一种直升机振动健康状态监测方法
By conducting big data analysis and statistical learning on helicopter vibration data, the vibration frequency threshold was optimized, solving the problem of inaccurate judgment of helicopter vibration health status and achieving higher monitoring accuracy and safety.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHAANXI QIANSHAN AVIONICS
- Filing Date
- 2022-07-11
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, the vibration frequency threshold of helicopters is given by expert experience, which leads to inaccurate judgment of vibration health status, and may result in missed or false judgments, thus reducing the performance of helicopter health status monitoring.
Vibration data is used as a large data sample. Statistical learning methods are combined to optimize the threshold of vibration frequency points. By dividing the dataset into inherent and non-inherent vibration frequencies, abnormal vibration frequencies are extracted. Statistical methods are used to obtain vibration thresholds and optimize the helicopter health status monitoring model.
It improves the accuracy of helicopter vibration health status monitoring, reduces maintenance costs, and enhances flight safety.
Smart Images
Figure CN115358286B_ABST