Photoelectric Retro-Reflective Sensor Dual Lens System IP67 & IP69K Rated Variant-3 SICK
The Photoelectric Retro-Reflective Sensor HL18G-N4A3BM features a dual lens system and a visible red light source for precise object detection.
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- Functional principle: Photoelectric retro-reflective with dual lens system
- Sensing range: 0.1 m to 2.5 m (max 3 m)
- Light source: PinPoint LED, wavelength 631 nm
- Supply voltage: 10 V DC to 30 V DC
- Current consumption: ≤ 20 mA
- Switching output: NPN complementary, light/dark switching
- Output current max: ≤ 100 mA
- Response time: ≤ 0.5 ms
- Switching frequency: 1000 Hz
- Connection: Male M12, 4-pin connector
- Protection class: III
- Enclosure rating: IP67, IP69K
- Housing material: Plastic VISTAL®, optics material: PMMA
- Operating temperature: -40°C to +70°C
- EMC compliance: EN 60947-5-2
- Dimensions (H x L x W): 48.5mm x 31.8mm x 16.2mm
- Weight: 0.1 kg
- Photoelectric retro-reflective sensor with dual lens system
- Visible red light with PinPoint LED source
- AutoAdapt signal strength light bar for easy adjustment
- Adjustable on delay from 0 to 2 seconds
- Polarizing filter included to reduce false triggers
- High switching frequency of 1000 Hz
- Robust plastic housing with IP67 and IP69K protection
- Wide operating temperature range from -40°C to +70°C
- Installation by qualified personnel is recommended to ensure proper electrical connections and sensor alignment.
- Industrial automation for object detection
- Detecting transparent objects in manufacturing
- Use in harsh environments requiring IP67/IP69K protection
- Complies with AS/NZS 60950 – Safety of IT and Communication Equipment
- Low power consumption with ≤ 20 mA current draw
- Durable design reduces waste and replacement frequency
- Complies with China-RoHS for hazardous substance restrictions
Standard manufacturer warranty applies; please refer to SICK for specific warranty terms.
The SICK HL18G-N4A3BM Photoelectric Retro-Reflective Sensor is available for immediate purchase, ideal for industrial automation and object detection applications.
