GoPxL Anomaly Detector AI
Flawless Quality Inspection with Artificial Intelligence Supported 3D Anomaly Detection
GopXL Anomaly Detector AI automatically detects surface defects and structural anomalies by analyzing the data obtained from 3D laser profile sensors and snapshot sensors on production lines with artificial intelligence.
The model performs its own learning by referencing only the good parts; In this way, it detects new or unexpected deviations with high accuracy without the need for predefined defect data.
This approach provides more stable and reliable quality control results based on 3D data.
Main Features
- Learning Without Data (Unsupervised AI)
Using only the good parts, it learns the normal surface model and identifies possible anomalies. - 3D Deep Learning Architecture
It detects errors at the micron level by analyzing depth data received from laser profile sensors or snapshot systems. - Adaptive Model
It provides self-calibration and adaptation on different surfaces such as metal, plastic, rubber, glass and textile. - Easy Integration
Directly processes data from 3D sensors; Compatible seamlessly with Omron, LMI3D, or similar industrial 3D systems. - Visual and Depth Based Reporting
It provides detailed analysis by marking faulty areas on both 2D images and 3D height maps.
Why GopXL?
GopXL Anomaly Detector AI goes beyond classic 2D image control systems and combines 3D depth analysis and artificial intelligence.
In this way, it detects not only surface but also geometric and volumetric anomalies.
Advantages
- High accuracy even on complex surfaces
- Eliminates operator dependency
- 100% automatic and consistent quality control
- Reduces waste rate and increases productivity
Technical Specifications
| Feature | Value |
| Algorithm Type | Deep learning based 3D anomaly detection |
| Model Training | Only the good parts (unsupervised learning) |
| Supported Sensors | 3D laser profile sensors, snapshot sensors |
| Data Format | Point cloud, depth map |
| Processing Time | < 150 ms / parça |
| Interfaces | REST API, OPC UA, TCP/IP |
| Platform Compatibility | Windows / Linux / Edge devices |
| Output Format | 3D anomaly mask, height difference map, classification score |