A network measure probability model-based offshore wind power structure dynamic performance tracking method, medium and equipment

The method for evaluating the dynamic performance of offshore wind power structures based on a network metric probability model solves the problems of isolated evaluation indicators and strong subjectivity in traditional methods. It enables dynamic performance tracking and trend evaluation of offshore wind power structures, improving the accuracy and real-time performance of monitoring.

CN115983670BActive Publication Date: 2026-06-19POWERCHINA HUADONG ENG CORP LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
POWERCHINA HUADONG ENG CORP LTD
Filing Date
2022-12-02
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

Traditional methods for monitoring the health status of offshore wind power structures cannot effectively track the dynamic performance of structures. They suffer from isolated evaluation indicators, strong subjectivity, and an inability to adapt to the time-varying characteristics of structures.

Method used

A dynamic performance evaluation method for offshore wind power structures is established by adopting a network-based probabilistic measurement model, classifying environmental conditions and using information entropy weights. By combining the mutual influence of responses among various sensors, the weights and correlations of each indicator are calculated to achieve dynamic performance tracking.

Benefits of technology

Accurate assessment of the overall dynamic performance and development trend of offshore wind power structures reduces misjudgments of abnormal data and enables real-time monitoring of changes in the dynamic performance of structures.

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Abstract

This invention provides a method, medium, and device for tracking the dynamic performance of offshore wind power structures based on a network measurement probability model. The method includes the following steps: S1, single-index evaluation based on marine environmental condition classification; S2, network measurement probability model based on the information entropy of the dynamic response of the wind power structure; S3, tracking the dynamic performance of the offshore wind power structure. This invention establishes the relationship between the probability distribution of the evaluated structure and various health level intervals based on the dynamically changing dynamic response signals after environmental condition clustering. This can distinguish the changing trends of the structure's dynamic performance under a single index evaluation, helping to identify the location and direction of abnormal data. It is the first to propose a network measurement probability model based on information entropy, introducing the mutual influence between individual indices and dynamically obtaining the participation weights of each index. It can obtain the dynamic performance state of the structure to be evaluated without prior knowledge of all damage states of the structure, and assess the development trend of the overall structural dynamic performance.
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