Polarization Sensor 3D Surface Detection for Fiber Composites
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for detecting defects in fiber composite materials during the automated fiber laying process are inefficient and unreliable, particularly due to the complex retroreflective behavior of fiber materials, leading to significant downtime and potential manufacturing errors in large-scale components like aircraft wings and wind turbine rotor blades.
Innovation Solution
A method utilizing at least two polarization-sensitive recording sensors to capture three-dimensional surface data of the fiber material, generating a digital image that allows for accurate detection of defects by analyzing polarization-dependent measurement data, which can be used to identify even the smallest errors in the fiber material surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional light sources and standard sensors are used to detect fiber material surface, then the detection system is simple, but the detection precision is insufficient due to complex retroreflective behavior of fiber materials
Solution Approach 1:
The patent changes the polarization state parameter of the light to resolve the retroreflective behavior issue. By using polarized light at specific angles (45 degrees to the fiber direction) and analyzing the polarization state of reflected light, the system can distinguish between fiber reflections and actual defects, significantly improving detection precision without requiring overly complex equipment
Solution Approach 2:
The patent introduces polarization filters as an intermediary element between the light source and the fiber material surface, and between the surface and the sensor. These filters mediate the interaction by controlling the polarization state of incident and reflected light, enabling precise defect detection while keeping the overall system structure manageable
2Productivity
If manual inspection is used to detect defects in fiber laminates, then the detection method is simple, but the productivity is significantly reduced due to long inspection time
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated optical detection system. The system uses polarized light sources, polarization-sensitive sensors, and automated image processing algorithms to detect defects continuously during the fiber laying process, eliminating the need for manual inspection and maintaining high productivity
Solution Approach 2:
The detection system is designed to operate continuously during the fiber laying process rather than requiring separate inspection steps. The polarized light detection occurs in real-time as fibers are deposited, allowing continuous monitoring without interrupting the production flow, thus maintaining high productivity while eliminating inspection time losses
3Reliability
If standard imaging methods are used to capture fiber material surface, then the imaging system is simple, but the detection reliability is insufficient for challenging materials like matt black carbon fibers and translucent glass fibers
Solution Approach 1:
The patent changes multiple imaging parameters including light polarization state, illumination angle (45 degrees), and sensor polarization sensitivity to improve detection reliability for challenging materials. Matt black carbon fibers and translucent glass fibers have different optical properties that require specific polarization configurations to generate sufficient contrast for reliable defect detection
Solution Approach 2:
The patent applies different polarization filter orientations at different locations in the imaging system to optimize detection for various fiber types and defect orientations. The polarization-sensitive sensors are configured with specific local orientations to enhance contrast for particular material types, improving overall detection reliability across diverse fiber materials
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
This approach enables reliable and efficient detection of defects in fiber preforms, improving the quality and speed of the fiber laying process by reducing manual inspection time and increasing the accuracy of defect identification, even for challenging materials like matt black carbon fibers and translucent glass fibers.
Implementation Method 1
the radiation reflected from at least part of the fiber material surface (electromagnetic radiation, for example in the visible or invisible spectrum of light) is recorded from a first direction using a polarization-sensitive sensor
Implementation Method 2
the radiation reflected from at least part of the fiber material surface is recorded from a first direction using a polarization-sensitive sensor, and corresponding initial polarization-dependent measurement data is generated as a function of the recorded reflected radiation
Data Source
Figure 1
Figure 2
AI summary
The invention relates to a method for the three-dimensional detection of a fiber material surface of a fiber composite material placed on a tool by means of a detection device, wherein the method comprises the following steps: - recording the radiation reflected from at least a part of the fiber material surface by means of a first polarization-sensitive recording sensor from a first recording direction and generating first polarization-dependent measurement data as a function of the detected reflected radiation, - recording the radiation reflected from at least a part of the fiber material surface by means of at least a second polarization-sensitive recording sensor from a second recording direction different from the first recording direction and generating at least second polarization-dependent measurement data as a function of the detected reflected radiation.and - Creating three-dimensional surface data of the fiber material surface as a function of the first polarization-dependent measurement data and at least the second polarization-dependent measurement data using a data processing unit.