| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Pepperl+Fuchs |
INDUCTIVE SEN 4MM NAMUR |
10 |
|
 |
Woodhead - Molex |
SI600 1MM M4SEMBPNOPUM8P3 |
0 |
|
 |
Panasonic |
SENSOR PROX INDUCTIVE 3.3MM MOD |
1913 |
|
 |
Woodhead - Molex |
SI600 4MM M18NNEMBNNOCPV3W |
0 |
|
 |
Balluff |
DIMENSION= 12 X 70 MM, STYLE=M12 |
19 |
|
 |
Balluff |
DIMENSION= 18 X 83 MM, STYLE=M18 |
145 |
|
 |
Omron Automation & Safety Services |
SENSOR PROX INDUCT 0.8MM CYLIND |
0 |
|
 |
Panasonic |
SENSOR PROX INDUCTIVE 3.3MM MOD |
1 |
|
 |
Woodhead - Molex |
SI700 20MM M18NEMBNNO |
0 |
|
 |
Omron Automation & Safety Services |
SENSOR PROX INDUCTIVE 16MM CYL |
5 |
|
 |
Panasonic |
SENSOR PROX INDUCTIVE 3.3MM MOD |
3732 |
|
 |
Woodhead - Molex |
SI600 8MM M18SEMBNNOCPV4W |
0 |
|
 |
Omron Automation & Safety Services |
SENSOR PROX INDUCT 1.5MM CYLIND |
1180 |
|
 |
Omron Automation & Safety Services |
SENSOR INDUCT 10MM NPN M18 NO |
4 |
|
 |
ifm Efector |
INDUCTIVE SENSOR; M18 X 1 / L = |
0 |
|
 |
ifm Efector |
INDUCTIVE SENSOR; M12 X 1 / L = |
9 |
|
 |
Woodhead - Molex |
SI500 40MM M30NNEMBNNCM12P4 |
0 |
|
 |
Woodhead - Molex |
SI600 8MM M30SEMBNNCCPV3W |
0 |
|
 |
Omron Automation & Safety Services |
SENSOR PROX INDUCTIVE 18MM CYL |
2 |
|
 |
DFRobot |
URM13 ULTRASONIC SENSOR |
2 |
|
Proximity sensors are non-contact detection devices that identify the presence, absence, or distance of objects within a specific range. These sensors convert physical phenomena into electrical signals, enabling automated systems to perceive environmental changes. Their importance in modern technology spans across industrial automation, consumer electronics, automotive safety systems, and smart infrastructure, providing critical data for process optimization and human-machine interaction.
| Type | Functional Characteristics | Application Examples |
|---|---|---|
| Inductive Proximity Sensors | React to metallic objects via electromagnetic fields | Industrial machinery position detection |
| Capacitive Proximity Sensors | Respond to dielectric properties of materials | Level detection in chemical tanks |
| Photoelectric Sensors | Use light beam interruption/reflection principles | Automatic door systems |
| Ultrasonic Sensors | Measure distance via sound wave propagation | Vehicle parking assistance |
| Hall Effect Sensors | Respond to magnetic field variations | Brushless motor commutation |
Typical proximity sensors consist of: - Sensing Element: Converts physical parameters to electrical signals - Signal Conditioning Circuitry: Amplifies and filters raw signals - Enclosure: IP65-IP69K rated housing for environmental protection - Interface Module: Provides analog/digital output interfaces - Power Supply Unit: Regulates operating voltage for internal components
| Parameter | Description | Importance |
|---|---|---|
| Detection Range | Effective operating distance (mm to meters) | Determines application suitability |
| Resolution | Smallest detectable distance change | Impacts measurement precision |
| Response Time | Signal processing speed ( s to ms) | Critical for high-speed operations |
| Environmental Resistance | Temperature, humidity, and vibration tolerance | Ensures operational reliability |
| Output Type | Analog voltage/current or digital interface | System integration compatibility |
| Manufacturer | Representative Product | Key Features |
|---|---|---|
| Omron | E2E-X10DT | 30mm detection range, IP69K rating |
| Keyence | LKG50 | Laser-based 50m range |
| Siemens | 3RG4134 | IO-Link interface support |
| TE Connectivity | KSC1093481 | Automotive-grade reliability |
| ams AG | TCS3701 | Capacitive touch detection |
Key selection criteria include: - Target material properties and detection requirements - Environmental operating conditions - Required detection accuracy and response speed - Interface compatibility with control systems - Mechanical mounting constraints - Total cost of ownership (TCO) considerations Example: For high-precision semiconductor handling, select capacitive sensors with sub-micron resolution and ESD protection.
Emerging trends include: - Miniaturization for IoT device integration - AI-powered adaptive sensing algorithms - Wireless sensor network (WSN) capabilities - Multi-spectral sensing fusion technology - Energy-harvesting self-powered sensors - Enhanced security protocols for industrial applications - MEMS-based micro-sensor arrays - Increased environmental robustness (IP69K, ATEX compliance)