A mover identification method and device based on magnetic suspension flexible assembly line

By constructing a topology model and selecting an appropriate recognition algorithm for moving part identification, the problems of accuracy and real-time performance in moving part identification in magnetic levitation flexible conveyor systems were solved, achieving high-precision dynamic adaptive control and improving production smoothness and product quality.

CN120397612BActive Publication Date: 2026-04-24SHEN ZHEN XING DONG YUAN ZHI NENG ZHUANG BEI YOU XIAN GONG SI
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Patent Information

Application Number
CN202510460129.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-04-14
Publication Date
2026-04-24
Estimated Expiration
2045-04-14

AI Technical Summary

Technical Problem

Existing methods for identifying moving parts struggle to balance accuracy and real-time performance in magnetically levitated flexible transport systems under complex line shapes, high-speed motion, and diverse application scenarios, leading to challenges in practical applications.

Method used

By constructing a topology model, periodically scanning the mover encoder data, selecting a suitable recognition algorithm for noise filtering and smoothing, performing correlation analysis and multi-dimensional verification, and generating a control instruction set to achieve high-precision real-time recognition and dynamic adaptive control.

Benefits of technology

It improved the accuracy of mover positioning, reduced the assembly error rate, improved data quality and processing efficiency, and ensured the safety, stability and production efficiency of the production line.

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Abstract

The application relates to a mover identification method and device based on a magnetic suspension flexible flow line, wherein the method comprises the following steps: activating a pre-generated topological model; periodically scanning the data of a mover encoder of a station driver to obtain real-time position and speed data of the mover and mapping the data to corresponding coordinates; performing noise filtering and smoothing processing on the data; selecting a corresponding identification algorithm according to the size of a line body, the bus communication frequency, the preset task sequence of the mover and the processed speed data; performing correlation analysis on the processed data to generate mover trajectory data; checking the trajectory data, and giving a warning if the trajectory data is abnormal; updating the data that passes the check to a database, generating a control instruction set based on the topological model coordinates, the motion state of the mover and external instruction parameters, and outputting the control instruction set to a path planning system to realize multi-mover high-precision real-time identification and dynamic adaptive control and provide support for asynchronous scheduling.
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