Inductive Sensor M12 Shielded NO/PNP Cable 2m Axial

Micro Detectors presents this high-quality inductive proximity sensor, a reliable and precise sensing solution for various industrial applications. This M12 sensor is designed for ease of integration and dependable performance.

Key Features and Benefits

• M12 Connector: Compact and widely compatible design for easy installation and integration into existing systems.
• Shielded: Provides superior noise immunity, ensuring accurate sensing even in electrically noisy environments.
• NO/PNP Output: Normally Open (NO) switching configuration with PNP output, offering flexibility in system design and compatibility with various PLCs and controllers.
• 2m Cable Length: Provides ample reach for convenient placement and wiring.
• Axial Sensing: Detects objects directly in line with the sensor's axis, simplifying alignment and installation.

Applications

This versatile inductive sensor is ideal for a wide range of applications, including:

• Automation Systems: Precise object detection in automated production lines and robotic systems.
• Industrial Control: Reliable sensing for various industrial processes and machinery.
• Position Sensing: Accurate detection of object position and presence.
• Level Detection: Monitoring material levels in containers and bins.

Why Choose This Product?

The Micro Detectors Inductive Sensor M12 Shielded NO/PNP Cable 2m Axial offers a combination of quality, reliability, and ease of use. Its compact design, shielded construction, and versatile output make it a superior choice for a variety of industrial sensing needs. Choose this sensor for its robust performance and long-lasting durability.

Technical Specifications

While detailed specifications are not provided here, please refer to the product datasheet for complete technical information.

This description is generated using artificial intelligence (AI) and may differ from the actual product. Common AI errors may include:

• Inaccurate product features: some technical specifications, colors, sizes or other parameters may be inaccurate or omitted.
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• Overly Optimistic Functions: in some cases functions may be provided whose product iš doesnt really have.
• Name or Model Discrepancies: AI may misrepresent the product name or model.

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