Sensing arrangement
Compare diffuse reflection from the object, a retro-reflective arrangement with a reflector, or a through-beam emitter and receiver. Choose around access and mounting space.
HERED INDUSTRIAL SENSORS
Photoelectric Sensors
Choose the sensing arrangement around the object, the optical path and the space available for installation.
Optical object detection
Application & selection
Explore diffuse, retro-reflective and through-beam sensing approaches for object detection. The target and installation determine the suitable arrangement.
- Conveyor object detection
- Part presence checks
- Position and counting tasks
What to define before selection
Object and optical path
Share the object size, colour, transparency and surface finish, along with the working distance and background.
Output and operation
Specify the controller input and required output. Define Light-ON or Dark-ON behaviour separately from the electrical output type.
Installation and pairing
Include alignment access, ambient light and contamination. For paired arrangements, identify the emitter, receiver or reflector needed.
Tell us about your application
Share the following details so our team can review your requirements.
- Object size, colour, transparency and surface finish
- Working distance, background and mounting space
- Preferred sensing arrangement and any paired components
- Supply, output, operating mode and connection
Selection questions
Which sensing arrangement should I choose?
Start with the object and installation. Diffuse sensors use light returned by the object; retro-reflective setups use a reflector; through-beam setups use a separate emitter and receiver.
Are the reflector or paired units always included?
Confirm the complete arrangement and the supplied components for the selected model. A sensor description alone does not establish what is included.
What matters when detecting a reflective or transparent object?
Share the actual object and its surface, the background and the available mounting positions. These conditions should be assessed before a model is selected.