Fiber Composite Material Analysis in Aerospace Using CT Data

Similar documents
Software tools for robust extraction, analysis and visualization of porosities in XCT scans of fiber-reinforced polymers

Klingleweg 8, Meersburg, Germany, Industriestr. 4, Donauwörth, Germany,

Wieblinger Weg 92a, Heidelberg, Germany, Phone: , Fax: ;

Digital Laminography and Computed Tomography with 600 kv for Aerospace Applications

Evaluation of 3D fiber orientation analysis based on x-ray computed tomography data

Advanced Computed Tomography System for the Inspection of Large Aluminium Car Bodies

Advanced Reconstruction Techniques Applied to an On-Site CT System

Translational Computed Tomography: A New Data Acquisition Scheme

X-ray Computed Tomography of Structural Parts made by Injection Molding and a local Reinforcement with Thermoplastic UD-Sheets

Comparison of Probing Error in Dimensional Measurement by Means of 3D Computed Tomography with Circular and Helical Sampling

Roger Wende Acknowledgements: Lu McCarty, Johannes Fieres, Christof Reinhart. Volume Graphics Inc. Charlotte, NC USA Volume Graphics

Non-Destructive Failure Analysis and Measurement for Molded Devices and Complex Assemblies with X-ray CT and 3D Image Processing Techniques

Closing the Gap between Process- and Crash Simulation for Composite Materials

Digital Shearographic Non-destructive Testing Laboratory

2. Combination of eddy current inspection and imaging analysis

UMASIS, AN ANALYSIS AND VISUALIZATION TOOL FOR DEVELOPING AND OPTIMIZING ULTRASONIC INSPECTION TECHNIQUES

The new generation of industrial computed tomography. The Desktop CT exact S

Advanced automated High Speed Computed Tomography for production process control. DGZfP 2011, Bremen

Saurabh GUPTA and Prabhu RAJAGOPAL *

17th World Conference on Nondestructive Testing, Oct 2008, Shanghai, China

John R. Mandeville Senior Consultant NDICS, Norwich, CT Jesse A. Skramstad President - NDT Solutions Inc., New Richmond, WI

THREE DIMENSIONAL EXAMINATION OF DIRECTIVITY PATTERN IN IMMERSION TANK TESTING

MObjects A Novel Method for the Visualization and Interactive Exploration of Defects in Industrial XCT Data

Investigating the influence of local fiber architecture in textile composites by the help of a mapping tool

Registration concepts for the just-in-time artefact correction by means of virtual computed tomography

Detection of Narrow Gaps Using Hessian Eigenvalues for Shape Segmentation of a CT Volume of Assembled Parts

An Acquisition Geometry-Independent Calibration Tool for Industrial Computed Tomography

3D Computed Tomography (CT) Its Application to Aerospace Industry

HIGH RESOLUTION COMPUTED TOMOGRAPHY FOR METROLOGY

CFRP manufacturing process chain observation by means of automated thermography

VGSTUDIO MAX 3.0. High-End Industrial CT Software

Impact of 3D Laser Data Resolution and Accuracy on Pipeline Dents Strain Analysis

Full 3D characterisation of composite laminates using ultrasonic analytic signals

MULTI-MODALITY 3D VISUALIZATION OF HARD-ALPHA IN TITANIUM

HIGH-SPEED THEE-DIMENSIONAL TOMOGRAPHIC IMAGING OF FRAGMENTS AND PRECISE STATISTICS FROM AN AUTOMATED ANALYSIS

VGStudio MAX 3.0. High-End Industrial CT Software

Robot-Based Solutions for NDT Inspections: Integration of Laser Ultrasonics and Air Coupled Ultrasounds for Aeronautical Components

MCT225 HA Metrology CT

Robot-based real-time ultrasonic tomography for industrial NDT applications

Simulation of the Stress Concentration around Pores in 3D Printed Components

THREE DIMENSIONAL INDUSTRIAL METROLOGY USING X-RAY COMPUTED TOMOGRAPHY ON COMPOSITE MATERIALS

VGSTUDIO MAX. High-End Industrial CT Software

Available online at ScienceDirect

Automatic analysis and weld indications classification on TFM acquisitions

Ultrasonic Multi-Skip Tomography for Pipe Inspection

UMASIS, an analysis and visualization tool for developing and optimizing ultrasonic inspection techniques

NDT of a Composite Using MicroCT Data and Image-based Finite Element Modelling

Visualization of voids in actual C/C woven composite structure

ADVANCED POST-PROCESSING OF RESULT FROM MOLDFLOW / MOLDEX3D AND EXTENSION

SHEAROGRAPHY TESTING ON AEROSPACE CFRP COMPONENTS AND OTHER COMPOUNDS. Abstract. Introduction

TOLERANCE ANALYSIS OF THIN-WALL CFRP STRUCTURAL ELEMENTS USING TOMOGRAPHIC IMAGING

INDUSTRIAL SYSTEM DEVELOPMENT FOR VOLUMETRIC INTEGRITY

Comparison of fiber orientation analysis methods in Avizo

coding of various parts showing different features, the possibility of rotation or of hiding covering parts of the object's surface to gain an insight

Characterization of damage mechanisms in glass fibre reinforced polymers using X-ray computed tomography

In-plane principal stress output in DIANA

The new generation of industrial computed tomography. The CT workstation exact M

A NUMERICAL SIMULATION OF DAMAGE DEVELOPMENT FOR LAMINATED WOVEN FABRIC COMPOSITES

Computerized Tomography for Industrial Applications and Image Processing in Radiology March 15-17, 1999, Berlin, Germany

VGSTUDIO MAX. High-End Industrial CT Software

CHARACTERISATION OF WAVINESS DEFECTS IN INDUSTRIAL COMPOSITE SAMPLES

2: Static analysis of a plate

Volume Rendering. Computer Animation and Visualisation Lecture 9. Taku Komura. Institute for Perception, Action & Behaviour School of Informatics

What makes Bolt Self-loosening Predictable?

High Resolution Phased Array Imaging using the Total Focusing Method

Simulation-Supported Decision Making. Gene Allen Director, Collaborative Development MSC Software Corporation

Volume Data Inspection Tools for Industrial Computed Tomography

CT Reconstruction with Good-Orientation and Layer Separation for Multilayer Objects

L1 - Introduction. Contents. Introduction of CAD/CAM system Components of CAD/CAM systems Basic concepts of graphics programming

MULTI-PURPOSE 3D COMPUTED TOMOGRAPHY SYSTEM

Shearography as an Industrial Application Including 3D Result Mapping

AUTOMATED HIGH SPEED VOLUME COMPUTED TOMOGRAPHY FOR INLINE QUALITY CONTROL

Limited view X-ray CT for dimensional analysis

Coordinate Measuring Machines with Computed Tomography

VALIDATION OF LOCAL STITCHING SIMULATION FOR STITCHED NCF PLY STACKS

17th World Conference on Nondestructive Testing, Oct 2008, Shanghai, China

Principal Roll Structure Design Using Non-Linear Implicit Optimisation in Radioss

Case Studies in the Use of Computed Tomography for Non-Destructive Testing, Inspection and Measurement

Application Note. Oechsler: Fewer Loops for Better Tools

Measuring Microfeatures with Dense Point Clouds

Sizing and evaluation of planar defects based on Surface Diffracted Signal Loss technique by ultrasonic phased array

INDUSTRIAL PHOTOGRAMMETRY FOR APPLICATIONS IN AUTOMOTIVE AND AEROSPACE INDUSTRY

Development of Optical Coherence Tomography for the Measurement of the Surface Wrinkle of Composite Parts

A new concept for high-speed atline and inline CT for up to 100% mass production process control allowing both 3D metrology and failure analysis

Example of one enclave in the field. strike. Right hand rule convention of orientation. pitch or rake. dip

Parameter Identification based on quasi-continuous strain data captured by high resolution fiber optic sensing. Andreas Künzel TU Berlin

Corrosion detection and measurement improvement using advanced ultrasonic tools

Non-Destructive Testing for Detection, Localization and Quantification of Damage on Composite Structures for Composite Repair Applications

Determination of the aperture of the LHCb VELO RF foil

Emissive Clip Planes for Volume Rendering Supplement.

FE ANALYSES OF STABILITY OF SINGLE AND DOUBLE CORRUGATED BOARDS

A new Concept for High-Speed atline and inlinect for up to 100% Mass Production Process Control

LightHinge+: Additively manufactured lightweight hood hinge with integrated pedestrian protection

Dedicated Software Algorithms for 3D Clouds of Points

XT H 225 Industrial X-ray and Computed Tomography

MODELING OF FIBER-REINFORCED PLASTICS TAKING INTO ACCOUNT THE MANUFACTURING PROCESS

A THIRD GENERATION AUTOMATIC DEFECT RECOGNITION SYSTEM

Computed tomography of simple objects. Related topics. Principle. Equipment TEP Beam hardening, artefacts, and algorithms

3D X-ray Microscopy Characterization. Metal Additively Manufactured Parts. Application Note

Automated In-Process Inspection System for AFP Machines

Transcription:

4th International Symposium on NDT in Aerospace 2012 - We.2.A.3 Fiber Composite Material Analysis in Aerospace Using CT Data Dr. Tobias DIERIG, Benjamin BECKER, Christof REINHART, Thomas GÜNTHER Volume Graphics GmbH; Heidelberg, Germany dierig@volumegraphics.com, becker@volumegraphics.com, reinhart@volumegraphics.com, guenther@volumegraphics.com Abstract. In this paper we will show how CT as a non destructive test method can improve the quality of fiber composite materials. Using new algorithms, it is now possible to determine the internal fiber structure of composite parts by using a CT scan. This is used today, e.g., to examine helicopter rotor blades, allowing for the detection e.g. of ripples even in cases where the resolution of the scan is not good enough to separate single fibers in the blade. The results of this analysis, the local orientation of the fiber structure, can be calculated on an arbitrary scale and exported to other software packages. This functionality enables the user for the first time to compare the simulated fiber orientation with the real 3D distribution of the fiber directions in the samples without the need to destroy the part. But not only a comparison between simulated and real structure can be realized; these analysis results can also be used as input values, e.g., for a mechanical simulation of the part. Introduction In today s aerospace industry, a huge challenge is an overall design optimized for lightweight. To solve these tasks, composite and fiber enforced materials are widely used. Aside from the capability to analyze the porosity and the geometry of a part in a CT scan, it is now possible to analyze the internal structure of a scanned part. Especially for the production of all kinds of fiber enforced products, an exact knowledge of the internal fiber structure is needed to improve the production and of course the product development process. The fiber distribution and direction are crucial factors for the mechanical properties of the final part like the shear- and the elasticity-module. New algorithms analyzing the grey value gradient in a CT data set make it now possible to analyze the internal fiber structure in a scanned part without the need to destroy it. 1. Non destructive Fiber Orientation Analysis using CT data 1.1 General approach Due to the nature of an X-ray CT scan you will get information on the internal material structure of the scanned part. Up to now this information is used, e.g., to analyze the parts for manufacturing imperfections like pores or inclusions. These defects can be detected automatically by analyzing the grey value differences within the scan between the material and the imperfection. Licence: http://creativecommons.org/licenses/by-nd/3.0 1

Using dedicated new algorithms, it is now possible to analyze the orientation of the internal grey value structure of a scanned part. If you have a scan where you have fiber structures as internal structures this analysis will give you the orientation and distribution of the fibers in your part. As a result of the orientation analysis you have a tensor for the local grey value orientation for every position in your dataset. This tensor can now be projected to a userdefined plane or compared to a specified reference direction. The results can be visualized as a color overlay showing local orientation (see Figure 1). Using this analysis in a Region of Interest with a known nominal fiber orientation, the statistics provided along with the analysis result gives the possibility to compare nominal and real orientations. Figure 1: The left image shows the fibers in a CT scan, in the right image the orientation of the fibers is color-coded and locally probed at 2 positions. Apart from to the color coded visualization of the local orientation, where the calculated local orientation tensor is projected in a plane or compared to a reference direction, the actual tensor can also be visualized directly in 3D. The determined tensor is shown as several ellipses in Figure 2. The different colors of the ellipses represent their different shapes. In this example, the tensors shown are averaged within a certain volume. Having this averaging capability can give you a very quick overview of the average orientation within a specific region of your object. To understand the distribution of fiber orientations along a given coordinate axis (e.g., perpendicular to the surface of the part), it is possible to calculate averaged orientation tensors slice by slice in an arbitrary direction. The result is displayed in a line plot of the individual components of the orientation tensor, providing the possibility to compare nominal and actual values. A typical plot is shown in Figure 3. In this real world example, the mean orientation of the fibers in the middle of the part is perpendicular to the orientation at the edges. This can be seen also in Figure 2 where the same results are shown in 3D as described above. 2

Figure 2: The orientation tensors are visualized as ellipses in the 3D image of the scanned object. The change of the local orientation in the middle region of the object is clearly visible. Figure 3: Line plot through one slice of the 3D data set, showing the xx,yy and zz components of the orientation tensor. 3

2. Closing the loop of simulation using fiber orientation in CT data 2.1 A non destructive way to verify simulations in the manufacturing process Using a CT for the inspection of fiber structures will open the possibility to close the big gap between the simulation of fiber-reinforced parts and their respective quality control. Once you have the information of the local orientation generated via a CT scan available at every single position in the object, it is easy to compare the actual orientation of the fibers with the simulated nominal orientation. Normally the detail level of a CT scan is much higher than the used grid size for mechanical and manufacturing simulations. To overcome this problem, it is useful to average the orientation results on a higher scale. In Figure 4 the averaged results for a coarse grid are shown. To get comparable results between a simulation and real world data, it is possible to import the specific simulation mesh directly into the visualization/analysis software. The analysis will then calculate averaged values of the local fiber orientation and also the fiber/matrix ratio for each single cell. This will allow for the direct comparison of calculated and simulated values without any mapping error. Using the simulation grid as a basis for an averaging of the local orientations makes a comparison of the simulated and the measured orientations- very accurate. With this functionality a complete new level of simulation accuracy will be achieved. An improvement of the simulated manufacturing process will lead to a shorter product development time, and of course will increase the overall quality of the part. All this can be done without destroying the part and very fast compared to the standard methods used today like cutting, polishing and 2D analysis. With this kind of direct 3D analysis the quality and process control of composite parts will come to a new level of accuracy and speed. 2.2 Getting data for real world mechanical simulations of composite parts The orientation of fibers or fiber bundles is crucial for the mechanical properties of a part. Especially the shear and the elasticity module are heavily influenced by the internal fiber structure. For the whole design process of a lightweight part, a simulation of the mechanical properties is important. For fiber enforced parts, up to now this has been difficult to achieve without the exact knowledge of local fiber orientation and distribution. Having now the possibility to get the exact local fiber orientation and the fiber matrix ratio for every single simulation cell will increase the quality of the simulation results dramatically. Taking advantage of all information a CT scan provides, especially the distribution of pores, fiber directions and the fiber matrix ratio is leading to a better understanding of the interactions between these components. Building up on this knowledge leads to a deeper insight into the dependencies between material used and the mechanical properties that can be achieved. Especially the influence of imperfections of and within the materials used on the mechanical properties can be predicted more accurately. Using these new possibilities will make the whole product design process much faster and more reliable. 4

Figure 4: The top left image shows the original CT data. Top right shows the grid as basis for the averaging. The bottom left image shows the color coded visualization of the orientation analysis. In the bottom right image the structure tensors are shown averaged within the grid. 3. Fiber Analysis in helicopter rotor blades The analysis described above returns very good results even in a scan where the single fibers could not be segmented (see Figure 5). That means that the software tool can handle whole fiber bundles in the same way as single fibers (see Figure 5) if the resolution in the scan is not good enough to make single fibers visible. The described fiber structure analysis in combination with the capability to compare parts against an averaged master part is already used today, e.g., to inspect rotor blades of helicopters [1]. 5

Figure 5: The left image is showing a fiber orientation analysis in a helicopter rotor blade to identify ripples. The defect could clearly be detected, although the resolution is not good enough to segment single fibers in the blade, see right image. The comparison against an averaged master part as described in [1], which has been generated based on a statistically significant number of good parts, allows for deciding whether a specific analysis result is a defect, or if it is within the local production tolerances at this specific position in the part. At the end the nominal values of the orientation for every position and the permissible deviations caused by the production process are available. 4. Conclusion and Outlook In this paper a complete new way of analyzing fiber orientations in CT data has been shown. Furthermore a real world example illustrates that these techniques can be used for parts in the aerospace industry e.g., for the inspection of rotor blades, even if the scan does not have the resolution to separate every single fiber within the scan. Aside from the ability to check the orientation of the internal structures of a part, it is also possible for the first time to get a direct link to the simulation world. By averaging the local fiber orientations within a grid, which can be imported or exported into a simulation software, a better understanding of the effect of the defect can be achieved. Here again, using CT can and will improve the whole process chain linked to the production and development of fiber enforced materials. The techniques described above opens up a lot of new possibilities for quality control, especially in the aerospace industry, where safety and lightweight design are the crucial factors for further product developments. References [1] B Diewel, R Oster, T Dierig, T Günther, Computed Tomography Image Processing automated Analysis on GFRP Helicopter Rotor Blades`, DGZfP Proceedings BB 128, P30, June 2011. 6