Eddy Current Testing has been mainly used to determine defects of conductive materials and wall thicknesses in heavy industries such as construction or aerospace. Recently, high frequency Eddy Current imaging technology was developed. This enables the acquirement of information of different depth level in conductive thin-film structures by realizing proper standard penetration depth. In this paper, we summarize the state of the art applications focusing on PV industry and extend the analysis implementing achievements by applying spatially resolved Eddy Current Testing. The specific state of frequency and complex phase angle rotation demonstrates diverse defects from front to back side of silicon solar cells and characterizes homogeneity of sheet resistance in Transparent Conductive Oxide (TCO) layers. In order to verify technical feasibility, measurement results from the Multi Parameter Eddy Current Scanner, MPECS are compared to the results from Electroluminescence.
Carbon fiber based materials are used in many lightweight applications in aeronautical, automotive, machine and civil
engineering application. By the increasing automation in the production process of CFRP laminates a manual optical
inspection of each resin transfer molding (RTM) layer is not practicable. Due to the limitation to surface inspection, the
quality parameters of multilayer 3 dimensional materials cannot be observed by optical systems. The Imaging Eddy-
Current (EC) NDT is the only suitable inspection method for non-resin materials in the textile state that allows an
inspection of surface and hidden layers in parallel. The HF-ECI method has the capability to measure layer
displacements (misaligned angle orientations) and gap sizes in a multilayer carbon fiber structure.
EC technique uses the variation of the electrical conductivity of carbon based materials to obtain material properties.
Beside the determination of textural parameters like layer orientation and gap sizes between rovings, the detection of
foreign polymer particles, fuzzy balls or visualization of undulations can be done by the method.
For all of these typical parameters an imaging classification process chain based on a high resolving directional ECimaging
device named EddyCus® MPECS and a 2D-FFT with adapted preprocessing algorithms are developed.
Carbon fiber materials become more and more important for many applications. Unlike metal the technological
parameters and certified quality control mechanisms for Raw Carbon Fiber Materials (RCF) have not yet been
developed. There is no efficient and reliable testing system for in-line inspections and consecutive manual inspections of
RCF and post laminated Carbon Fiber Reinforced Plastics (CFRP). Based upon the multi-frequency Eddy Current
system developed at Fraunhofer IZFP, structural and hidden defects such as missing carbon fiber bundles, lanes,
suspensions, fringes, missing sewing threads and angle errors can be detected. Using an optimized sensor array and
intelligent image pre-processing algorithms, the complex impedance signal can be allocated to different carbon fiber
layers. This technique enables the detection of defects in depths of up to 5 layers, including the option of free scale
measuring resolution and testing frequency. Appropriate parameter lists for optimal error classifications are available.
The dimensions of the smallest detectable flaws are in the range of a few millimeters. Algorithms and basic Eddy
Current C-Scan processing techniques for carbon fiber material testing are described in this paper.
Carbon fiber materials become more and more important for many applications. Unlike to metal, the technological
parameters and certificated quality control mechanisms have not been developed yet. There is no efficient and reliable
testing system for an inline inspection and a consecutively manual inspection of the Raw Carbon Fiber materials (RCF)
and the post laminated Carbon Fiber Reinforced Plastics (CFRP). Based upon the multi-frequency Eddy Current device
developed at Fraunhofer IZFP structural and hidden defects such as missing carbon fiber bundles, lanes, suspensions,
fringes, missing sewing threads and angle errors can be detected. Due to the help of an optimized sensor array and an
intelligent image pre-processing algorithm the complex impedance signal can be allocated to different carbon fiber
layers. This technique enables the possibility to detect defects in the depth up to 5 layers including the option of free
scale resolution and testing frequency. Appropriate parameter lists for an optimal error classification are available. The
dimensions of the smallest detectable defects are in the range of a few millimeters. A prototype of a special single sensor
and an eddy-current sensor array are developed and establish the way to transfer the prototype into an industrial
application.
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