By combining their laser light process and 2-D vision sensors with integrated LEDs, Pepperl+Fuchs has taken their sensor technology to the next level.
Let’s start at the very beginning. Back in 2011, P+F released their PCV (Position Coded Vision) technology along with their Position Guided Vision line. “Using an advanced industrial 2-D camera, PCV data matrix position system not only guides a carrier along its coded or colored path, it also offers an integral identification solution to initiate starts, stops, and turns and an absolute encoding system capable of positioning the carrier with sub-millimeter precision.”
This brings us to today and the newest product line to incorporate and improve upon those previous sensing methods. Whether you’re looking for high-detail, vision-system-like detection or plug-and-play profile comparisons, the SmartRunner Matcher and SmartRunner Detector have you covered.
Laser Light Technology: A line projected onto an object is detected by a camera at a certain angle with height and width information determined though the triangulation principle.
- Easy installation due to swiveling connections
- Recording of error images for machine diagnostics
- Easy-to-process digital signals, say goodbye to raw data outputs!
- Integrated vision camera allows for easy parameterization via Data Matrix control codes
- SmartRunner sensors come optimized and preconfigured to handle specialized applications right out of the box
- Equipped with deviation mirrors extending the base length, reducing space requirements and compacting the housing – meaning you can install these bad boys in tight spaces!
Designed with the automotive, packaging and machinery industries in mind, the SmartRunner Matcher design is focused on ensuring a smooth production while protecting high-cost products on the manufacturing line. With the addition of the data matrix control codes, raw data is a thing of the past and setting up new parameters for the next application is a piece of cake.
How Does the SmartRunner Matcher Work?
Below you’ll see how the Matcher compares object contour, position, and distance based on the adjustable tolerance:
|“Good” Signal Scenario 1: the Matcher recognizes the previously taught-in reference contour. The gripping process starts.||“Bad” Signal Scenario 3: the deviation is outside the tolerance rage. The gripping process stops.|
|“Good” Signal Scenario 2: the Matcher detects a slight deviation that is still within tolerance range. The gripping process starts.||“Bad” Signal Scenario 4: too long distance between sensor and object. The robot has to be moved before the gripping process can be initiated.|
|“Bad” Signal Scenario 5: detection of an incorrect or defective object. The gripping process stops.|
Here, you can see how the Matcher works by comparing object contour, position, and distance:
|“Good” Signal Scenario 1: The Matcher recognizes the previously taught-in reference contour. The gripping process starts.||“Bad” Signal Scenario 3: The twist is outside the tolerance rage. The gripping process stops.|
|“Good” Signal Scenario 2: The Matcher detects a slight deviation that is still within tolerance range. The gripping process starts.||“Bad” Signal Scenario 4: Too long distance between sensor and object. The robot has to be moved before the gripping process can be initiated.|
|“Bad” Signal Scenario 5: Detection of an incorrect or defective object. The gripping process stops.|
- Protection for sensitive machine parts
- Fast adaptation to new application requirements
- Insensitivity to extraneous light
- High-precision area monitoring down to 0.25 mm thanks to simultaneous object and background laser line evaluation
- Detection of component overlap (even reflective or translucent materials!)
- Detection of objects that are not visible to the camera (e.g. reflecting objects) due to simultaneous evaluation
- A large area of detection – large 180 mm detection field and easy teach-in of new reference contours
- Customizable “regions of interest” (ROI) reducing the potential of false triggers and unnecessary machine downtime
- “Good” Signal Scenario 1: no object interferes with the laser line. Machine operation proceeds as planned.
- “Bad” Signal Scenario 1: the Detector recognizes an object interfering with the laser line. A switching signal causes machine operation to stop.
- “Bad” Signal Scenario 2: a hard to detect object with a mirroring surface interferes with the laser line. Since the detector evaluates both the laser line on the object as well as on the background, the detection results are always plausible. Therefore, a broken background line is shown on the malfunctioning object in the detection area, so that the sensor responds immediately. This parallel evaluation ensures completely reliable processes for the user.
The SmartRunner Detector includes transmitter and receiver in a single housing and can be quickly and easily aligned with natural objects such as a wall. Additional alignment and cabling is no longer necessary.
Visual thinker in a digital spectrum, or in layman’s terms….I make all the visual content for Marshall Wolf Automation 🙂 With a background in video advertisement and film production, I work with MWA’s marketing department to keep our customers reading our blogs and viewing our products.