MFL Inspection Equipment
Advanced Non-Destructive Testing with MFL Technology
The MFL Inspection Equipment portable system represents cutting-edge non-destructive evaluation for wire ropes and metallic cables. Using magnetic flux leakage (MFL) technology, it accurately detects faults such as wire breaks, wear, abrasion, and corrosion, even identifying minor damages that could compromise operational safety.
Robust and Portable Design
This MFL Inspection Equipment features a rugged and portable design, capable of operating in extreme conditions from -35°C to +70°C with 95% humidity. Its intuitive touchscreen interface and wireless connectivity allow seamless management of historical data and automatic generation of PDF and Excel reports, ensuring full traceability and operational control.
Models and Technical Specifications
Four models are available, covering diameters from 10-50 mm. Each unit provides 6-8 hours of battery life with fast charging in 2-3 hours. Quick installation using safety buckles and guide wheels allows efficient setup within seconds, optimizing workflow and minimizing personnel requirements.
Industrial Applications of MFL Inspection Equipment
- Cranes and lifting systems
- Mining operations
- Critical infrastructure and energy facilities
- Predictive maintenance and structural integrity management
- Inspection of cables in heavy transportation and construction
Key Benefits of MFL Inspection Equipment
- Reduces inspection time by more than 70% compared to traditional methods
- High accuracy in detecting minimal defects
- Complies with international standards
- Specialized technical support and continuous software updates
- Manufactured with high-quality components for long-term durability
- Portable and easy to transport across multiple sites
Commitment to Quality
The MFL Inspection Equipment ensures maximum reliability and efficiency in demanding industrial environments. It is the ideal solution for companies seeking optimized inspections, operational safety, and critical asset protection through reliable predictive maintenance.
