Photoelectric Retro-Reflective Sensor M3 Mounting Hole Focus in 100 mm IP66 IP67 IP69K Rated SICK
The Photoelectric Retro-Reflective Sensor WL9L-3P2432S01 is designed for precise object detection in industrial automation
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- Supply voltage: 10 V DC to 30 V DC
- Current consumption: 30 mA
- Switching output: PNP complementary
- Output current max: ≤ 100 mA
- Switching mode: Light/dark switching
- Response time: ≤ 0.5 ms
- Switching frequency: 1000 Hz
- Connection type: Male M12, 4-pin connector
- Protection class: III
- Housing material: Plastic, VISTAL®
- Optics material: Plastic, PMMA
- Operating temperature: -10 °C to +50 °C (extended -30 °C to +55 °C)
- Storage temperature: -30 °C to +70 °C
- Enclosure rating: IP66, IP67, IP69K
- Laser class: 1 (IEC 60825-1 / CDRH 21 CFR 1040.10 & 1040.11)
- Dimensions (H x L x W): 52.2mm x 23.6mm x 12.2mm
- Weight: 0.1 kg
- Photoelectric retro-reflective sensor with autocollimation/coaxial optics
- Visible red laser light source with 650 nm wavelength
- Sensing range up to 12 meters without reflector
- Focus at 100 mm with a light spot size of 0.2 mm
- Single teach-in button for easy adjustment
- High switching frequency of 1000 Hz and response time ≤ 0.5 ms
- IP66, IP67, and IP69K rated enclosure for robust protection
- Polarizing filter and special device features included
- Installation by qualified personnel is recommended to ensure proper setup and compliance with safety standards.
- Industrial automation for object detection
- Small object detection in manufacturing lines
- Use in environments requiring precise laser sensing
- Complies with AS/NZS 3820 – Essential Safety Requirements for Electrical Equipment
- Energy-efficient laser technology reduces power consumption
- Durable IP69K rated housing minimizes environmental impact by extending product life
Standard manufacturer warranty applies; please refer to SICK for specific terms.
The SICK WL9L-3P2432S01 Photoelectric Retro-Reflective Sensor is available for immediate purchase, ideal for industrial automation and precise object detection applications.
