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TS80P (Main) Smart Soldering Iron

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SKU TPX00060 Barcode 6970634010864 Show more
Original price €0
Original price €53,16 - Original price €53,16
Original price
Current price €53,16
€53,16 - €53,16
Current price €53,16
VAT included

TS80P really takes things to the next level!

Overview

TS80P is the upgraded version of TS80 Smart Soldering Iron. TS80P is a smart soldering iron powered by USB Type-C® PD2.0/QC3.0 standard input, which can be powered by charging plugs, power banks and mobile power supplies that comply with PD2.0 (12V 3A)/QC3.0 (9V 2A) standard. Its output power has been increased from 18W to 30W max, with an 8-second heating time at fastest from room temperature to 300℃, meeting a wider range of soldering.

TS80P controller is made of aluminum alloy through CNC into a compact structure and high-tech design, ergonomic, beautiful and fashionable. The controller is also equipped with an OLED screen, so that you can monitor the status of the soldering iron at any time. Moreover, it features a brand new easy-push tip fastener, which provides a best holding experience and an easy push to loosen the soldering tip for quick replacement. With a built-in smart chip, TS80P can smartly control the rise and fall of tip temperature, and features sleep, automatic power-off, safety protection and other modes. The code application layer is open source; you can develop firmware for the soldering iron freely as needed.

TS80P shares the same tips with TS80. The soldering tip has an internal thermal ceramic heating core, and through the pure copper heat conduction, it can quickly transfer heat to the tip of soldering tip, achieving an excellent temperature control performance.

Features:

  • OLED screen, full body CNC aluminum alloy casing
  • USB Type-C 0/QC3.0 standard input
  • Power increased from 18W to 30W max
  • Only 8s to heat from room temperature to 300℃
  • Brand new easy-push tip fastener, one push to loosen tips
  • Builtin smart chip for Port Protection
  • Share same tips with TS80

Tech specs

  • Temperature Range: 100℃- 400℃(Max)
  • Input: 9V 2A (QC 3.0)/ 12V 3A(PD2.0)
  • Power: 30W Max
  • Fastest heating time (from room temperature to 300℃): 8s
  • Data/Power Interface: USB Type-C
  • Temperature stability: ±3%
  • Display: OLED
  • Length: controller: 96mm; tip: 100mm(60+40mm)
  • Weight: 38g (power adaptor not included); Tip: 14g (B02 tip)
  • Certifications: CE, FCC

Conformities

The following Declarations of Conformities have been granted for this board:
CE
For any further information about our certifications please visit docs.arduino.cc/certifications

Get Inspired

PROJECT HUB
Tiny ML in interactive spaces Arduino X K-WAY Challenge Project
Tiny ML in interactive spaces Arduino X K-WAY Challenge Project
Project Tutorial by fullmakeralchemist

An intelligent device to track moves with responses during an interactive space with mapping, backlight, music and smart sculptures. This project makes use of a machine learning algorithm capable of tracking and detecting moves to identify associated gesture recognition through a microcontroller. Smart sculptures, lighting, music and video projection to trigger with each assigned gesture, creating a powerful AV experience highlighting the incredible potential of TinyML for the performing arts. This allows the corresponding media set Tiny ML in interactive to play when the right move was made because all these elements interact to create a new experience. This allows us to create Interactive installations, these sculptures use a combination of motors, sensors, and other electronics to create an immersive and interactive experience for the viewer. They may include projections, sound, and other sensory elements to create a complete experience.

read more
BLOG
These projects from CMU incorporate the Arduino Nano 33 BLE Sense in clever ways
These projects from CMU incorporate the Arduino Nano 33 BLE Sense in clever ways
May 22, 2023

With an array of onboard sensors, Bluetooth® Low Energy connectivity, and the ability to perform edge AI tasks thanks to its nRF52840 SoC, the Arduino Nano 33 BLE Sense is a great choice for a wide variety of embedded applications. Further demonstrating this point, a group of students from the Introduction to Embedded Deep Learning course at Carnegie Mellon University have published the culmination of their studies through 10 excellent projects that each use the Tiny Machine Learning Kit and Edge Impulse ML platform. Wrist-based human activity recognition Traditional human activity tracking has relied on the use of smartwatches and phones to recognize certain exercises based on IMU data. However, few have achieved both continuous and low-power operation, which is why Omkar Savkur, Nicholas Toldalagi, and Kevin Xie explored training an embedded model on combined accelerometer and microphone data to distinguish between handwashing, brushing one’s teeth, and idling. Their project continuously runs inferencing on incoming data and then displays the action on both a screen and via two LEDs. Categorizing trash with sound In some circumstances, such as smart cities or home recycling, knowing what types of materials are being thrown away can provide a valuable datapoint for waste management systems. Students Jacky Wang and Gordonson Yan created their project, called SBTrashCat, to recognize trash types by the sounds they make when being thrown into a bin. Currently, the model can three different kinds, along with background noise and human voices to eliminate false positives. Distributed edge machine learning The abundance of Internet of Things (IoT) devices has meant an explosion of computational power and the amount of data needing to be processed before it can become useful. Because a single low-cost edge device does not possess enough power on its own for some tasks, Jong-Ik Park, Chad Taylor, and Anudeep Bolimera have designed a system where

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