Measurement method, measurement device, measurement system, and measurement program

The proposed measurement method addresses the accuracy issues in displacement time series by filtering velocity data to reduce noise and estimating correction data, resulting in improved measurement accuracy and reduced complexity.

JP7683240B2Active Publication Date: 2025-05-27SEIKO EPSON CORP
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Patent Information

Application Number
JP2021029750
Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
Filing Date
2021-02-26
Publication Date
2025-05-27
Estimated Expiration
2041-02-26

AI Technical Summary

Technical Problem

The accuracy of displacement time series in existing displacement acquisition devices is affected by the approximation between detected girder displacement and stored static components, and there is no means to recognize changes in static components due to environmental changes, leading to potential errors and increased complexity in data management.

Method used

A measurement method that involves high-pass filtering velocity data to reduce drift noise, integrating the filtered data to generate displacement data, estimating correction data based on the difference between the displacement data and data obtained by integrating velocity data, and generating measurement data by adding displacement data and correction data.

Benefits of technology

This method reduces errors in displacement measurement by effectively removing drift noise and vibration components, improving the accuracy of displacement data without the need for pre-stored static component data, thus simplifying the configuration and reducing costs.

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Patent Text Reader

Abstract

To provide a measurement method that can generate measurement data with reduced drift noise without the need to prepare in advance information for reducing the drift noise.SOLUTION: A measurement method includes: a high-pass filter processing step of performing high-pass filter processing on velocity data including drift noise based on observation data to generate drift noise reduced data with reduced drift noise; a displacement data generation step of integrating the drift noise reduced data to generate displacement data; a correction data estimation step of, on the basis of the displacement data, estimating correction data corresponding to a difference between the displacement data and data obtained by excluding the drift noise from the data obtained by integrating the velocity data; and a measurement data generation step of adding up the displacement data and the correction data to generate measurement data.SELECTED DRAWING: Figure 27
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Citation Information

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