Method and system for automatically calibrating installation error of MEMS

CN120801758APending Publication Date: 2025-10-17WUHAN ZHIYUAN TECH CO LTD
View PDF 0 Cites 0 Cited by

Patent Information

Application Number
CN202510766139.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-10
Publication Date
2025-10-17

AI Technical Summary

Technical Problem

When installing MEMS devices in wind turbine towers, installation errors cannot be effectively calibrated, and existing technologies cannot meet actual application requirements.

Method used

By installing MEMS devices on the wind turbine tower, collecting three-axis accelerometer data, and using clustering algorithm and rotation matrix calculation, the installation error is automatically calibrated. This includes static component extraction, clustering calculation and rotation matrix construction, thus achieving automatic calibration of installation errors.

Benefits of technology

No high-precision surveying and mapping methods are required, which simplifies the installation steps, improves installation efficiency, and reduces the requirements for on-site technicians. The calibration accuracy can reach 0.05°.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN120801758A_ABST
    Figure CN120801758A_ABST
Patent Text Reader

Abstract

The invention discloses an MEMS automatic installation error calibration method and system, and the method comprises the steps: collecting the data ax (i), ay (i) and az (i) of a triaxial accelerometer in an MEMS, caching the data for a period of time, and obtaining three acceleration arrays ax (N), ay (N) and az (N); judging whether the fan is in a non-power-generation state or not; if the acceleration array is in the non-power-generation state, static component extraction is carried out on the acceleration array, and axstate, aystate and azstate are obtained; the extracted static components are written into a database, and when the number of data in the database is larger than a threshold value M, M pieces of latest static component data are taken out; using a clustering algorithm to calculate the sum of the mean value to obtain a vector [ax, ay, azz]; and calculating a space rotation matrix from the vector [ax, ay, azz] to the vector [0, 0, 1], and taking the space rotation matrix as an installation error calibration matrix G.
Need to check novelty before this filing date? Find Prior Art