Fiber Preform Winding Machine With Hidden-Face Anomaly Detection
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Solution Overview
Problem
Existing methods for manufacturing composite material fan retention casings for aeroengine gas turbines fail to detect anomalies such as pollution and weaving faults on the hidden face of the preform during the winding operation, which are not visible and can only be identified after the impregnation stage, leading to potential defects in the final product.
Innovation Solution
A method using cameras and an image analysis module to scan the hidden face of the fiber preform during the winding process, comparing the images with reference patterns to detect anomalies in real-time, allowing for immediate correction or rejection of the preform before impregnation, and providing a 3D representation of the anomalies for operator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the preform is wound in superposed layers on an impregnation mandrel, then the composite material casing is formed, but the hidden face of the preform cannot be visually inspected for anomalies
Solution Approach 1:
The patent replaces manual visual inspection with an automated optical inspection system. Cameras capture images of the hidden face of the preform during the winding operation, and an image analysis module automatically detects anomalies such as pollution and weaving faults. This substitution eliminates the limitation of human visual inspection while maintaining the winding process.
Solution Approach 2:
The patent introduces an intermediary inspection system between the winding process and the final product. The cameras and image analysis module act as intermediaries that capture and analyze the hidden face of the preform during winding, providing data about anomalies without interfering with the winding operation itself.
2Productivity
If anomalies are not detected during winding, then the winding operation can proceed, but the anomalies are hidden by superposition of layers and cannot be validated
Solution Approach 1:
The patent implements a feedback mechanism where the image analysis module continuously monitors the hidden face of the preform during winding and provides real-time information about anomalies. This feedback allows for quality validation without stopping the winding process, as the system can identify and record anomalies for subsequent review and decision-making.
Solution Approach 2:
The patent performs preliminary inspection of the hidden face during the winding operation itself, rather than waiting until after winding is complete. By capturing images and analyzing anomalies during the winding process, the system enables early detection and validation of quality issues before they are hidden by subsequent layers.
3Measurement precision
If manual inspection is used for the hidden face, then operators can detect anomalies, but the inspection process is time-consuming and cannot be performed during winding
Solution Approach 1:
The patent replaces time-consuming manual inspection with automated optical inspection and image analysis. The system captures images of the hidden face during winding and uses computer algorithms to detect anomalies, eliminating the need for separate manual inspection steps and significantly reducing the time required for quality assessment.
Solution Approach 2:
The patent enables continuous inspection during the winding operation rather than requiring separate inspection steps. The camera system and image analysis module operate continuously throughout the winding process, maintaining productivity while providing constant quality monitoring of the hidden face.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time monitoring and correction of weaving or winding anomalies, ensuring higher quality control and reducing fabrication cycle time by allowing for automated operation and statistical analysis of anomaly data, thus improving the reliability of composite material casings.
Implementation Method 1
a plurality of cameras looking at the underside of the fiber texture scan the hidden face of the fiber preform and acquire images of the hidden face
Implementation Method 2
an image analysis module processes the images of the hidden face of the fiber preform in a plurality of adjacent scan windows in order to extract weaving patterns therefrom and compare them with reference weaving patterns previously stored in the module
Data Source
AI summary
A machine for weaving or winding a fiber preform on a mandrel having an axis of rotation that is substantially horizontal and that serves to receive the preform, the machine having a plurality of cameras pointing towards the underside of the fiber preform in order to scan the hidden face of the fiber preform and acquire images of the hidden face; an image analysis module for processing these images of the hidden face of the fiber preform in a plurality of adjacent scan windows, and for extracting weaving patterns therefrom and comparing them with reference weaving patterns previously stored in the module; a motor for driving the mandrel in rotation about its axis of rotation; and a control unit for stopping rotation of the mandrel if the result of the comparison reveals a difference of appearance between the two weaving patterns.