Intelligent early warning method for dam safety monitoring data

Abstract

The invention discloses an intelligent early warning method for dam safety monitoring data. The method comprises the steps of early warning model establishment, threshold value setting and mutual feedback type early warning. Gross error identification and gross error processing are carried out, model sample data quality is improved, according to the monitoring items, independent variable relevance, historical monitoring data quantity and historical monitoring data distribution, different early warning models and indexes are established, including a stepwise regression model, a correlation vector machine model and a gray system model; the established models can reflect the relationship between the independent variable and the dependent variable more truly and are wide in application range,according to a measuring instrument, measuring point attributes, a threshold value, an early warning model and indexes, real-time early warning is carried out on monitoring data, monitoring instrumentabnormity early warning is sent to monitoring personnel, or dam safety early warning is sent to dam safety management personnel, experts with professional knowledge and rich experience are not needed, the workload is small, the early warning speed is high, and the early warning result is more accurate and reliable.

Description

technical field [0001] The invention relates to the technical field of dam safety monitoring, in particular to an intelligent early warning method for dam safety monitoring data. Background technique [0002] Reservoir dams are an important infrastructure of the national economy, an important engineering measure to regulate the temporal and spatial distribution of water resources and optimize the allocation of water resources, and an important part of the national flood control and drought relief system and the river flood control engineering system. Reservoir dam safety is not only related to Flood control safety, water supply safety, and food safety are also related to economic, ecological, and national security. In the process of dam safety monitoring, some abnormal data will be generated. These abnormal data may be erroneous data caused by instrument failure, environmental impact or human error, or may indeed be a true reflection of the dangerous situation of the dam. ...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides an intelligent early warning method for dam safety monitoring data, which can effectively solve the current problem proposed in the above background technology. For these abnormal data, manual identification is mainly adopted, or threshold control or statistical model early warning is performed, and then manual processing is performed. , both require a lot of manpower, and experts with professional knowledge and rich experience can identify the cause of abnormal data from it

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