Gravity dam time-space correlation monitoring data acquisition and visual presentation method

Abstract

The invention relates to a gravity dam time-space association monitoring data acquisition and visual presentation method, which is characterized by comprising a wireless sensing data acquisition algorithm based on time-space association and a data analysis algorithm based on time-space association, the wireless sensing data acquisition algorithm based on time-space correlation is a time domain sampling frequency adjustment algorithm adopted on the basis of considering spatial correlation; the data analysis algorithm based on time-space association comprises a time-space autoregression moving average model and a time-space autoregression model. Multiple parts, multiple measuring points and multiple types of monitoring data of the gravity dam are covered, visual comprehensive analysis and rapid evaluation are carried out on the working state of the key parts of the gravity dam in real time, and dam safety evaluation is changed into multi-measuring-point and multi-project multi-dimensional comprehensive evaluation from traditional single-measuring-point independent analysis evaluation.

Description

technical field [0001] The invention belongs to the technical field of water conservancy and hydropower engineering, in particular to the technical field of a time-space correlated monitoring data collection and visualization presentation method for a gravity dam. Background technique [0002] In the traditional monitoring data analysis process of gravity dams, the monitoring sequence of a single measuring point is usually modeled, which means that all measuring points need to be modeled, resulting in a large number of model redundancy. There is not only time correlation between the dam monitoring data, but also the displacement of each monitoring point of the dam as a whole structure is interrelated, that is, there is spatial correlation. The visualization technology of relationship, data time series characteristics and dam characteristic parameters can comprehensively analyze and quickly evaluate the working performance of each part of the dam in the river basin in real ti...

AI Technical Summary

Problems solved by technology

[0002] In the traditional monitoring data analysis process of gravity dams, the monitoring sequence of a single measuring point is usually modeled, which means that all measuring points need to be modeled, resulting in a large number of model redundancy

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