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Benchtop solder fume extractor - 23W

SKU TPX00188 Barcode 7630049204539 Show more
Original price €0
Original price €60,10 - Original price €60,10
Original price
Current price €60,10
€60,10 - €60,10
Current price €60,10
VAT included

Compact and silent benchtop fume extractor for soldering with active carbon filter.

Overview

It eliminates harmful welding fumes, various resins and pyrograph fumes from the workstation. It can be easily adjusted in several positions to ensure optimal smoke extraction.
It comes complete with a filter.

 

*The plug included in this product is a European one.


Tech specs

  • Weight: 1.4 kg Air flow rate: 1 m³ / min
  • Filter: activated carbon
  • Body material: antistatic plastic
  • Power supply voltage: 230 V AC / 50Hz
  • Length: 160 mm
  • Width: 200 mm
  • Height: 270 mm
  • Maximum power: 23W

Get Inspired

PROJECT HUB
Accessing and Displaying the Portenta Vision Shield  - LoRa Image
Accessing and Displaying the Portenta Vision Shield - LoRa Image
Project Tutorial by soothingmist

Begins a process of combining Portenta H7 with Vision Shield – LoRa by acquiring, sending, and displaying a camera image via USB/Serial connection.

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BLOG
This converted RC car uses a Portenta H7 to drive itself
This converted RC car uses a Portenta H7 to drive itself
June 22, 2023

Jeremy Ellis is a teacher, and as such, wanted a longer-term project that his students could do to learn more about microcontrollers and computer vision/machine learning, and what better way is there than a self-driving car. His idea was to take an off-the-shelf RC car which uses DC motors, add an Arduino Portenta H7 as the MCU, and train a model to recognize target objects that it should follow. After selecting the “RC Pro Shredder” as the platform, Ellis implemented a VNH5019 Motor Driver Carrier, a servo motor to steer, and a Portenta H7 + Vision Shield along with a 1.5” OLED module. After 3D printing a small custom frame to hold the components in the correct orientation, nearly 300 images were collected of double-ringed markers on the floor. These samples were then uploaded to Edge Impulse and labeled with bounding boxes before a FOMO-based object detection model was trained. Rather than creating a sketch from scratch, the Portenta community had already developed one that grabs new images, performs inferencing, and then steers the car’s servo accordingly while optionally displaying the processed image on the OLED screen. With some minor testing and adjustments, Ellis and his class had built a total of four autonomous cars that could drive all on their own by following a series of markers on the ground. For more details on the project, check out Ellis' Edge Impulse tutorial here.

read more

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