**Online Monitoring and Fault Diagnosis System for Rotating Axial Main Fan** Home > Bearing Knowledge > Online Monitoring and Fault Diagnosis System for Rotating Axial Main Fan *728*90 created on 2018/5/16* var cpro_id = "u3440131";

Online Monitoring and Fault Diagnosis System for Rotating Axial Main Fan

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**Introduction** With the continuous advancement of sensing and computer technologies, online monitoring and fault diagnosis systems have made significant progress. To convert these skills into practical productivity and further enhance the automation and intelligence of coal enterprises, a company successfully applied an online monitoring and fault diagnosis system to the counter-rotating axial main fan. This implementation has provided a solid foundation for the informatization and management improvement of the coal enterprise. This paper takes the FJC online monitoring and fault diagnosis system as an example, analyzing the requirements, composition, and operational process of the system for the rotating axial main fan. It also covers its working conditions and performance. **2. Demand Description** **2.1 Utility Requirements** The main ventilator in coal mines is one of the four key pieces of equipment. Operating continuously 24 hours a day, it acts as the mine's "respiratory system." As a critical safety production device, any failure could pose a serious threat to the entire mine. Therefore, the online monitoring and fault diagnosis system must be highly reliable, ensuring that even if the system fails, it does not affect the normal operation of the main fan. Since the counter-rotating main fan is driven by two motors, their parameters must be sampled separately. According to the "Coal Mine Safety Regulations," the main ventilation fan must have two sets of equal capacity primary ventilation units, with one serving as a backup. To reduce user investment, the system can switch between the two fans for monitoring. Additionally, the system includes five functions: online assistance, condition monitoring, defect diagnosis, machine balancing, and material search. It supports both real-time and manual monitoring, recording air volume, pressure, power, speed, vibration, motor power, winding temperature, bearing temperature, and inlet and outlet gas temperatures. It generates intuitive visualizations such as signal maps, pressure-volume curves, and data tables. The system can automatically alarm before faults occur (e.g., bearing damage or blade deformation) and intelligently identify the nature and location of the issue. To ensure ease of use, the software operates on a standard Windows platform. **2.2 Technical Function Indicators and Parameters** (1) Input from sensors, output with 4-digit precision (2) Error rate per channel ≤ 2% (3) Microcomputer screen misinterpretation rate: 1/10,000 (4) Software reliability: No crashes under long-term operation; anti-interference and self-recovery features (5) Accurate measurement and printing of bearing temperature, winding temperature, pressure, airflow, power, and vibration curves; maximum error ≤ 2% (6) Power supply: AC 220V ± 5%, 43–67 Hz (7) Operating temperature: -40°C to 180°C (8) Steady-state analysis: Time domain waveform, axial orbit, precession, spectrum, and low-frequency refinement (9) Transient analysis: Speed Bode diagram, harmonic analysis, and process maps (10) Trend analysis: Oscillation trend, precession trend, harmonic oscillation trend, and real-time monitoring of key features such as total amplitude, time domain waveform, harmonic differences, axis orbit, momentum, and more. Based on these features, engineers can accurately assess the machine condition and identify issues like rotor imbalance, shaft cracks, rotor-stator contact, hot twisting, blade loss, misalignment, instability, and surge. **3. Composition of the Online Monitoring and Fault Diagnosis System** The FJC system includes industrial computers (with software), control cabinets, pressure devices, vibration equipment, transmission units, and auxiliary components. The system is divided into three levels: sensor level, data collection, and signal analysis. It ensures real-time monitoring and intelligent fault diagnosis. The system operates in two modes: active monitoring (for normal conditions) and secondary monitoring (for adjustment or repair). Data is collected simultaneously from multiple signals and stored for analysis. Calculated values are displayed, recorded, and visualized for further review. The real-time monitoring subsystem compares measured values with thresholds to determine whether the machine is operating normally, positively, or abnormally. If abnormal, it triggers an alarm. Fault diagnosis uses the system’s layout and operational characteristics to analyze spectral and time-domain data. Peaks are identified, and characteristic parameters are compared against thresholds to detect fault locations, causes, and types. Manual peak detection is also available for complex cases. **4. Machine Balancing** When balancing is required, the system collects axial pulse and vibration signals, filters them, extracts transition frequencies, and performs phase and amplitude analysis to calculate balance quality and orientation. **5. Working Conditions** The system has been tested with a set of explosion-proof counter-rotating axial fans for 1–2 years, proving stable and easy to use. It allows personnel to monitor the main fan’s condition, adjust parameters, and operate efficiently, reducing costs and improving economic benefits. **6. Conclusion** The FJC online monitoring and fault diagnosis system meets the needs of coal mine axial flow main fans, enhances automation and intelligence, and supports the informatization of coal companies. Its early warning function improves system reliability and ensures safe ventilation operations.

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