EC: E67 Series Long Range Perfect Prox sensor
Machine and Embedded Control - Discrete sensors: The E67 Series Long Range Perfect Prox sensor is engineered to solve the most difficult photoelectric sensing applications through patented optics technology reliably detecting targets regardless of material color, texture, reflectance, contrast, or surface shape. This is a Control Engineering 2013 Engineers' Choice Awards Honorable Mention.
Control Engineering
The E67 Series Long Range Perfect Prox photoelectric sensor can detect objects that cause trouble for most other sensors up to 8 ft away, while ignoring even highly reflective objects, just outside of the target range.
The E67 Series sensors reliably detect flat black, highly translucent and off-angle targets. A high-performance, long-range background rejection sensor, the E67 Series Long Range Perfect Prox sensors reliably detects targets in range, regardless of variations in color, reflectance, contrast, or surface shape.
The Perfect Prox technology is engineered to provide exceptional background rejection and application problem solving.
http://bit.ly/UobO9p Eaton Corp.
Integrator Guide
| Search the online Automation Integrator Guide |
|
|
|
|
Visit the System Integrators page to view past winners of Control Engineering's System Integrator of the Year Award and learn how to enter the competition. You will also find more information on system integrators and Control System Integrators Association.
Case Study Database
Get more exposure for your case study by uploading it to the Control Engineering case study database, where end-users can identify relevant solutions and explore what the experts are doing to effectively implement a variety of technology and productivity related projects.
These case studies provide examples of how knowledgeable solution providers have used technology, processes and people to create effective and successful implementations in real-world situations. Case studies can be completed by filling out a simple online form where you can outline the project title, abstract, and full story in 1500 words or less; upload photos, videos and a logo.
Click here to visit the Case Study Database and upload your case study.