GB/T 36468.1-2018 Crane Condition Monitoring Guide
Standard Core RequirementsGB/T 36468.1-2018, "Cranes — Condition Monitoring — Part 1: General Principles," serves as the governing document for the crane condition monitoring standard series. It defines the overall system architecture, selection of monitoring parameters, sensor configuration schemes, data acquisition and analysis methods, as well as evaluation criteria for monitoring systems. The standard applies to the design and implementation of condition monitoring systems across various crane types, including bridge cranes, gantry cranes, tower cranes, and mobile cranes. Its core value lies in guiding crane operators to establish a scientific predictive maintenance framework—by monitoring critical parameters in real time, the standard enables a shift from reactive "breakdown maintenance" to proactive "predictive maintenance," significantly reducing the risk of unplanned downtime.
GB/T 36468.1-2018 is Part 1 (General Principles) of the crane condition monitoring standard series, specifying system composition, monitoring parameters, and evaluation methods. Condition monitoring technology forms the foundation for predictive maintenance and intelligent crane management. By collecting operational data in real time through sensors and applying data analysis algorithms to assess equipment health, potential faults can be detected before they occur—dramatically cutting unplanned downtime and maintenance costs. This standard was proposed by the China Machinery Industry Federation and is under the jurisdiction of the National Technical Committee for Standardization of Lifting Appliances. It serves as the key reference standard for the intelligent upgrade of cranes.
System Architecture for Condition Monitoring
GB/T 36468.1-2018 defines the overall architecture of a crane condition monitoring system, which consists of five layers: the sensor layer, data acquisition layer, data transmission layer, data processing and analysis layer, and human-machine interface layer. The sensor layer is responsible for sensing physical quantities such as vibration, temperature, stress, and displacement on the crane. Common sensors include accelerometers, temperature sensors, strain gauges, encoders, and laser distance sensors. The data acquisition layer conditions, filters, and digitizes sensor signals, with sampling rates ranging from 10 Hz to 10 kHz depending on the monitored component.
The data transmission layer delivers collected data to the processing center via industrial Ethernet, wireless networks, or fieldbus. The standard recommends a redundant communication architecture to ensure reliable data transmission. The data processing and analysis layer forms the core of the system, incorporating algorithms for signal processing, feature extraction, condition identification, and trend prediction. The human-machine interface layer presents equipment status, alarms, and trend reports through graphical dashboards accessible from both mobile terminals and PCs. Kelude Heavy Industry's CMS condition monitoring system strictly follows the architectural design of GB/T 36468.1-2018, employing a three-tier distributed architecture that supports remote real-time monitoring and historical data analysis of crane operations. The system has been successfully deployed in multiple intelligent overhead crane projects.
Monitoring Parameters and Sensor Selection
The standard provides a detailed breakdown of key monitoring parameters and their corresponding sensor selection guidelines. For structural component monitoring, the focus is on main girder mid-span deflection (measured with draw-wire displacement sensors or laser rangefinders), stress at critical weld seams (using resistance strain gauges with a sensitivity of no less than 2.0 mV/V), and structural vibration acceleration (using piezoelectric accelerometers with a frequency response of 0.5 Hz to 1 kHz). For hoisting mechanism monitoring, the standard requires tracking reducer gear vibration acceleration, gearbox oil temperature, motor current, brake status, and wire rope tension.
The standard also specifies sensor installation positions, quantities, and protection rating requirements. For example, vibration sensors on the reducer should be mounted at the bearing housings of both the input shaft and output shaft, with at least two accelerometers per reducer (one horizontal and one vertical). Sensors must have a protection rating of no less than IP65, and those installed in high-temperature zones must withstand temperatures above 85°C. Cable connections should use aviation plugs or waterproof connectors, and signal cables must be shielded twisted pair to minimize electromagnetic interference. Kelude Heavy Industry's condition monitoring system comes with a standard sensor package comprising 8 to 16 vibration sensors, 4 to 8 temperature sensors, and 2 to 4 displacement sensors, with sensor layout schemes customizable based on the specific crane type (gantry or bridge) and working environment.
Data Analysis and Fault Diagnosis
Data analysis and fault diagnosis are central to GB/T 36468.1-2018. The standard recommends a combined approach using time domain analysis, frequency domain analysis, and time-frequency domain analysis. Time domain analysis involves calculating statistical features such as root mean square (RMS), crest factor, and kurtosis. Trends in RMS values reflect the overall vibration energy level of the equipment. Frequency domain analysis employs the Fast Fourier Transform (FFT) to convert time-domain signals into spectra, enabling fault localization by identifying gear meshing frequencies and bearing fault characteristic frequencies.
The standard establishes a four-level early warning mechanism: Level 1 (Attention)—parameters show slight deviation, operators are notified to monitor closely; Level 2 (Warning)—parameters show noticeable changes, scheduled shutdown for inspection is recommended; Level 3 (Danger)—parameters approach limit values, immediate shutdown is required; Level 4 (Emergency)—parameters exceed limit values, emergency shutdown must be initiated immediately. For diagnostic algorithms, the standard recommends combining threshold comparison, trend analysis, and machine learning classification methods to comprehensively assess equipment health. Kelude Heavy Industry's CMS system incorporates a deep learning-based fault diagnostic model specifically trained on common crane fault modes—including reducer gear pitting, bearing wear, wire rope wire breaks, and main girder fatigue cracks—achieving a diagnostic accuracy of over 95%.
System Integration and Communication
GB/T 36468.1-2018 sets clear requirements for system integration and communication. The condition monitoring system must integrate seamlessly with the crane's PLC control system, exchanging data through industrial communication protocols such as OPC UA, Modbus TCP, or Profinet. The standard recommends a hybrid network architecture combining an Ethernet backbone with wireless sensor networks—the backbone covers the entire plant area, while wireless networks cover the crane itself. Communication protocols must support real-time data transmission (latency not exceeding 100 ms) as well as batch transfer of historical data (latency acceptable up to a few seconds).
Regarding system integration, the standard requires the condition monitoring system to connect with the enterprise's MES (Manufacturing Execution System) or EAM (Enterprise Asset Management) platform, enabling coordination between equipment status and production planning. Monitoring data should support long-term storage in industrial databases such as Trend or Historian, with a minimum retention period of three years. The standard also specifies basic cybersecurity requirements, including access control, encrypted data transmission, and operation log auditing. Kelude Heavy Industry's condition monitoring system features a dual-platform architecture for both web and mobile access, allowing operators to receive equipment alerts and process work orders directly via WeChat or DingTalk on mobile terminals—a digital upgrade that streamlines crane operation and maintenance management.
Implementation and Maintenance
The implementation and maintenance section of the standard outlines the deployment process and operational requirements for crane condition monitoring systems. The implementation process includes: preliminary investigation (equipment records, operating environment, and monitoring needs analysis) → solution design (measurement point layout, sensor selection, and system architecture confirmation) → equipment installation (sensor mounting, cable routing, and data acquisition device commissioning) → system commissioning (communication testing, parameter calibration, and alarm threshold configuration) → trial run (continuous operation for at least 30 days to verify system stability) → final handover.
For system maintenance, the standard recommends quarterly calibration checks for sensors, with a maximum calibration interval of 12 months. Maintenance of data acquisition equipment includes periodic inspection of power supply modules, data backup, and storage space cleanup. Alarm thresholds should be reviewed and optimized regularly based on accumulated operational data, typically every six months. The standard also emphasizes that condition monitoring systems must be equipped with fault self-diagnosis capabilities, automatically generating alerts when sensors or acquisition modules malfunction. Kelude Heavy Industry provides a 3-year warranty period and remote operation & maintenance services with every condition monitoring system. Customers can access system health reports, view sensor offline alerts, and receive periodic maintenance reminders through a dedicated mobile app.
Kelude Heavy Industry holds multiple patented technologies and extensive project experience in the crane condition monitoring field, having deployed GB/T 36468.1-2018-compliant monitoring systems for customers across various industries. Through these systems, clients have transitioned from scheduled maintenance to condition-based maintenance, achieving a 35% or greater improvement in mean time between failures (MTBF) and a 20% to 30% reduction in annual maintenance costs. When selecting a condition monitoring system, it is recommended to prioritize suppliers that provide a declaration of conformity to the standard, demonstrate proven project track records, and offer robust after-sales service capabilities.
Monitoring Parameters
- Structural vibration acceleration
- Critical weld seam stress
- Main girder deflection
- Reducer temperature/vibration
Sensor Configuration
- Accelerometer IP65
- Temperature Sensor PT100
- Strain gauge with sensitivity ≥ 2 mV/V
- Laser displacement sensor
Data Analysis
- Time domain analysis: RMS / crest factor
- Frequency domain analysis: FFT spectrum
- Trend analysis / threshold comparison
- Machine learning-based fault diagnosis
Early Warning Grading
- Level 1: Caution (minor deviation)
- Level 2: Warning (noticeable change)
- Level 3: Danger (approaching limit)
- Level 4: Emergency (exceeded limit – shutdown)
Communication
- OPC UA / Modbus TCP
- Industrial Ethernet backbone
- Real-time latency ≤ 100 ms
- Data retention ≥ 3 years
Implementation Process
- Preliminary survey + solution design
- Equipment installation + system commissioning
- 30-day trial run for validation
- Official handover + periodic maintenance
Frequently Asked Questions
Q: What components typically make up a crane condition monitoring system?
A: Per GB/T 36468.1-2018, a crane condition monitoring system consists of five core layers. The first is the sensor layer, which includes vibration accelerometers, temperature sensors, strain gauges, displacement sensors, and current sensors that directly capture the equipment's physical state. The second is the data acquisition layer, responsible for signal amplification, filtering, and analog-to-digital conversion, typically using 16-bit or higher ADCs with sampling frequencies ranging from 10 Hz to 10 kHz depending on the parameter type. The third is the data transmission layer, which relays data to the processing center via industrial Ethernet, wireless Wi-Fi, or 4G/5G networks. The fourth is the data processing and analysis layer, where signal processing algorithms, feature extraction, and fault diagnosis models are deployed. The fifth is the human-machine interface layer, which presents status information and early warnings through web dashboards, mobile apps, or industrial control panels. Kelude's CMS integrates all five layers into a single platform, allowing users to manage everything from sensor configuration to diagnostic report generation in one system.
Q: How does condition monitoring differ from periodic inspection? Can it replace inspection?
A: Condition monitoring and periodic inspection are fundamentally different and cannot substitute for one another. Periodic inspection is a statutory requirement under national special equipment safety technical regulations (such as TSG Q7015-2016), carrying legal enforceability and standardized inspection items. It must be performed by qualified third-party inspection bodies and is a mandatory prerequisite for the legal operation of special equipment. Condition monitoring, by contrast, is a voluntary technical management practice adopted by enterprises. It uses sensors and data analytics to track equipment health in real time, with the goal of optimizing maintenance strategies and reducing failure risks. While condition monitoring can flag potential issues early and help prioritize inspection focus areas, it cannot replace legally mandated comprehensive periodic inspections. The ideal relationship is complementary—condition monitoring supports day-to-day operational decisions, while periodic inspection ensures regulatory compliance.
Q: What are the key parameters monitored in a condition monitoring system?
A: Based on the recommendations in GB/T 36468.1-2018, key crane condition monitoring parameters fall into four categories. Structural parameters: mid-span deflection of the main girder, stress at critical weld seams, structural vibration acceleration, and outrigger leg verticality. Hoisting mechanism parameters: gearbox vibration acceleration (both horizontal and vertical), gearbox oil temperature (normal limit 75°C, alarm at 85°C), motor three-phase current (alarm when balance deviation exceeds 10%), brake clearance (characteristic value 0.5–1.0 mm), and wire rope tension variations. Travel mechanism parameters: crane bridge and trolley travel motor current and rotational speed, crane rail irregularities, and crane wheel wear amount. Environmental parameters: wind speed (alarm for outdoor gantry cranes above 12 m/s), ambient temperature, and humidity.
Q: How are alarm thresholds set in a condition monitoring system?
A: Setting alarm thresholds correctly is critical to the effective operation of a condition monitoring system. GB/T 36468.1-2018 recommends a three-stage approach. Stage one (initial commissioning): set initial thresholds based on international standards such as ISO 10816 and manufacturer factory data, typically using 70% of the standard recommended value as the starting point. Stage two (break-in period, after 1–3 months of operation): calculate statistical thresholds using the mean ± 3 standard deviations from actual operating data, with differentiated thresholds for different operating conditions (no-load, light load, full load). Stage three (steady-state operation, after 6 months): leverage historical lifecycle data and apply machine learning methods to dynamically adjust thresholds. Kelude's CMS supports both automatic threshold learning and manual fine-tuning modes, ensuring an optimal balance between alarm sensitivity and false alarm rate.
