ARMA model-based bridge damage pre-warning method

Abstract

The invention discloses an ARMA model-based bridge damage pre-warning method. The method comprises the following steps of: 1, collecting acceleration data under a bridge heath condition; 2, carrying out smoothing, trend term removal and standardization on the acceleration data to obtain health data; 3, carrying out ARMA modeling on the health data and extracting an AR coefficient; 4, calculating adamage recognition pre-warning index DSF of the health data to serve as a health sample; 5, collecting bridge acceleration data monitored in a certain time, and solving a damage pre-warning index DSFaccording to the steps 2-4 to serve as an inspection sample; 6, carrying out hypothesis inspection on the health sample and the inspection sample; and 7, when the hypothesis inspection result is 1, considering that the bridge structure is damaged and pre-warning the bridge damage, and otherwise, considering that the bridge is safe and extending the current inspection sample into the original health sample. The method has the beneficial effects of constructing damage pre-warning indexes through an ARMA model according to existing monitoring data, establishing a complete damage pre-warning process and improving the utilization of measured data.

Description

technical field [0001] The invention relates to the technical field of bridges, in particular to a bridge damage early warning method based on an ARMA model. Background technique [0002] As an important structure of railway engineering, the bridge structure will be damaged to varying degrees with the increase of service time, which seriously threatens the safety of operation. With the emergence of the bridge health monitoring system, the research on damage identification of bridge structures based on long-term monitoring has gradually begun, and scholars at home and abroad have done a lot of research on this aspect, and achieved certain results, and put forward some damage identification theories and methods . [0003] In terms of the characteristics of long-term monitoring, it is more practical and reliable to use the time domain response of the structure under load to identify the damage of the structure. Among them, the damage identification method based on time series...

AI Technical Summary

Problems solved by technology

Existing bridge health monitoring systems rarely involve damage identification and early warning of bridges. The commonly used method is threshold warning. When the bridge monitoring value exceeds a certain limit, it is considered that the bridge structure has been damaged, and the long-term monitoring data cannot be fully excavated. value, resulting in the waste of a large amount of monitoring data

In addition, different types of bridge structures may have different sensitivity to damage indicators, which requires targeted selection of early warning indicators, taking into account the characteristics of the health monitoring system, and the existing bridge monitoring system fails to reasonably select early warning indicators. Indicators to establish a reasonable damage early warning method

Images