##### CASE STUDY

# Pipeline Welding Inspection

Our client, a leading global pipeline supplier, enlisted our support in elevating the quality control of defect inspection in their welding lines. They specifically emphasized the need for advanced x-ray image analysis to accurately identify pores. Mindtrace, acknowledged for its expertise in this field, was approached to deliver a customized solution to meet their precise requirements.

**Challenges**

- A limited quantity of unlabelled training data (15 images)
- Only 5 available images for testing
- Several types of pipeline defects

### Defect detection and classification

The Detection Brain (D-brain) proficiently identified various types of defects present in the welding lines of the pipelines. These defects encompassed cracks, penetration issues, fusion irregularities, porosity, and other anomalies.

### Radiography film image collection

Mindrace collected all available welding images, all of which were radiographic film images.

### Radiography film quality classification

Our Classification brain (C-Brain) assessed the quality of radiographic film in order to accept or reject images, resulting in a final selection of 10 training images.

### Defect detection and classification

### Radiography film image collection

Mindrace collected all available welding images, all of which were radiographic film images.

## Outcome

Mindtrace effectively demonstrated the Brain-Sense™ platform’s anomaly detection capabilities. Despite constraints with a small dataset (10 training images and 5 testing images), the delivered solution achieved an impressive 91% accuracy. As the model processes more images, its accuracy is anticipated to improve further, leveraging the continuous learning capabilities of the AI brain.

**AI Brains Used**

1. Classification  
   Object identification & classification.

2. Detection  
   Identifies defect types, severity & location.

3. Analytics  
   Generates insights & recommendations.