The AI-powered Balloon Inspection Machine (BA-AI-1000) provides a comprehensive solution for efficient and accurate
balloon outer surface inspection, leveraging advanced defect
detection technology. Equipped with ultra-high-resolution imaging
and precise optical measurements, it significantly reduces errors,
lowers quality control costs, and optimizes inspection times,
ensuring faster and more reliable detection.
Adaptive Infeed and High-Speed Auto Focus: Automatically adjusts to incoming balloon materials, enabling rapid
focus on key parameters such as diameter and length through visual
inspection.
Ultra-Precision Non-Contact Wall Thickness Measurement: Utilizing proprietary interferometry technology, the system
achieves precise wall thickness measurement within a 150µm
detection area, with a measurement range from 5µm to 100µm.
Advanced Optical Imaging Technology: Using specialized lighting and a 25MP high-definition camera, the
system delivers clear imaging of surface defects on transparent
balloon materials.
Detection Accuracy: With AI-driven and traditional vision-based defect screening, the
system achieves a miss rate of less than 0.1%, outperforming
operators with two years of experience.
Rapid Inspection Efficiency: The system is also well-suited for larger medical balloons. For a
100-millimeter balloon, size detection is completed in
approximately 500 milliseconds. Defect detection is conducted
within 35 seconds, and wall thickness detection, including 3-6
detection points, is also completed within 35 seconds.
Upper Computer Communication: The upper computer communication capability ensures seamless
integration with systems, enabling real-time monitoring and control
via a centralized interface. This enhances production efficiency
and transparency. It supports data storage and analysis,
facilitating long-term optimization and intelligent management of
machines and equipment.
What are the core technologies used in the AI-powered balloon
inspection machine? The system integrates convolutional neural networks (CNN), deep
learning, computer vision, and advanced imaging techniques to
detect defects in medical balloons with high precision.
What types of defects can the AI detect, and what is the detection
accuracy? The AI can identify surface irregularities, thickness variations,
dimensional inconsistencies, etc.
How does the system handle real-time inspection and defect
classification? The AI processes high-resolution images in real-time, classifies
defects based on severity, and provides instant feedback for
process adjustments.
Can the AI model be customized for different balloon types and
materials? Yes, the AI model is adaptable and can be trained on different
balloon geometries, polymer compositions, and manufacturing
tolerances.
How does the AI system improve over time? The system continuously learns from new defect patterns, improving
accuracy and reducing the need for manual re-inspection.
How does the AI-powered inspection system integrate with existing
manufacturing lines? It supports seamless integration via industrial protocols and can
connect with SCADA and MES for real-time quality tracking.
How does AI-driven inspection reduce costs? It minimizes waste, reduces reliance on manual inspection, lowers
rework rates, and improves overall production efficiency.
