Save Energy Costs, Improve Efficiency, Maintain Uptime

 

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The automotive industry uses vast amounts of compressed air, which makes timely air leak detection vital for cost and energy efficiency as well as operational continuity.

Enter the acoustic camera, an advanced predictive maintenance solution that scans large areas and pinpoints the exact location of compressed air leaks. Acoustic imagers such as the FLIR Si-Series can be used to find hidden compressed air leaks without shutting down operations. What's more—they can be a key tool for maintaining quality control by detecting miniscule vacuum leaks that could introduce air into engine systems, reducing overall efficiency and potentially causing engine misfires.

 

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With an acoustic camera you can:

  • Proactively Detect Leaks: Identify even the most minute leaks that are inaudible in bustling factory environments.
  • Maintain Operational Efficiency: Seamlessly integrate the camera into any maintenance phase without stopping production.
  • Achieve Cost & Energy Savings: Get insights from AI-driven analytics on leak magnitude and associated cost implications.
  • Drive Informed Repairs: Use real-time data to craft strategic maintenance and repair plans.
  • Support Quality Control: Ensure engines have appropriate vacuum seal for maximum efficiency and smooth running.

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Calculate Your Return on Investment

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FLIR Si-Series Acoustic Imaging Cameras for Compressed Air and Vacuum System Leak Detection

Ultrasonic imaging with an acoustic camera is an effective way to identify efficiency loss and potential failures up to 10 times faster than traditional methods—with minimal training.

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Core Benefits of Acoustic Imaging:

  • Reduced energy usage
  • Reduced CO2 and other gas emissions
  • Prolong compressor/vacuum pump life

 

 

FLIR Si-Series Advantages:

  • No training required
  • Concise reporting
  • Leak quantification
  • Background noise filtering
  • Accurate measurement of leaks as small as 0.004 l/min from 1 m (3.0 ft)

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Si2-LD

For pressurized leak detection and mechanical fault detection.