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ASDevices > Products > GC Platforms > ASDSense
GC Platforms


Embedded process GC software

Innovative software built for ease of use and robustness

The ASDSense is powerful GC analysis software that runs on all our OEM GC platforms. It’s been designed to be robust enough for 24/7 process use with laboratory-like data analysis features. What’s more, it’s intuitive and loaded with features like multiple innovative advanced signal processing algorithms, making it the most powerful and versatile process GC software on the market.


  • Based on a real-time industrial operating system
  • Designed based on software redundancy for reliability
  • Advanced signal processing
  • Multi-method capability with automatic sampling system synchronization
  • Data analysis
  • Multilingual (English, Simplified Chinese)
  • IIoT ready
  • Support digital relays, 4-20 mA, RS-232, ethernet, Modbus
  • Full feature GC laboratory software also available.

Solution highlights

Asynchronous (parallel) chromatographic analysis

In chromatography, it’s common to have parallel channels. But because traditional GC software are synchronous, it’s not possible to analyze each one independently. If one channel requires a 5-minute analysis and another requires a 10-minute analysis, the shorter cycle is slowed down by the longer one, and this is a major limitation. As we always want to offer best-in-class solutions, our GC software natively support asynchronous chromatography.


Chromatogram denoising

ASDSense offers a powerful signal processing algorithm to improve signal to noise (SNR), without impacting peak shape and peak area. Based on techniques used in image processing, the algorithm not only filters the peak shape in the frequency domain like a FFT of FIR type filter, but it also takes into account both time and frequency.

  • Baseline noise reduction
  • Limit of detection improvement
  • Peak shape and area are preserved



Enhanced LOD (ELOD) and peak re-modeling algorithm

Over time, the ELOD algorithm analyzes and learns the detector’s baseline noise and peak shape based on a number of consecutive chromatograms. The learning process allows for a better understanding of the signal’s power distribution and differentiates between noises.

  • LOD is improved by up to 10 times
  • Random noise is removed
  • Retention time variation is reduced
  • Peak shape is improved

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