Crimp Connection Image Evaluation Using Neural Segmentation
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Solution Overview
Problem
Current methods for evaluating the quality of crimp connections in cable manufacturing are labor-intensive, non-reproducible, and lead to inaccurate results due to manual handling, making it difficult to trace and search archived evaluations and increasing costs.
Innovation Solution
An image processing device using a deep neural network for semantic segmentation of crimp connection cross-sectional images, converting raster images into vector contours to determine qualitative and quantitative quality parameters, thereby enhancing reliability and automation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual evaluation of crimp connection quality is performed, then flexibility and adaptability are maintained, but labor intensity increases and measurement precision decreases
Solution Approach 1:
The patent replaces manual mechanical evaluation with an automated image processing system that captures cross-sectional images of crimp connections and uses algorithmic analysis to determine quality parameters. This substitution eliminates human subjectivity and labor while maintaining objective assessment criteria, directly improving measurement precision without requiring complex manual intervention procedures
Solution Approach 2:
The evaluation system performs self-assessment by automatically analyzing captured images through programmed algorithms that identify crimp defects and quality parameters without human intervention. The system serves itself by integrating image capture, processing, and evaluation functions into a unified automated workflow, reducing labor intensity while maintaining consistent assessment standards
2Productivity
If automated image analysis algorithms are used, then productivity increases, but measurement precision decreases due to inaccurate results requiring manual correction
Solution Approach 1:
The system incorporates feedback mechanisms where evaluation results are continuously refined based on comparison with reference data and quality standards. The algorithm learns from evaluation outcomes and adjusts its analysis parameters to improve accuracy over time, allowing automated processing to maintain high precision without requiring manual correction of each result
Solution Approach 2:
The system performs preliminary actions by capturing and processing reference images of known good and defective crimp connections before evaluating production samples. This pre-establishment of quality benchmarks enables the algorithm to accurately classify new samples without manual intervention, maintaining both high productivity and measurement precision through pre-programmed evaluation criteria
3Productivity
If manual documentation of evaluation results is performed, then flexibility in handling diverse cases is maintained, but loss of information increases and productivity decreases
Solution Approach 1:
The patent replaces manual documentation with automated digital recording of evaluation results. The system automatically captures image data, analysis results, and quality parameters in structured digital formats that are immediately stored and searchable, eliminating the information loss and inefficiency associated with manual writing and archiving while maintaining complete traceability of each evaluation
Solution Approach 2:
The system creates digital copies of evaluation results that can be stored, retrieved, and analyzed without degrading the original information. These digital replicas enable efficient searching, archiving, and re-evaluation of historical data, dramatically improving productivity while preserving complete information traceability through searchable databases and structured data storage
Data Source
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AI summary
The invention relates to an image processing device (100) for supporting a qualitative and/or quantitative assessment of the quality of a crimp connection, an image evaluation device (200) and a production release system (300) for a crimping device, with an image evaluation device (200) according to one of claims 7 to 9, with a data interface to a database (304) in which production order-dependent target values for crimp connections (C) are stored, with a release unit (305) which is designed to provide an approval or a refusal of approval for production of the error-classified crimp connection (C) after a comparison between at least one qualitative and/or quantitative quality parameter (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11) with an associated target value.This solves the problem of determining the quality parameters of crimp connections in a more robust and reliable manner and of making the production of corresponding crimp connections more reliable and less complex.