FLIR

FLIR, now operating as part of Teledyne FLIR, is a U.S.-based technology company founded in 1978 and recognized as a global leader in thermal imaging, infrared sensing, and advanced perception technologies. The company develops and manufactures thermal cameras, machine vision systems, video analytics platforms, measurement and diagnostic instruments, and security solutions for industrial, commercial, public safety, defense, and infrastructure markets. Its expertise supports applications such as predictive maintenance, condition monitoring, industrial inspection, optical gas imaging, transportation security, and critical infrastructure protection. FLIR’s added value lies in its long-standing innovation in infrared technology, integration of AI-powered analytics, high-performance sensing systems, and industrial-grade reliability that help organizations improve safety, operational efficiency, and asset management. With a worldwide presence, FLIR serves sectors including energy, utilities, manufacturing, oil & gas, transportation, research, defense, and public safety across global markets.
  www.flir.com

New FLIR T865 Joins T-Series Family with Improved Accuracy for Condition Monitoring and Science Applications

FLIR Systems today announced the latest T-Series high-performance thermal camera, the FLIR T865. Built for electrical condition and mechanical equipment inspection, and for use in research and development applications, the T865 provides ±1 °C (±1.6 °F) or ±1% temperature measurement accuracy, a wider temperature range between –40 °C to 120 °C (-40 °F to 248 °F), and more on-camera tools for improved analysis. A free 3-month subscription to FLIR Thermal Studio Pro and FLIR Route Creator, and a 1-month subscription to FLIR Research Studio is included with purchase.

Interfaces for Machine Vision

Choosing the right interface for your machine vision application is a key decision in your camera selection process. The following sections provide an overview of the different types of cables and connectors available for machine vision applications along with associated pros and cons.

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