Dynamic prediction method and device for electromagnetic wave transmission loss of waveguide tube

By constructing a directed attribute graph and a graph variational inference network, and combining an electromagnetic propagation model and a dual-channel time-series evolution model, the problem of dynamic prediction of transmission loss in waveguide networks in closed platforms was solved, and accurate inference of the degradation state of each node in the waveguide network and prediction of loss evolution were achieved.

CN122452307APending Publication Date: 2026-07-24HEBEI ZHAOYU MASCH MFG CO LTD
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Patent Information

Application Number
CN202610501896.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-16
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing technologies cannot effectively predict the dynamic evolution of transmission loss in metallic waveguide networks under conditions of highly incomplete observation information, especially in closed deployment platforms where segment-by-segment disassembly and testing are not possible, and there is a lack of effective methods for modeling the loss distribution and cascaded transmission effects of multi-segment cascaded waveguide networks.

Method used

A directed property graph of the waveguide network is constructed. Combining the graph variational inference mechanism and the dual-channel multi-scale temporal coupled evolution network, the degradation state of each node is inferred using port RF observations and sparse environmental sensor data. Through the electromagnetic propagation attenuation model and physical consistency constraints, the dynamic evolution of link transmission loss is predicted.

Benefits of technology

Under limited observation conditions, the degradation state distribution of each segment of the waveguide network and the flange connection can be accurately predicted, and the interaction of multiple physical degradation mechanisms at different time scales can be captured, realizing dynamic monitoring of transmission loss and accurate prediction of future evolution trends.

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Abstract

The invention discloses a waveguide tube electromagnetic wave transmission loss dynamic prediction method and device, and the method comprises the steps: constructing a directed attribute graph according to a physical connection structure of a waveguide tube network; the posterior distribution of the degradation state of each node is inferred by combining a graph variation inference network with an electromagnetic propagation attenuation model constraint, and the degradation state is subjected to multi-scale time sequence evolution prediction through a dual-channel neural state space model. And aggregating along the directed attribute graph through the loss mapping network to obtain a link total transmission loss predicted value and extrapolating a future evolution trend. The method can accurately deduce the degradation state of each node and predict the dynamic evolution of the transmission loss under the condition of incomplete observation.
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