Optical Window Sensors

Optical window sensors are utilized where reliable part counting is needed. This type of sensor technology is based on an array of LEDs on one side, opposite an array of phototransistors on the other side. This array covers the whole area of the window’s opening with an evenly as possible distribution of light. The more evenly distributed the light is throughout the window, the higher the resolution.

Optical window sensors are usually assigned a particular term to reveal their specific functionality type. The two typical functionality types for an optical window sensor are either static or dynamic. The differences between the two functionality types are briefly outlined here.

Static functionality looks for unchanging events. In the case for an optical window sensor, static means it detects the percentage of signal blocked by an object present in or passing through the window. Dynamic functionality looks for changing events. In the case for an optical window sensor, dynamic means it detects moving objects in the window and ignores non-moving objects. Still, in either case whether static or dynamic, the sensor detects objects as they pass through the window.

A common follow-up question is: what are the pros and cons for using either functionality over the other? This is a good question, because there are definite benefits and disadvantages to both approaches. A few of these benefits and disadvantages are briefly outlined below.

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Asset Tracking – Top 10

The goal of plant-based asset tracking is to reduce non-productive time and asset losses, while increasing overall productivity and utilization by accurately tracking assets. Bar code and RFID technologies track changes to an asset’s location, condition, conformity status, and availability.

Balluff has been in this business for over 25 years. Based on that experience, we have compiled the top 10 list of commonly tracked plant-based assets:

1. Dunnage containers
2. Machine tools
3. Plant-floor Equipment
4. Stamping dies
5. Torque Wrenches
6. Plastic Molds
7. Storage tanks and vessels
8. IT equipment
9. Automated Guided Vehicle (AGV)
10. Modular automation sub-systems

If you are looking to gain tighter control of your assets, visit www.balluff.us/traceability

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Error-proofing in Window Mode – Ultrasonic Sensing

In my previous post, I talked about Ultrasonic Sensors utilizing reflected mode. Window mode is an extension of the reflective mode setting. When the sensor is set up in window mode the sensor is only activated when the object target is located within the detection limit setting defined within the detection range of the sensor. So, for example a sensor that has 65…350mm operating range could be set up to see a target within 100…150mm. This mode is commonly used when target sizes require wider tolerances or size such as detecting tall to short targets or simply detecting the correct size of the target. Additionally, if the sensor selected offers an Analog output you can receive output within the new defined window.

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RFID – It’s Not a Matter of Privacy

With the recent boom in RFID implementations by organizations all over the globe, there is a buzz in the on-line communities and social networking sites about how the technology is an attempt to invade the privacy of every “Jane and Joe” on the planet. I have to admit when I first started to come across these public concerns I just assumed this was the vocal minority being overly paranoid. However, as the technology has progressed into many different areas of our life it has become pretty clear that little has been done to address the concerns of the public. So, I am going to address a few of those concerns here.

Recently, the GM plant in Tonawanda, NY incorporated RFID into their engine production process. They simply attach a Balluff Databolt (a specialized bolt with an RFID tag embedded in it) to every engine before it goes onto the assembly line. As with many manufacturing processes the engine will go to many different stations to be assembled and tested. At each of these stations data from the previous station is read and new data is written to the tag to ensure everything in the process went as planned. When the engine is completed the information written on the tag is uploaded to GM’s database and stored. In addition, the tag is removed, its memory erased and placed on another engine that goes through the same process. The tag DOES NOT stay with the engine. And, even if it did there would be no way to secretly track your vehicle by “pinging” this tag.

The GM example is just one of tens of thousands of applications where RFID is used to ensure quality, manage the production process, and manage product recalls in the manufacturing world. So, what about other applications like in retail where clothing is tracked via RFID or the livestock or pet industry where a small RFID tag is implanted in the animal?

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When to use a Vision Sensor for Error-Proofing Applications

Vision sensors are powerful Poka-Yoke tools ideal for error proofing your process. However, traditional sensors still solve more applications at a much lower cost. So, how do you decide when to jump up to a vision sensor? There are three application categories that require the use of a vision sensor, which include:

  

  1. Parts are not well fixtured: If the part is not contained in a fixture, or there is no opportunity to bring the part into an inspection station that has better tolerance, then a vision system is the best choice.
    Example: parts directly on moving conveyor belt.

    Parts on free conveyor

    Parts on free conveyor

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Meeting the Challenges of Precision Sensing: Very Small Target Displacement

Fundamental application problem: Inductive prox sensor is latching on (or…failing to turn on)

  • The prox sensor gap is set to turn on when the target approaches, but it does not turn off when the target recedes (latching on)
  • The prox gap is opened up until sensor turns off at maximum target approach, but it fails to detect the target upon the next approach cycle
  • The prox sensor gap is set to turn on when the target approaches, but later on the operation becomes intermittent (prox fails to reliably detect the target)

Solution: High-performance miniature inductive prox sensor

Critical sensing performance specifications:

o   Low variation of switch point from sample to sample
o   Tight repeat accuracy of switch point
o   Low temperature drift of switch point
o   Low maximum hysteresis (distance between switch-on to switch-off)

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The Other Retro-Reflective Sensors

Most of the time when we think of Retro-Reflective sensors the first thing that comes to mind is a photoelectric sensor. Photoelectric offerings use a reflector to reflect light from the internally mounted emitter and receiver. Retro photoelectric sensors come in many form factors with light source options such as infrared, red light and laser types.

Ultrasonic sensors are commonly forgotten when reflective sensors are needed in a particular application. Ultrasonic sensors when set up in “Window Mode” are similar to a photoelectric sensor however the ultrasonic sensor can use an existing background as the reflective surface such as a metal plate or a solid background. The sensor simply returns a signal as soon as an object fully covers the reflector. This mode is ideal for detecting difficult targets that photoelectric sensor can have trouble with such as poorly reflective materials

ultrasonicThe example shows an Ultrasonic sensor set up in window mode. The sensor is sending a sound wave to the background (reflector) so a target can be detected when entering the detection area between the sensor and the reflector background.

For more information Ultrasonic sensors, click here.

 

 

 

Improved Feedback for Valve Actuators

Here on SensorTech, we frequently talk about the need for high performance, rugged, reliable position feedback in modern industrial applications. A recent article in Valve Magazine, entitled “The Case for Magnetostrictive” illustrates how linear feedback transducers using non-contact magnetostrictive technology help to improve the performance and reliability of valve actuators used in the petrochemical industry.

It’s worth a read. See a variety of linear feedback transducers here.

Illustration of Magnetostrictive Linear Displacement Transducer (MLDT) inserted into a gun-drilled cylinder.

Illustration of Magnetostrictive Linear Displacement Transducer (MLDT) inserted into a gun-drilled cylinder.

RFID Journal Live…It was all about the “Bolt”

I have to be honest. It didn’t take much to lure me to Orlando following the Arctic winter which haunted pretty much everybody who lives north of Dallas. And, just as I had hoped, the sunshine was in full force and the bonus was Balluff being at center stage thanks to the Databolt and its recent success at GM.

If you missed this year’s edition of RFID Journal Live then you missed an opportunity to hear first-hand about the famous Databolt. Mark Chiappetta, The manufacturing Engineering Superintendent at GM in Tonawanda, explained to conference attendees how technology has improved overall efficiency in the manufacturing process at the plant. Of course, the Databolt was featured in his presentation which was followed by a wave of interest in the Balluff booth. Read the GM Databolt story: http://www.rfidjournal.com/articles/view?11329

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Are all capacitive sensors for liquid level detection created equal?

When standard capacitive sensors are used for liquid level detection in an indirect level detection application, the sensor must be adjusted to the point where it ignores the container wall but reliably detects the capacitance change caused by the changing liquid level. Typically, a standard capacitive sensor can be adjusted to disregard a wall thickness of approximately 4mm. In addition, the dielectric strength of the liquid must be higher than the container wall for reliable level detection.

Capacitive sensors detect any changes in their electrostatic sensing field. This includes not only the liquid itself, but also application-induced influences such as condensation, foaming, temporary or permanent material build-up. High viscosity fluids can cause extensive delays in the accurate point-level detection or cause complete failure due to the inability of a standard capacitive sensor to compensate for material adhering to the container walls.

A perfect capacitive sensor for non-invasive level detection applications would not require any user adjustment after the initial setup process. It would detect the true liquid level of any type of water-based liquid through any non-metallic type of tank wall while automatically compensating for material build-up, condensation, and foam. While ignoring these interferences, the sensors would still detect the relative change in capacitance caused by the liquid but use additional factors to evaluate the validity of the measurement taken before changing state.

These sensors would be fundamentally insensitive to any non-conductive material like plastic or glass up to 10mm thick, which would allow them to be utilized in non-invasive level applications. The enhanced capacitive sensors only limitation is it would require electrically conductive fluid materials with a dipole characteristic such as water to operate properly. This is a great concept but does a sensor like this exist today? The short answer is yes, and it is called SMARTLEVEL!

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