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| Distance Resolution: | ≤0.1m | Laser Safely Level: | Class 1M | 
|---|---|---|---|
| AmbientLight Resistance: | 100Klux | Beam 2: | 2.05°±0.2° | 
| Repeated Measurement Acuresy: | ±0.2m | Beam 3: | 4.09±0.2° | 
| Beam 1: | 0° | Enclosure Rating: | IP65 | 
Molas CL tower clearance lidar is a type of lidar system that continuously monitors the distance between blade tips in real-time. By alerting the main controller when the blade clearance approaches the critical limit, immediate protective actions such as deceleration or retraction can be implemented. The integration of tower clearance lidar technology onto current units can effectively prevent tower collisions, mitigate power constraints in risky units, and enhance power output.
Implementing tower clearance lidar on upcoming units has the potential to reduce blade expenses and alleviate structural pressure on the units' design. By leveraging this advanced technology, future units can optimize their performance and lower maintenance costs.
| Ambient Light Resistance | 100Klux | 
| Enclosure Rating | IP65 | 
| Measurement Accuracy | ±0.2m | 
| Repeated Measurement Accuracy | ±0.2m | 
| Distance Resolution | ≤0.1m | 
| Laser Safety Level | Class 1M | 
| Beam 3 | 4.09±0.2° | 
| Range of Working Temperature | -40℃~+60℃ | 
| Ranging Method | ToF | 
| Working Acceleration Range | -0.5g~0.5g | 
Single point precise feedback
Single-point precise feedback refers to receiving accurate and specific feedback at a particular point in time or during a specific event. This type of feedback provides detailed information and helps individuals or systems to make improvements or corrections based on the received data.
Threshold detection
Threshold detection involves setting a specific level or limit within a system or process to trigger a response when that threshold is reached or exceeded. This mechanism is commonly used in various fields to monitor and control different parameters, ensuring that certain conditions are met or avoided.
Trend detection
Trend detection is the identification of patterns or trends in data over time. By analyzing historical information, trends can be observed, allowing for predictions or adjustments to be made based on the direction in which the data is heading. This analysis is crucial in decision-making and planning for future actions.
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