Sick WTB12-3N2431 Photoelectric Sensor

The Sick WTB12-3N2431 Photoelectric Sensor utilizes a background suppression mechanism to ensure precise detection of objects at distances ranging from 20 mm to 350 mm. Equipped with a visible red LED light source operating at 640 nm, it creates a focused Ø 6 mm light spot at 200 mm, allowing it to distinguish objects clearly without interference from the background. Its compact design, combined with a rectangular metal housing and M12, 4-pin male connector, makes it suitable for installations in tight spaces on industrial lines.

Operating efficiently on a 10–30 V DC power supply with a low current consumption of 45 mA, the WTB12-3N2431 supports NPN output with a complementary switching function. It provides fast signal response with a response time of ≤ 330 µs and a switching frequency of 1,500 Hz, making it ideal for high-speed applications. With its robust build and IP66, IP67, and IP69K protection ratings, this sensor is well-suited for environments exposed to dust, water, and cleaning procedures. Its reliability and long service life make it a trusted choice across sectors like packaging, bottling, material handling, and factory automation.

The Sick WL4S-3F2130 Photoelectric Sensor is often used in compact automation setups where space is limited but high accuracy is essential. It is especially useful in detecting small or lightweight components, such as plastic caps, connectors, or semiconductor parts on fast-moving conveyor systems. Maintenance engineers value it for its ability to detect even slightly misaligned or tilted objects, helping prevent jams and errors in the assembly process.

In training setups and student projects, the WL4S-3F2130 is commonly used to teach the fundamentals of light-based sensing and alignment. Its compact design allows for easy mounting, while its performance characteristics introduce learners to real-world automation challenges like object reflectivity, detection distance, and wiring configurations.

Whether in educational labs or in high-volume production environments, this model consistently proves its value by improving system precision, reducing false positives, and supporting clean, consistent signal outputs that are critical for downstream automation systems.