VSC523F16.021P-000 B & R Automation

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The VSC523F16.021P-000 is a smart camera from B & R Automation, part of the VS Smart Sensors series. It features a 3.5 MP color resolution, a 4.6 mm F3.5 lens, and supports several vision functions at once. The camera uses a Cortex A9 i.MX6 quad core processor running at 800 MHz, has 4 GB of RAM, and includes an inference accelerator for preprocessing performance.

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Product Description:

The VSC523F16.021P-000 smart camera is built by B&R Automation as part of the VS Smart Sensors series. It combines a lens, lighting, and a quad-core processor in one housing, allowing inline inspection, measurement, and guidance without a separate industrial PC. Its machine-vision platform executes several vision functions at once, helping simplify automation layouts.

Its sensor captures images at 3.5 MP color resolution, keeping fine characters distinct for OCR or code verification. A sustained rate of 43 fps suits medium-speed conveyors and helps maintain stable image acquisition. Processing is handled by a Cortex A9 i.MX6 quad core running at 800 MHz, while 4 GB of onboard RAM stores multiple frames for parallel analysis. This combination supports deterministic cycle times even when classical tools and neural-network inference run together.

Wide-area coverage is provided by a 74° field of view coupled to a 4.6 mm F3.5 lens in an S-mount. Illumination comes from 16 LEDs in four segments, and the white emitters with a wide-beam optic spread light evenly across the target area. An inference accelerator handles preprocessing so quad-core utilization stays low, and a 1 MB L2 cache helps reduce latency. The camera is the deep learning variant, allowing convolutional classifiers to run alongside rule-based algorithms in the same device.

Wake Industrial can arrange same-day shipping for teams that need replacement units. Quotations remain valid for 30 days to simplify budget planning. For part numbers, fault codes, or specification questions, customers may use the chat tool available on the website before ordering.

Angle
74°
Clock Frequency
800 MHz
Focal Length
4.6 mm
Frame Rate
43 fps
Front Glass Type
Glass with anti-reflective coating
Functionality
Several vision functions simultaneously
L2 Cache
1 MB
LED Configuration
16 LEDs (4 segments with 4 one-color LEDs each)
LED Lens Type
LED lens type 1, wide beam
Lens Type
4.6 mm, F3.5 1/1.8"
Lighting Type
White
Line Sensor Suitability
No
Mount
S-mount
Number of Cores
4
Peak Wavelength
Entire visible spectrum
Preprocessing Performance
With inference accelerator
Processor Type
Cortex A9 i.MX6 quad core
Product Group
Smart Camera
Product Range
Integrated machine vision
RAM
4 GB
Resolution
3.5 MP color
Variant Option
Deep learning variant

Frequently Asked Questions about VSC523F16.021P-000:

Q: What is the image resolution of the VSC523F16.021P-000 smart camera?

A: This model has a resolution of 3.5 megapixels and provides color imaging.

Q: What is the angle of view offered by the VSC523F16.021P-000 camera?

A: The angle of view for this smart camera is 74°, allowing wide scene capture.

Q: What type of lighting and LED configuration does the VSC523F16.021P-000 use?

A: The VSC523F16.021P-000 uses 16 white LEDs arranged in four segments with a wide beam LED lens type.

Q: How much RAM does the VSC523F16.021P-000 smart sensor have?

A: This device is equipped with 4 GB of RAM, supporting substantial onboard processing.

Q: What variant option is available for the VSC523F16.021P-000?

A: The VSC523F16.021P-000 features a deep learning variant for advanced vision functions.


Internal Product Review

  • ‘‘The VSC523F16.021P-000 from B & R Automation's VS Smart Sensors line is a smart camera featuring a 3.5 MP color resolution and a 74° angle of view, ideal for integrated machine vision tasks. Powered by a Cortex A9 i.MX6 quad core processor at 800 MHz with a dedicated inference accelerator, this model excels at running several vision functions simultaneously. The deep learning variant and anti-reflective front glass highlight its advanced capabilities for demanding inspection environments.’’

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