The Wind Turbine Health Monitoring Platform collects operational data of wind turbines using various instruments, sensors, etc. After performing edge computing, the data is uploaded to the wind farm server through a gateway. Based on the collected data, the platform analyzes the operational status of the wind turbines, promptly detects warning signs, and takes necessary measures to ensure the safe operation of the turbines.
Traditional wind turbine management is facing numerous challenges and often finds itself in a reactive mode. To address this, it is necessary to install corresponding sensing devices within the wind turbine structural system and utilize online monitoring technologies to achieve real-time sensing of operational conditions and timely warnings of equipment hazards. This assists managers in making informed decisions and issuing appropriate instructions, enabling early detection and prompt mitigation of potential accidents, ensuring the reliable operation of the structure in a consistently good condition.
tracking fault frequencies of major components, and operational status
Configure settings for total vibration value, broadband energy, narrowband energy, time-domain waveform, power spectral density curve, long data acquisition, envelope spectrum parameters, and SFI (Spectral Fatigue Index) parameters.
Settlement, Sway Displacement, Stiffness Circle Analysis
Wind turbine tower sway, tilt, and uneven settlement monitoring system for ensuring tower safety. It provides real-time monitoring of tower tilt angle, sway displacement, and uneven settlement of the tower base.
Diagnostic Analysis: Changes in Natural Frequencies, Imbalance of the Three Blades
Users can analyze turbine blade conditions systematically using various diagnostic tools. These tools detect trends in blade natural frequencies, imbalance, similarity among the three blades, effective values, and frequency amplitude scatter plots.
Integrating sensor tech, signal processing, and computing enables real-time wind turbine monitoring. Data is collected and sent to the control room server for processing and analysis.
Edge computing and deep learning analyze data, generating control commands for wind turbines based on processed results stored in a server.
Multiple warning settings ensure system safety, with notifications available via LAN Web and App, supporting email and SMS alerts.
The Remote Monitoring Center offers fault warning, emergency handling, expert consultation, and on-site diagnostics to promptly address issues until resolved.
Start Free!
Get Free Trail Before You Commit.