Wind Turbine Blade
Ronds' intelligent blade monitoring solution uses intelligent monitoring sensors to collect data such as blade vibration, temperature, and load. It uses intelligent algorithms combined with the operating status of the wind turbine to conduct comprehensive analysis and predict potential blade failures, make early warning analysis of the blades, and achieve blade status assessment and fault diagnosis, providing services for maintenance and management decisions of blade equipment.
Monitoring Challenges
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Failures Are Prone to Occur
The blades are subject to irregular alternating wind loads, which can easily cause surface damage, such as coating peeling, pitting, mild cracks, etc. The blades are also susceptible to lightning strikes and ice coating.
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The Accident Had a Great Impact
Minor damage to the fan over time may cause serious cracks in the blades. In severe cases, the blades may break and the tower may collapse, causing economic losses and safety accidents.
Solution Advantages
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01Improve Lightning Protection Measures
The vibration sensor has passed the 5000V withstand voltage test, and the system has complete lightning protection measures and can withstand 60KA current.
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02Understand Real-Time Status
The system integrates front-end intelligent algorithms to achieve in-depth analysis of vibration signals, and has unique "similarity analysis", "modal analysis" and "peak frequency distribution diagram" maps to understand the real-time operation status of the blades. It supports the cyclic collection and upload of on-site blade monitoring data without missing any abnormal data, intelligent blade alarm at the station, and real-time push of blade status.
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03Accurate and Reliable Monitoring
The integrated solution of optical fiber load + vibration is more accurate and reliable for fault monitoring throughout the life cycle of blades.
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04Efficient Early Warning Analysis
The system stores historical data for a long time and conducts comparative analysis of historical data, analyzes and predicts potential failures of blades, and makes early warning analysis of blades.
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