Everything You Always Wanted to Know About 3D Scanning – Data Collection

3D Scanning Data Collection

Now that you have a basic idea about how 3D scanning and modelling work, let’s really get started. Before you can have a 3D model, you must have 3D data to create that model. Let’s start there…

So, what are the ways that 3D data can be collected?

There are multiple ways to collect 3D data but two of the most common methods (and the two most frequently used by ASTCAD) are laser scanning and digitizing.

During laser scanning, a laser line is passed over the surface of an object in order to record three-dimensional information. The surface data is captured by a camera sensor mounted in the laser scanner which records accurate dense 3D points in space, allowing for very accurate data without ever touching the object.

Laser scanners can be broken down further into types such as laser line, patch, and spherical. The FARO ScanArm, the FARO LS, the Surphaser, Konica Minolta Vivid 9i and Range 7 are some examples of laser scanners that we often use at Direct Dimensions.

3D Scanning Data Collection

The second major method is digitizing, which is a contact-based form of 3D data collection. This is generally done by touching a probe to various points on the surface of the object to record 3D information. Using a point or ball probe allows the user to collect individual 3D data points of an object in space rather than large swathes of points at a time, like laser scanning. This method of data collection is generally more accurate for defining the geometric form of an object rather than organic freeform shapes. Digitizing is especially useful for industrial reverse engineering applications when precision is the most important factor. Stationary CMM’s (coordinate measurement machine), portable CMM arms, and the FARO Laser Tracker are all examples of digitizers that we often use at Direct Dimensions.

Other methods of collecting 3D data include white light scanning, CT scanning and photo image-based systems. These technologies are being utilized more frequently in the field of 3D scanning and new applications are being discovered every day.

To be digitized or laser scanned?

A general “rule” is that scanning is better for organic shapes and digitizing is most accurate for geometric shapes. In general, laser scanning is also used for higher-volume work (larger objects like cars, planes, and buildings). Laser scanning is also a great option for people who need 3D data of an object but would prefer that the object not be touched, such as for documentation of important artifacts.

Digitizing is often used for our engineering projects and first article inspections, in instances where precise measurements are required for geometrically-shaped subjects. This includes objects that have defined lines and planes and curved shapes, like spheres and cylinders.

This doesn’t mean that you can never laser scan a part with many geometric features or that you can’t digitize a plane (an entire plane can be digitized, believe us – we’ve done it!) or even a sculpture. These are just rules of thumb.

Utilizing multiple methods of Data Collection

There are projects when it is more cost and time effective to use multiple methods of data collection. A good example is a cast part with geometric machined features. You might need a 3D model of the entire part but really need incredible accuracy on the machined features while the freeform cast surface itself is not as important. In such a case it can be much more effective to laser scan the entire part and then digitize the geometric features. The data can be combined during the modelling phase (more on that in the following chapters).

Additional Scanning Information

Because you are trying to collect the most accurate data possible, there are a few more things to keep in mind before you run out and start scanning everything in sight.

  • Bright light sources in the area, including the sun, can really mess up your scan data. At Direct Dimensions, if we are laser scanning an object outdoors we prefer to do it at night if able. Light can reflect off of your scanning object and create “noisy” data. This brings us to:
  • Very reflective materials generally do not scan well. This can be avoided with a light coating of white powder spray (or anything that dulls the reflectivity). There are also some scanner manufacturers who are actively working to solve this problem.
  • Fixturing: whether you are laser scanning or digitizing, it important that your scan object will not move while you are collecting data. The tiniest motion will cause inaccurate data.
  • If you need hard to reach/impossible to see internal data, you should consider CT scanning or destructive slicing, both can be great ways to augment your data. (more on those later).

Moving on to 3D modelling

Now that you have a good idea of what you need to collect data, you are ready to learn all about the various ways the data can be modelled. Chapters three through five will cover, 3D Modeling, Reverse Engineering, and Inspection Analysis.

Contact Australian Design & Drafting Services for more information.

What are the methods of data collection?

Data collection methods vary depending on the type of data being collected, the research objectives, and the resources available. Here are some common methods:
Surveys and Questionnaires: Surveys involve asking a series of questions to a sample of respondents. They can be conducted through paper forms, online platforms, telephone interviews, or face-to-face interviews.
Interviews: Interviews involve direct interaction between the researcher and the respondent. They can be structured (with a predetermined set of questions), semi-structured (with some flexibility in questioning), or unstructured (open-ended discussions).
Observation: This method involves systematically observing and recording behaviors, events, or activities as they occur in their natural setting. Observations can be participant (the researcher actively participates) or non-participant (the researcher remains separate from the activity).
Experiments: Experiments involve manipulating one or more variables to observe the effect on another variable. They are often conducted in controlled environments to establish cause-and-effect relationships.
Secondary Data Analysis: Researchers analyze data that were collected by others for a different purpose. This can include sources like government statistics, organizational records, or previously conducted research.
Focus Groups: Focus groups involve bringing together a small group of individuals to discuss a specific topic guided by a moderator. This method allows for in-depth exploration of attitudes, opinions, and perceptions.
Document Analysis: Researchers analyze documents such as texts, reports, articles, and historical records to extract relevant information.
Ethnography: Ethnographic research involves immersing oneself in the culture or context being studied to gain a deep understanding of the behaviors, beliefs, and social dynamics.
Diaries and Logs: Participants record their activities, thoughts, or experiences over a specified period, providing insights into their daily lives or specific events.
Social Media Monitoring: Researchers analyze data from social media platforms to understand trends, opinions, and behaviors of individuals or groups.

What is data collection format?

The data collection format refers to the structure or template used to gather and organize data during the data collection process. The format outlines how data will be collected, recorded, and stored, ensuring consistency and accuracy. Depending on the research methodology and objectives, data collection formats can vary widely. Here are some common formats:

Structured Surveys and Questionnaires: These formats consist of predefined questions with fixed response options. Respondents are typically asked to select their answers from multiple-choice options, Likert scales, or yes/no responses. Structured formats are efficient for collecting quantitative data and facilitating analysis.

Semi-Structured Interviews: In semi-structured interviews, researchers have a predetermined set of questions but also allow flexibility for probing and exploring topics in more depth. The format provides a balance between standardization and flexibility, allowing for richer qualitative data collection.

Unstructured Interviews: Unstructured interviews have no predetermined set of questions, allowing for open-ended discussions and free-flowing conversation. Researchers rely on active listening and follow-up inquiries to delve into topics of interest. Unstructured formats are suitable for exploratory research or when a deep understanding of participants’ perspectives is desired.

Observation Protocols: Observation protocols outline the specific behaviors, events, or phenomena to be observed and recorded during observational studies. They include guidelines for documenting observations, such as timestamps, descriptions, and contextual details. Observation protocols ensure consistency and objectivity in data collection.

Experimental Designs: Experimental formats include protocols for manipulating independent variables, measuring dependent variables, and controlling extraneous variables during experimental research. They specify procedures for randomization, treatment administration, data collection, and statistical analysis.

Focus Group Guides: Focus group guides outline the topics, questions, and discussion prompts to be covered during focus group sessions. They structure the flow of the discussion and ensure that all relevant issues are addressed. Focus group guides may include opening questions, transition points, and closing reflections.

Data Collection Instruments: Data collection instruments encompass various tools and materials used to collect data, such as surveys, questionnaires, interview guides, observation forms, checklists, and rating scales. They may include instructions for administration, response options, and data recording procedures.

Digital Data Collection Tools: With advancements in technology, digital data collection formats have become increasingly common. These include online surveys, mobile data collection apps, electronic diaries, and sensor-based data collection systems. Digital formats offer advantages such as real-time data capture, automated data processing, and remote data collection capabilities.

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