Battery Components Opto solino RTI sensor
Detecting micro defects using BRDF computational imaging
Customer Task:
Battery components such as button cells, coin batteries and cylindrical battery housings must meet strict quality and safety standards. Surface defects can affect sealing, electrical contact, corrosion resistance and overall product reliability.
Manufacturers therefore require reliable inspection methods for:
- coin cell batteries (e.g. CR series)
- cylindrical battery housings
- stamped and engraved markings
- sealing surfaces and edges
- coated and metallic surfaces
The goal is to detect surface defects early in the production process and ensure consistent quality across all battery components before assembly or shipment.
Inspection Challenges:
Inspecting battery surfaces is challenging for conventional machine vision systems due to a combination of material properties, geometry and process variability.
- Highly reflective metallic surfaces on housings (nickel, stainless steel, aluminum) create strong reflections and glare, which can hide defects or create false detections.
- Curved edges of Coin cells and cylindrical batteries have rounded edges that cause changing light reflections.
- Low-contrast engravings and laser markings, stamped text or logos have minimal contrast and are difficult to detect reliably
- Micro-scale defects, scratches, dents, coating irregularities or early corrosion are often in the micron range and barely visible
- Surface contamination and dust particles, oil residues or process contamination can affect sealing, electrical contact and long-term reliability.
- Coating and material inconsistencies like thin coatings, oxidation layers or surface treatments may vary locally and are difficult to detect visually.
- Process-related variability, differences in stamping, forming or coating processes lead to variations in surface appearance that complicate automated inspection.
- Unstable inspection results of traditional vision systems depend heavily on fixed lighting setups, leading to inconsistent results when surface reflectance changes.
Technology Principle
The solino RTI sensor uses BRDF-based computational imaging to reveal weld surface structures that conventional imaging cannot reliably detect.
Within milliseconds the system captures a series of 64 images under multiple illumination directions and reconstructs the surface reflectance information computationally. Key elements include:
- 64 multi-directional LED illumination
- photometric stereo image capture
- reflectance-based surface reconstruction
- computational defect enhancement
This approach creates a stable and repeatable inspection environment independent of external lighting conditions.
.
.
Application
solino 25×25 can be used to inspect battery components across a wide range of sizes, from small button cells to larger cylindrical housings with typical inspection targets include:
- coin cell surfaces and engraved labels
- cylindrical battery housings
- sealing edges and contact areas
- surface coatings and finishes
- contamination or handling damage
Because the system captures the surface under 64 illumination directions, even very small defects become visible with enhanced contrast.
Original RGB image vs. solino Structural CPI Image
Original RGB image vs. solino reflectance CPI Image
Technology Benefits
Using controlled multi-directional illumination, solino enhances the visibility of surface anomalies on battery components such as:
- micro scratches and dents on metal housings
- irregularities in engraved markings
- coating defects or corrosion spots
- particles and contamination on surfaces
The technology works particularly well on reflective and curved metal surfaces where traditional imaging often fails due to uncontrolled reflections.
Original RGB image vs. solino Surface Anomaly CPI Image
Solution Architecture:
Item nummer: 100-SO-25-MAN-001 solino 25x25 - Viewer - Stand
The inspection system consists of:
- solino RTI sensor integrated 64 LED dome illumination
- high-resolution 20 MP industrial camera
- solinoStudio SW for acquisition and processing
The compact sensor design allows easy integration into automated production systems or inspection stations.
Inspection workflow:
- Battery component is positioned under the solino sensor
- The system captures images under different illumination directions
- Computational algorithms reconstruct the surface reflectance information
- solinoStudio enables visualization of surface structures
Conclusion
The solino RTI sensor combines controlled illumination with computational imaging to reveal surface structures that are difficult to detect using traditional machine vision systems.
This enables reliable inspection of battery components, helping manufacturers improve quality assurance, reduce defects and ensure long-term product reliability.
Additional Image processing and AI available on request
Want to see solino® in action or discuss your specific application?
See solino® in action — book a live demo.
Let’s discuss your application — book a call with our expert.