3D texture data can look like a solid, continuous surface. But in reality, there’s space between the measured pixels, and some of those pixels may not have been measured at all.
Missing Data Fill is a pre-processing step that bridges those bad pixels, making data easier to interpret. But sometimes looking at the Raw data, before data fill, can be instructive as well.
In this 60-Second Surface Analysis video we look at how Missing Data Fill can smooth out missing pixels in surface roughness data. We also look at how you can use the Raw data view to check whether that missing data is a concern, or not.Read More
When we look at surface texture data from a measurement system, we have to consider whether the features we are seeing are real, or whether they might be noise or bad pixels.
In this 60-Second Surface Analysis video we show how you can zoom in on a feature in OmniSurf3D software to see just how many actual measurement points we have for a feature. It’s a very useful tool, and a great sanity check.Read More
Custom software tools, or “helper applications,” can pick up where off-the-shelf instrument software leaves off, filling in features that are absent from native software. In this post we look at how a helper application can add custom parameters, analyses, and displays to native software, to optimize your measurement process.Read More
Join us at the Engine Performance EXPO 2024, January 11-12! Digital Metrology's Mark Malburg will be participating in a number of presentations and round table discussions with some of racing's biggest technology experts. Join the excitement online or in person.
see below for a schedule of talks and panels—hope you can join us for some very interesting discussions!Read More
Where's the wear on the porous surface on the left? There IS a wear scar at the center, but it’s nearly impossible to see within all that porosity. In this joint post with Michigan Metrology, we show how to use a series of "closing" and "opening" filters to isolate features like this wear scar so that we can analyze their volume, depth, etc.Read More
The last time you saw a zebra: was it black with white stripes, or white with black stripes? In this Notepad series we show how “stripes” of light and dark in surface texture can be an indicator of wear. The spacing of those stripes will depend on the surface geometry—and we’ll show you how do tell whether those stripes are due to changes in the longer wavelength waviness or shorter wavelength roughness.Read More
Join us at NCSLI's Technical Exchange for a session on the metrology of surface measurement (2D and 3D) and the many traps that people can fall into. We'll use case studies and actual surface data to explore the analysis essentials (geometries, filtering, and parameterization) to turn complex shapes into more manageable numbers.Read More
Will you be attending the upcoming PRI (Performance Racing Industry) expo in Indianapolis?
At PRI, the panel of Mark Malburg (Digital Metrology), Ed Kiebler (Rottler Manufacturing) and Keith Jones (Total Seal Piston Rings) will dive into the topic of surface finishes for racing applications. These panel discussions will take place at the Rottler Manufacturing booth #5129. Dates and times for the panel discussions are shown below. Use the QR codes to register for the individual sessions!
Measuring the surface texture of this O-ring presents a challenge. With a small radius and cross-section, steep sides, and soft material, it’s almost impossible to measure with a stylus. An optical instrument can do the job...but that's just the first hurdle! In this Surface Notes blog post we show you how to use the Geometry Removal and Filtering tools in OmniSurf3D to measure this complex shape. You can try it for yourself as well—the dataset is available in our Surface Library!Read More
"Can I trust my measurement?" That question drives us to produce meaningful measurement results. In this post we examine how dirt and debris can produce artificial "features" in surface texture data—errors that are sometimes the exact opposite of what you might expect to find. And those errors may have you chasing down changes in your process that aren't really there. We'll show you what to look for, and some steps you can take to tell whether features are real or not.Read More