Working Acceleration Range -0.5g～0.5g Wind power with Class 1M Laser Safely level

Product Description:

Molas CL Tower Clearance Lidar: Molas CL tower clearance lidar is a type of lidar that continuously monitors the clearance distance of blade tips in real-time. It is designed to alert the main controller of the fan unit when the monitored blade clearance approaches the specified minimum value. The main controller can then promptly implement protective measures, such as deceleration and retraction, to ensure the safety of the unit.

Benefits on Existing Units: The installation of tower clearance lidar on existing units helps to prevent tower sweeping incidents, raises the power limit on potentially dangerous units, and boosts power generation capacity. By leveraging this technology, operational efficiency and safety can be significantly improved.

Advantages for Future Units: Implementing tower clearance lidar on future units offers several advantages, including reduced blade costs and decreased design pressures on the units. This innovation could contribute to enhanced performance, lower maintenance expenses, and increased reliability for upcoming facilities.

Features:

• Product Name: Wind Measurement Lidar
• Beam 1: 0°
• Detection Distance: 300m @ 10% reflectivity
• Range of Working Temperature: -40℃ to +60℃
• Working Acceleration Range: -0.5g to 0.5g
• Measurement Accuracy: ±0.2m

Technical Parameters:

Applications:

Single Point Precise Feedback
Single point precise feedback refers to providing specific and detailed feedback on a particular aspect or element. It involves offering clear and targeted information to help individuals improve their performance or outcomes in a focused manner.

Threshold Detection
Threshold detection entails identifying and recognizing certain predefined levels or limits. It involves the ability to detect when a particular value or condition has crossed a specific threshold, prompting a response or action based on this detection.

Trend Detection
Trend detection involves recognizing patterns or tendencies in data or behaviors over time. It focuses on identifying consistent and significant trends that can help in predicting future developments or making informed decisions based on the observed patterns.