Magnetic Encoder Self-Calibration for Low-Cost Angle Detection
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Solution Overview
Problem
The calibration cost of magnetic encoders is high due to the need for additional high-precision optical encoders, increasing hardware and time costs.
Innovation Solution
A self-calibration method for magnetic encoders involves setting reference points, performing low-pass filtering and averaging to create a trimming reference table, eliminating the need for expensive optical encoders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high-precision optical encoder is added to calibrate the magnetic encoder, then the detection precision is improved, but the hardware cost and device complexity increase
Solution Approach 1:
The magnetic encoder performs self-calibration by detecting its own output signals and automatically generating correction values through low-pass filtering and averaging processes, eliminating the need for external high-precision optical encoders or manual calibration equipment
Solution Approach 2:
The patent creates a virtual reference system by processing the magnetic encoder's own output signals through filtering and averaging to generate trimming values that simulate the effect of a high-precision reference encoder, thereby achieving calibration without physical copying equipment
2Measurement precision
If a high-precision optical encoder is added to calibrate the magnetic encoder, then the detection precision is improved, but the hardware cost increases
Solution Approach 1:
The magnetic encoder performs self-calibration by detecting its own output signals and automatically generating correction values through low-pass filtering and averaging processes, eliminating the need for external high-precision optical encoders or manual calibration equipment
Solution Approach 2:
The patent uses software-based signal processing algorithms (low-pass filtering and averaging) instead of expensive hardware equipment, replacing costly physical calibration tools with computationally inexpensive digital processing methods
3Measurement precision
If traditional calibration methods are used with optical encoders, then the detection precision is improved, but the time cost increases
Solution Approach 1:
The magnetic encoder performs self-calibration by detecting its own output signals and automatically generating correction values through low-pass filtering and averaging processes, eliminating the need for external high-precision optical encoders or manual calibration equipment
Solution Approach 2:
The calibration process operates continuously during motor operation by constantly processing the magnetic encoder's output signals through filtering and averaging, allowing calibration to occur during normal operation rather than requiring separate calibration time
Data Source
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AI summary
This application belongs to the field of rotation angles detection, and provides a self-calibration method for a magnetic encoder, a motor, and a method for calibrating detection values of angles. The self-calibration method for the magnetic encoder includes: performing a low-pass filtering process on detection values θdet(ij) to obtain filtered values θfilt(ij); setting m reference points θref(n) within 360°, and selecting detection values θdet(ij-n) respectively closest to each reference point θref(n) in each period; selecting filtered values θfilt(ij-n) corresponding to θdet(ij-n); calculating trimming values θcal(i-n) = θfilt(ij-n) - θdet(ij-n); performing an averaging process on θcal(i-n) over p periods for each reference point θref(n) to obtain target trimming values θcal(n); and storing each of the reference points θref(n) and the target trimming values θcal(n) respectively corresponding to the each of the reference point in a one-to-one correspondence as a trimming reference table. The self-calibration method for a magnetic encoder provided in this application can reduce the calibration cost for a magnetic encoder.