Self-adapting consistent data fusion method

Abstract

The invention relates to a self-adapting consistent data fusion method which comprises the following steps: firstly, collecting structure response with multiple sensors; then, estimating the measured variance of each sensor according to self-measured variance of each sensor and the data collected by each sensor; according to a measurement model, defining a self-adapting confidence distance between any two sensors, and calculating comprehensive support of each sensor from other sensors; and finally, performing final fusion by using a method of weighted mean by taking the comprehensive support of each sensor as a weight coefficient. With the method, a multiple-degree-of-freedom response signal, a non-free vibration response signal, a nonlinear response signal and non-stable response signal can be well processed; and the method can be used for processing signals in the fields of civil engineering, aerospace, automatic control, mechanical engineering, bridge engineering, hydropower engineering and the like, and has the characteristic of improving the antijamming capability of data.

Description

technical field [0001] The invention relates to a technology for real-time estimation of variance measured by sensors, in particular to an adaptive consistency data fusion method that changes in real time as environmental factors change. Background technique [0002] Structural damage diagnosis and safety assessment are of great significance to ensure the normal use of major civil engineering structures such as bridges, dams, power plants, military facilities, and high-rise buildings. Monitoring and diagnosis of these engineering structures usually requires a large amount of observation data. The information of a single sensor obviously cannot meet the requirements, and due to the influence of noise, external environmental factors and the performance of the sensor itself, large measurement errors may occur, and even lead to wrong conclusions. Therefore, the use of multiple or multiple sensors for measurement has become become an inevitable requirement. How to comprehensivel...

AI Technical Summary

Problems solved by technology

Consistent multi-sensor data fusion method is one of the more representative ones, but with the increase of research and application, the problems of this algorithm are becoming more and more obvious. Although some scholars have made improvements, it still has two problems: (1 ) The algorithm regards the sensor’s own measurement variance as the actual measurement variance, without considering that the actual measurement variance is caused by the sensor’s own credibility and environmental interference; (2) The sensor’s own measurement variance in the algorithm is in the fusion It is specified before and remains unchanged during the measurement process, so the algorithm cannot make adaptive adjustments to the uncertainty factors in the measurement

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