Handwritten Data Recognition for Spinning Process Automation
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Solution Overview
Problem
The spinning process in the industrial scenario is long and complicated, with key links requiring manual recording and data upload, leading to inefficiencies and resource costs.
Innovation Solution
A model training method and data processing method that involve obtaining historical process flow cards, extracting and classifying handwritten areas, constructing digit and text recognition models, and using these models to automatically extract and upload data to a process flow database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual recording and data upload operations are used for spinning process key links, then data can be captured, but human resource costs increase and efficiency decreases
Solution Approach 1:
The system enables automatic self-service data capture by having the spinning machine automatically record process parameters and generate process flow card information, eliminating the need for manual intervention in data collection and upload operations
Solution Approach 2:
The patent replaces the manual mechanical operation of recording and uploading data with an automated digital system that uses the spinning machine's control unit to capture, process, and transmit data electronically to the database
2Reliability
If manual data recording is performed for spinning process key links, then process data can be captured, but human resource costs increase
Solution Approach 1:
The spinning machine's control system automatically performs data capture and recording functions, making the system self-sufficient in terms of data collection without requiring human operators to manually record information
Solution Approach 2:
The patent substitutes manual human operations with an automated control system that reads sensor data, processes information, and stores records electronically, thereby eliminating human resource consumption while maintaining data reliability
3Loss of information
If manual operation is used for recording spinning process data, then data can be entered into system, but efficiency is reduced
Solution Approach 1:
The system implements continuous automated data capture and processing operations where the spinning machine continuously records process parameters and immediately transmits them to the database without interruption or manual intervention, maintaining continuous useful action throughout the data flow
Solution Approach 2:
The patent replaces slow manual data entry operations with automated electronic data transmission that occurs in real-time or near-real-time, dramatically increasing data processing speed while ensuring complete data capture through the machine's integrated sensing and recording systems
Data Source
AI summary
Provided is a model training method, a data processing method and related apparatuses, relating to the technical fields of large model, image processing, and computer vision. The method includes: obtaining a historical process flow card set for spinning process; extracting a handwritten area from each historical process flow card; classifying the handwritten area to obtain a handwritten digit image block and a handwritten text image block; constructing a digit recognition model of different handwritten digit categories based on the handwritten digit image block, to extract a target digit from a newly-added process flow card; and constructing a text recognition model of different handwritten text categories based on the handwritten text image block, to extract a target text from the newly-added process flow card; wherein the target digit and the target text are used to construct a process flow database for the spinning process.