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SWIR Imaging for Lithium-Ion Battery Inspection

JiangJenny |


SWIR MACHINE VISION

SWIR Imaging for Lithium-Ion Battery Inspection

Exploring how short-wave infrared imaging can reveal material and layer information that may be difficult to distinguish with conventional visible-light inspection.


As lithium-ion battery manufacturing becomes more automated, machine vision systems need to inspect not only surfaces, but also the positional relationship between different materials and layers.

SWIR provides an additional imaging channel for applications where visible-light contrast is not sufficient.

This is particularly relevant to battery stacking processes, where electrode sheets and separators form a layered structure. Depending on the materials and inspection conditions, SWIR imaging can provide additional contrast and help reveal features that are difficult to observe using visible light alone.


01 / INSPECTION CHALLENGE

Why Battery Layer Inspection Can Be Difficult

Lithium-ion batteries contain multiple layers of electrode sheets and separators. During stacking, maintaining the intended positional relationship between these layers is an important inspection task.


Layered Structures

Electrode sheets and separators are physically stacked on top of one another. Once a layer is covered, its edge or position may become difficult to distinguish using conventional imaging.


Alignment Matters

Small positional differences between electrode sheets and separators can be difficult to evaluate when the materials have limited visible-light contrast.


``` Visible light and SWIR imaging comparison for lithium-ion battery electrode inspection
Conceptual comparison: SWIR imaging can provide additional contrast for layered battery structures that may be difficult to distinguish under visible illumination.
```
 02 / WHY SWIR

What Can SWIR Add to Battery Inspection?

SWIR uses longer wavelengths than visible-light imaging. Depending on the material, wavelength and optical configuration, these wavelengths can interact with materials differently and provide information that is not readily available from visible images.

Beyond Conventional Surface Imaging

For lithium-ion battery stacking, this additional spectral information can help distinguish the position of electrode sheets and separators.

In Sony's published battery inspection example, electrode sheets beneath separators were difficult to distinguish with visible light, while SWIR imaging made the electrode misalignment more apparent.


03 / APPLICATION AREAS

Where Can SWIR Be Applied in Battery Inspection?

The exact inspection opportunity depends on the battery material, process stage, optical configuration and required measurement. Several areas can be evaluated when visible imaging alone is not enough.

Electrode Alignment

Evaluate the positional relationship between electrode sheets and separators during stacking.

Layer Position Inspection

Identify layer edges or displacement where overlapping materials make conventional imaging challenging.

Electrode Inspection

Explore additional contrast for electrode boundaries, surfaces and material-related features.

Material Differentiation

Use spectral response differences to complement conventional visible-light inspection.

Automated Inspection

Integrate SWIR imaging into machine vision systems for automated image analysis and process monitoring.

R&D and Process Development

Evaluate whether SWIR provides useful information before developing a production inspection system.


``` SWIR camera system for lithium-ion battery machine vision inspection
A typical SWIR inspection concept combines the camera, optics, illumination and image processing around the specific battery inspection target.
```
04 / SYSTEM INTEGRATION

Integrating SWIR into a Battery Vision System

For system integrators and machine builders, the camera is only one part of the inspection architecture. The imaging system should be developed around the actual battery material and inspection objective.

Start With the Inspection Requirement

Before selecting the camera, define what needs to be detected, the inspection area, working distance, required spatial resolution, material characteristics and available illumination.

Battery Material
→
Inspection Target
→
→
Optics + Illumination
→
Image Processing

05 / VISION DATUM SOLUTION

A Practical SWIR Camera for Battery Inspection

For battery inspection systems where visible imaging does not provide enough contrast between layers or materials, SWIR can be evaluated as an additional imaging channel.

Vision Datum iCt-SWG130S-Pro

For system integrators and machine builders developing lithium-ion battery inspection equipment, the iCt-SWG130S-Pro can be evaluated as a SWIR imaging option for applications where additional spectral information is required.

The camera can be integrated into a GigE-based machine vision architecture, allowing developers to combine SWIR imaging with their existing image-processing and automation systems.

The most appropriate configuration should be determined from the actual battery material, inspection target, working distance, field of view, illumination and processing requirements.

 Explore iCt-SWG130S-Pro

06 / KEY TAKEAWAY

SWIR as an Additional Layer of Inspection Information

SWIR does not need to replace conventional visible-light imaging. Instead, it can provide an additional imaging channel when the material or layered structure being inspected is difficult to distinguish under visible illumination.

For lithium-ion battery manufacturing, this can be particularly relevant to stacking and alignment inspection, where the positional relationship between electrode sheets and separators is important.

For developers building automated battery inspection equipment, the next step is to evaluate the actual material, illumination conditions and inspection target to determine whether SWIR can provide useful additional contrast.


Explore SWIR for Battery Inspection

Developing a lithium-ion battery inspection system? Explore the Vision Datum iCt-SWG130S-Pro and evaluate how SWIR imaging can fit into your machine vision architecture.

View Camera Details →  

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