一种基于大数据分析的文物展柜防震预测方法及系统
By generating a weighted multidimensional dynamic time series matrix and using a deep learning model to optimize the vibration risk factor of the artifact display case, the problem of insufficient adaptability of traditional methods in diverse vibration environments is solved, and a more reliable earthquake prediction effect is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JIANGSU ZHONGGU LIBAO CONSTR TECH CO LTD
- Filing Date
- 2025-01-09
- Publication Date
- 2026-07-17
AI Technical Summary
Existing anti-vibration designs for artifact display cases lack adaptability and accuracy when facing diverse and dynamic vibration environments. Furthermore, existing models fail to comprehensively consider the physical characteristics of the artifact display cases and the dynamic changes in vibration signals, resulting in a lack of stability and reliability in prediction results in the medium to long term.
By acquiring the physical parameters and historical vibration data of the artifact display cases, a weighted multidimensional dynamic time series matrix is generated. A deep learning model is used to optimize the vibration risk factors and make short-term and medium-to-long-term predictions. Reliability assessment is combined to improve the accuracy of the predictions.
It improves the calculation accuracy and prediction robustness of vibration risk factors, ensures risk coverage in different time windows, reduces the model's sensitivity to abnormal data, reduces the risk of erroneous decisions, and comprehensively protects the safety of cultural relics.
Smart Images
Figure CN120124422B_ABST