THz Sensor System for Wet Paint Layer Characterization
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Solution Overview
Problem
Current methods for characterizing wet paint layer stacks in the automotive industry are limited by their inability to accurately measure the thickness and properties of multiple wet paint layers non-contactedly and reliably, especially in industrial settings where layers are applied before previous ones have dried, leading to inaccuracies and inefficiencies in quality control.
Innovation Solution
A method utilizing THz radiation to characterize wet paint layer stacks by fitting a physical model to detected THz radiation signals, allowing for the determination of individual paint layer parameters, including thickness and optical properties, without contact, enabling accurate prediction of dry layer thicknesses after curing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wet-on-wet technique is used to spray next layer on previous wet layer, then painting lead time is reduced, but measurement reliability deteriorates because traditional techniques cannot accurately characterize multiple wet layers
Solution Approach 1:
The patent replaces traditional mechanical contact-based measurement systems (acoustic sensors, magnetic sensors) with a non-contact optical measurement system using THz radiation. This substitution enables reliable characterization of multiple wet paint layers without physical contact, solving the reliability problem while maintaining the efficiency of wet-on-wet painting processes
Solution Approach 2:
The patent utilizes the unique interaction parameters of THz radiation with wet paint layers (absorption coefficients, refractive indices) that differ from traditional measurement frequencies. By operating in the THz frequency range and analyzing frequency-dependent optical properties, the system can distinguish between multiple wet layers and accurately measure their individual thicknesses and compositions
2Ease of operation
If traditional contact-based techniques (acoustic, magnetic sensing) are used, then measurement can be performed, but device complexity and contact requirements increase, limiting versatility
Solution Approach 1:
The THz measurement system provides universal applicability across different paint compositions, layer configurations, and measurement scenarios. A single non-contact THz system can characterize various paint types (solvent-based, water-based, powder coatings), multiple layer structures, and different substrate materials, eliminating the need for composition-specific calibration required by traditional contact-based techniques
3Ease of operation
If THz radiation methods are used for non-contact measurement, then contact mode limitations are overcome, but measurement precision deteriorates for multilayers with unknown refractive indices
Solution Approach 1:
The patent measures and utilizes more spectral information than traditionally required by analyzing the frequency-dependent optical properties across the THz spectrum. By capturing excessive spectral data points and using model fitting to extract parameters, the system achieves precise thickness measurements even when refractive indices are unknown, converting the challenge of unknown parameters into an opportunity for comprehensive material characterization
4Ease of manufacture
If peak position subtraction method is used for thickness determination, then calculation is simplified, but robustness deteriorates for wet paint layers with unknown optical properties
Solution Approach 1:
The patent introduces a physical model (transfer matrix method) as an intermediary between the raw THz spectral data and the thickness parameter. This model-based approach acts as a mediator that incorporates known physics of THz-wave interaction with multilayer structures, enabling robust and accurate thickness determination for wet paint layers with unknown optical properties by fitting model predictions to measured spectra
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 provides reliable, accurate, and efficient quality control of wet paint layer structures, enabling on-line, in-line, at-line, and off-line monitoring, significantly reducing production lead times in industries like automotive and aviation by ensuring precise paint layer characterization even when layers are still wet.
Implementation Method 1
Emitting, by the emitter system, a THz radiation signal towards the painted body such that the THz radiation interacts with the wet paint layer stack
Implementation Method 2
detecting, by the detector system, a response signal being the detected THz radiation signal having interacted with the wet paint layer stack
Data Source
Figure 1~2b
Figure 3~4
Figure 5~6(d)
AI summary
A method of characterizing a wet paint layer stack of a painted body is provided, which comprises at least two wet paint layers, by individual parameters of the wet paint layers, based on fitting to a physical model, the method being carried out by a sensor system in a non-contact manner The sensor system comprises an emitter system for emitting THz radiation, a detector system for detecting THz radiation, and a processing unit operationally coupled to the emitter system and the detector system. The method comprises: Emitting, by the emitter system, a THz radiation signal towards the painted body such that the THz radiation interacts with the wet paint layer stack,detecting, by the detector system, a response signal being the detected THz radiation signal having interacted with the wet paint layer stack;Determining model parameters of the physical model by optimizing the model parameters such that a predicted response signal of the physical model, which approximates the interaction of the THz radiation signal with the wet paint layer stack, is fitted to the detected response signal, wherein at least some of the model parameters are indicative of individual optical properties of the wet paint layers and of a wet paint layer thickness; and Determining, from the determined model parameters, the individual paint layer parameters of at least one of the wet paint layers.