Intelligent Power-Analysis Anti-Mislifting System
Detects un-disengaged twistlocks and container hang-up incidents through CNN analysis of motor electrical waveforms — false-alarm rate < 0.5 %, 0 % missed alarms.
Request data sheetOverview
When a twistlock fails to fully disengage, continued hoisting can lift the entire trailer together with the container — a major cause of port accidents. Celijia's anti-mislifting system analyses the multi-impulse signature of the hoisting motor's transient electrical parameters using a Convolutional Neural Network to detect the unique waveform of a trailer-lifting event.
Because the system is based on the Intelligent Power-Analysis Sensor — pure electrical signal analysis — it is inherently insensitive to weather and lighting conditions, eliminating the persistent false alarms typical of camera- or laser-based solutions.
Deployed on remotely operated rail-mounted gantry cranes in Zhejiang, the system successfully prevented a real trailer-lifting incident in December 2025.
Key features
- Built on the Intelligent Power-Analysis Sensor
- False-alarm rate < 0.5 %, missed-alarm rate 0 %
- Detects all four twistlock combinations and snagging conditions
- CNN-based waveform recognition, OTA model upgrades
- Unaffected by rain, fog, temperature or vibration
- Validated by 6 years of R&D and 100+ field installations
- Cycle-time saving ≈ 5 s per lift; ≈ 10 % energy saving
Architecture & operating modes
Schematic illustrations showing where the system sits in the crane control loop and how it behaves under each fault scenario.

Installation photos








