News

Sensor Technology :

• Weight sensor : monitor the load of the hook in real time to prevent overloading or unbalanced loading.

• Stress/strain sensor : detects micro deformation or cracks in the hook structure.

• Acceleration/inclination sensor : monitors hook swing, collision or abnormal movement.

• Temperature sensor : detects abnormal temperature rise caused by friction or overload.

• Visual sensor (camera) : Combined with AI image recognition, it detects cracks, deformation or wear on the hook surface.

Internet of Things (IoT) and Data Transmission :

• Through wireless technologies such as 5G/4G and LoRa, sensor data is transmitted to the cloud or local server in real time.

• Edge computing technology enables data preprocessing and reduces transmission delays.

Data analysis and AI algorithms :

• Fault prediction : Use machine learning (such as LSTM, random forest) to analyze historical data and predict potential faults.

• Anomaly detection : Detect risks such as abnormal vibration and sudden load changes through pattern recognition.

• Life Assessment : Estimate remaining service life based on material fatigue models and wear data.

Digital Twin :

• Build a virtual model of the hook, map the physical state in real time, and simulate performance under extreme conditions.

Real-time security monitoring :

• Overload alarm, wire rope unhooking warning, hook swing exceeding limit reminder.

• Automatically trigger emergency stop or load reduction operation.

Preventive Maintenance :

• Plan maintenance intervals based on wear data to reduce unplanned downtime.

Accident tracing :

• Store operating data for accident cause analysis.

Intelligent port/construction site :

• Linked with the crane control system to realize automated lifting operations.

Improved safety : reduce accidents caused by hook breakage and overloading.

Cost optimization : extend the hook life and reduce emergency maintenance costs.

Efficiency improvement : Reduce the frequency of manual inspections through condition monitoring.

Compliance : Meet the safety regulatory requirements for special equipment (such as ISO 4309, GB/T 3811).

Technical difficulties :

• Reliability of sensors in complex environments (high temperature, dust).

• Multi-source data fusion and high-precision algorithm optimization.

Future Directions :

• AI lightweighting : Deploy more efficient edge AI models.

• Blockchain : Ensure the immutability of monitoring data.

• AR/VR assistance : Repairs are guided by augmented reality.

Sany Heavy Industry Intelligent Crane : Integrated hook health monitoring system to achieve remote diagnosis.

TRUCONNECT® by Konecranes : hook status reporting via a cloud platform.

Zhenhua Heavy Industries Port Crane : Using vision to detect hook cracks.

Sensor Technology :

• Weight sensor : monitor the load of the hook in real time to prevent overloading or unbalanced loading.

• Stress/strain sensor : detects micro deformation or cracks in the hook structure.

• Acceleration/inclination sensor : monitors hook swing, collision or abnormal movement.

• Temperature sensor : detects abnormal temperature rise caused by friction or overload.

• Visual sensor (camera) : Combined with AI image recognition, it detects cracks, deformation or wear on the hook surface.

Internet of Things (IoT) and Data Transmission :

• Through wireless technologies such as 5G/4G and LoRa, sensor data is transmitted to the cloud or local server in real time.

• Edge computing technology enables data preprocessing and reduces transmission delays.

Data analysis and AI algorithms :

• Fault prediction : Use machine learning (such as LSTM, random forest) to analyze historical data and predict potential faults.

• Anomaly detection : Detect risks such as abnormal vibration and sudden load changes through pattern recognition.

• Life Assessment : Estimate remaining service life based on material fatigue models and wear data.

Digital Twin :

• Build a virtual model of the hook, map the physical state in real time, and simulate performance under extreme conditions.

Real-time security monitoring :

• Overload alarm, wire rope unhooking warning, hook swing exceeding limit reminder.

• Automatically trigger emergency stop or load reduction operation.

Preventive Maintenance :

• Plan maintenance intervals based on wear data to reduce unplanned downtime.

Accident tracing :

• Store operating data for accident cause analysis.

Intelligent port/construction site :

• Linked with the crane control system to realize automated lifting operations.

Improved safety : reduce accidents caused by hook breakage and overloading.

Cost optimization : extend the hook life and reduce emergency maintenance costs.

Efficiency improvement : Reduce the frequency of manual inspections through condition monitoring.

Compliance : Meet the safety regulatory requirements for special equipment (such as ISO 4309, GB/T 3811).

Technical difficulties :

• Reliability of sensors in complex environments (high temperature, dust).

• Multi-source data fusion and high-precision algorithm optimization.

Future Directions :

• AI lightweighting : Deploy more efficient edge AI models.

• Blockchain : Ensure the immutability of monitoring data.

• AR/VR assistance : Repairs are guided by augmented reality.

Sany Heavy Industry Intelligent Crane : Integrated hook health monitoring system to achieve remote diagnosis.

TRUCONNECT® by Konecranes : hook status reporting via a cloud platform.

Zhenhua Heavy Industries Port Crane : Using vision to detect hook cracks.