ISO 21936:2020 Crane Condition Monitoring Explained
ISO 21936:2020, "Condition Monitoring and Fault Diagnosis of Cranes," is the technical standard governing crane condition monitoring. It defines monitoring schemes, parameter acquisition requirements, fault diagnosis methods, and predictive maintenance strategies for crane steel structures, mechanical systems, and electrical systems, covering key technologies such as vibration, temperature, stress, and oil analysis.
Monitoring Parameters and System Setup
Crane condition monitoring covers three primary systems. For the steel structure, strain gauges on the main girder mid-span measure stress concentration zones, while dynamic acceleration sensors on the outriggers capture vertical and horizontal vibration. The mechanical system monitors hoisting motor bearing temperature (Pt100) and vibration, reducer oil temperature/level and vibration, and brake wear and open/closed status. The electrical system tracks motor current, voltage, power factor, control cabinet temperature and humidity, and cable insulation resistance through online monitoring. Dynamic parameters are sampled at ≥100 Hz, steady-state at ≥1 Hz. Data acquisition units offer IP65 or higher protection and support local storage for at least 7 days with offline data buffering and retransmission.
Fault Diagnosis Methods
Online diagnosis relies on threshold-based rules—exceeding vibration limits triggers an early warning. Trend analysis tracks parameter changes over time; for example, a month-over-month increase in vibration indicates bearing wear. Offline diagnosis uses vibration spectrum analysis, where frequency components correspond to distinct fault modes: bearing fault frequencies appear at 0.4–0.6× rotational frequency, and gear mesh frequency equals tooth count × rotational frequency. FFT spectrum analysis identifies the faulty component. Oil analysis detects metal particle concentration and size distribution to determine wear type and severity. Kelude Heavy Industry provides integrated condition monitoring systems and fault diagnosis services.
| diagnostic method | Principle | Application |
|---|---|---|
| Threshold Method | vibration/Temperature Exceedance | Real-time Online Alarm |
| Trend Analysis | Parameter Month-over-Month Variation | Wear Accelerationearly warning |
| Spectrum Analysis | FFTcharacteristic frequency | Identification Fault Component |
| Oil Analysis | Metal Particle Analysis | Diagnosis Wear Type |
System Integration & Maintenance
Integrating a condition monitoring system involves sensor installation, data acquisition device deployment, communication network setup, and cloud platform configuration. Sensor calibration is performed monthly with a deviation tolerance of ≤±5%, and a comprehensive system inspection is conducted annually. Data analysis covers vibration trends, temperature patterns, and cumulative fatigue damage, enabling Predictive Maintenance that detects sensor accuracy drift and mechanical performance attenuation early. Kelude provides full-lifecycle services for its condition monitoring systems.
| maintenance | Period | Content |
|---|---|---|
| sensor calibration | Monthly | Deviation≤±5% |
| Communication | Quarterly | Signal Strength |
| System Inspection | Annual | Full Functionality |
| Data Backup | Monthly | Cloud+Local |
Condition Monitoring FAQs
Q: What are the three main subsystems of a condition monitoring system?
A: The steel structure (main girder stress and vibration), the mechanism (motor, reducer, and brake temperature and vibration), and the electrical system (current, insulation, temperature, and humidity). Dynamic monitoring samples at ≥100 Hz, steady-state at ≥1 Hz. Data is stored for at least 7 days with offline buffering and retransmission, and the system is rated IP65.
Q: What are the online and offline diagnostic methods?
A: Online diagnostics use alarm thresholds and trend analysis—for instance, tracking parameters that increase month over month to detect accelerated wear. Offline diagnostics apply FFT spectrum analysis on vibration data to identify characteristic frequencies of bearing or gear faults, along with oil debris analysis to determine the type and extent of wear.
Q: What are the typical alarm thresholds?
A: Main girder vibration ≤10 mm/s, motor bearing temperature ≥85°C, reducer oil temperature ≥75°C, and insulation resistance ≥1 MΩ. Trend analysis is also used to flag abnormal acceleration in parameters that increase month over month.
Q: What services does Kelude offer?
A: Kelude provides complete condition monitoring system integration, including sensor deployment, data acquisition installation, cloud platform setup, and fault diagnosis analysis.
