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Imaging Radar - 3D imaging system

Detection of hidden objects with radar technology

Radar imaging technology – for efficient, automated, and non-destructive quality control

Quality assurance is a crucial factor for companies. They face the challenge of testing products efficiently, automatically, and without damage. Manufacturing companies must ensure product quality in order to achieve maximum output. This is exactly where radar imaging technology comes in – Balluff's radar-based imaging system is the ideal solution for modern industrial imaging applications and offers maximum quality assurance with a 3D imaging system.

Our RadarImager

Making the invisible visible – with 3D radar imaging for maximum quality assurance

Our imaging radar system uses advanced radar imaging technology to take quality assurance to a whole new level. The industrial 3D imaging system is a powerful example of industrial imaging. It scans a wide variety of packaging and uses radar technology to scan all kinds of “hidden objects” and make anomalies visible. The 3D radar imaging solution translates electromagnetic reflections into images, providing a sophisticated imaging radar system for automated quality control.

With the RadarImager, you can easily check packaging for completeness and product integrity or identify foreign objects—all thanks to a modern 3D imaging system based on radar imaging.


The advantages of the RadarImager

  • Reliably scans all non-conductive materials such as films, cardboard and plastics - thanks to the latest radar imaging technology.
  • Reduces recall costs through fast and precise detection of contaminants and foreign bodies directly in the production process.
  • 3D imaging system automatically detects anomalies based on intelligent image and data evaluation.
  • The radar imaging technology works independently of ambient conditions such as dust, light conditions or humidity - for maximum process reliability.
  • Uses AI-based 3D image analysis for significantly improved quality assurance and reliable inline inspection.

Applications of the RadarImager

Whether for companies in the packaging, pharmaceutical, or food and beverage industries, there are numerous applications for imaging radar technology. This is how you can ensure the quality of your products with the help of modern radar technology.

Application example of radar imaging in the food and beverage sector:

  • Checking the contents of packaging for completeness

  • Detect foreign objects

  • Check packaging for intactness

  • Checking the closures

  • Detect fill levels

Application example of radar imaging in the pharmaceutical industry:

  • Checking the completeness of the packaging incl. package insert

  • Check packaging for integrity

  • Detect foreign objects

AI-based image evaluation with the RadarImager


AI takes image analysis with the RadarImager to a new level by enabling precise, fast and reliable defect detection and significantly improving quality assurance in production. AI-based image evaluation offers decisive advantages for quality assurance in industrial production when using the RadarImager from Balluff:

  • AI-supported algorithms, especially deep learning (DL), enable the effective analysis of complex, multi-layered image data that is difficult to capture using classic methods
  • With 2.5D and 3D DL algorithms, spatial information can be better utilized and deeper patterns and correlations in image data can be recognized - even those that remain hidden to the human eye
  • AI helps to identify anomalies and sources of error faster and more accurately, which significantly shortens the response time in automated quality control
  • Sequential data processing allows image data to be contextually linked and evaluated, enabling potential problems to be identified at an early stage and failures to be avoided

Expertise and advice - how to contact us

Our team of experts is here to help and advise you. If you are unsure which sensor is best suited to your requirements, we will be happy to help you.
Get in touch with us!

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