects of various factors, random and sudden interference sources are more and more complex, making accurate signal prediction is still not easy work

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Embodiment Construction

[0041] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0042] figure 1It is a schematic flow chart of the method of the present invention, as shown in the figure, the prediction method of the bridge structure safety monitoring data of the present invention comprises the following steps:

[0043] Step 1: Select bridge monitoring data as the object to be analyzed, and predict its future development trend; the bridge monitoring data includes: crack data, strain data, inclination data, deflection data, displacement data, acceleration data and cable force monitoring data, etc.;

[0044] Step 2: Select the sample data of the bridge monitoring data, use the sample data to train the auto regression moving average model ARMA (Auto Regression Moving Average), establish the ARMA model, and use the model to predict the value of the monitoring variable at the next moment;

[0045] Step 3: Use the sample da...

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Abstract

The invention relates to a bridge structure safety monitoring data prediction method, and belongs to the technical field of bridge health monitoring. The method includes the following steps that (1) bridge monitoring data are selected to serve as an object to be analyzed, and the future development trend of the object to be analyzed is predicted; (2) sample data of the bridge monitoring data are selected, an auto regressive moving average (ARMA) is trained through the sample data, and the monitoring variable value of the next moment is predicted through the ARMA; (3) a least squares support vector machine (LS-SVM) is trained through the sample data, and the monitoring variable value of the next moment is predicted through the LS-SVM; (4) the prediction result of the ARMA and the prediction result of the LS-SVM serve as input samples, the fuzzy membership degree is given to the input samples, a least squares fuzzy support vector machine (LS-FSVM) is trained, the monitoring variable value of the next moment is predicted through the LS-FSVM, and the value is the final prediction result of the method. By means of the bridge structure safety monitoring data prediction method, on-line, real-time prediction can be conducted on bridge structure safety monitoring information, and the error is smaller and the accuracy is higher compared with a traditional method.

Description

technical field [0001] The invention belongs to the technical field of bridge health monitoring, and relates to a method for predicting bridge structure safety monitoring data, in particular to a method for predicting bridge structure safety monitoring data based on quadratic fuzzy least squares support vector machine based on an autoregressive moving average model. Background technique [0002] The construction and maintenance of bridges are an important part of a country's infrastructure and play an important role in national construction and people's lives. In recent years, with the rapid development of bridge construction, the forms and functions of bridge structures have become more and more complex, and the scale of projects has also become larger and larger. However, bridge safety accidents have occurred from time to time, and the safety hazards of bridge structures are widespread. In the United States, about 575,000 bridges are inspected at least every two years. Acc...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/08G06F17/30
CPCG06F30/367G06Q10/04G06Q50/08
Inventor 唐浩孟利波廖敬波宋刚陈果谭川
Owner 重庆物康科技有限公司
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