SICK W9 PHOTOELECTRIC SENSOR

Product Description

The SICK WL9G-3N2432 is a compact, high-performance photoelectric retro-reflective sensor designed for reliable object detection in industrial automation systems. It uses visible red light and advanced autocollimation optics to detect objects, including transparent materials, with high precision. With a maximum sensing range of 5 m and a standard operating range of up to 3 m, it is suitable for a wide variety of industrial applications.

Equipped with a PinPoint LED light source, the sensor provides a clearly visible light spot for convenient alignment and accurate detection. Its integrated teach-in button simplifies adjustment, while AutoAdapt technology helps maintain reliable switching performance under changing operating conditions. The sensor features an NPN switching output with complementary output functions and light-on/dark-on switching modes, allowing flexible integration into automation control systems.

The compact rectangular housing measures just 12.2 × 50 × 23.6 mm, making it suitable for installations where space is limited. Its robust construction, fast response time and reliable optical performance make the WL9G-3N2432 an excellent choice for packaging machinery, conveyor systems, production lines and automated material handling.

Technical Specifications

Parameter Specification

Manufacturer SICK

Product Series W9

Model Number WL9G-3N2432

Part Number 1054152

Sensor Type Photoelectric retro-reflective

Maximum Sensing Range 5 m

Standard Sensing Range 0–3 m

Light Source PinPoint LED

Light Type Visible red light

Wavelength 650 nm

Supply Voltage 10–30 V DC

Switching Output NPN

Output Function Complementary

Switching Mode Light-on / Dark-on

Response Time Less than 0.5 ms

Switching Frequency 1,000 Hz

Connection M12, 4-pin male connector

Adjustment Single teach-in button

Housing Dimensions 12.2 × 50 × 23.6 mm

Mounting M3 mounting holes

Operating Temperature −40°C to +60°C

Protection Rating IP66, IP67, IP69K

Special Feature Transparent object detection