Description
Manufacturer | ABB |
Brand | ABB |
Series | module |
Part Number | DSQC509 |
Product Type | module |
Quality | 100% New Original |
Stock | In stock |
Delivery time | 1-3 days after Payment |
After-sales Service | Have |
Warranty | 1 year |
Shipping term | DHL / FEDEX/ EMS /UPS/TNT/EMS |
Packaging details: if you need an urgent delivery order, please feel free to contact us, and we will do our best to meet your needs.
Price problem: if you find that other suppliers offer cheaper prices for the same product, we are also willing to provide you with reference prices and give you further discounts.
CoreSense M10 multigas analyzer
The CoreSense M10 utilizes Fourier-transform
infrared (FTIR) technology combined with solidstate hydrogen and moisture sensors to measure
moisture and nine gases: hydrogen (H2
), methane
(CH4), acetylene (C2
H2
), ethylene (C2
H4), ethane
(C2
H6), propene (C3
H6), propane (C3
H8), carbon
monoxide (CO) and carbon dioxide (CO2
). The
CoreSense M10 is also provided with a local version
of Ellipse, ABB’s asset management solution. Ellipse
employs a number of algorithms sequentially to
establish if there is any abnormality and, if there is,
to make recommendations for action →4.
Tough and accurate enough for space
The gas-measuring FTIR module in the CoreSense
M10 is based on the same ABB technology that is
deployed in satellites to analyze greenhouse gases
and meteorology in the Earth’s atmosphere. The
first unit was launched more than 15 years ago and
is still in service today. This technology is sought
after for its outstanding reliability, accuracy
and stability in harsh environments. In addition,
the calibration-free nature of the technology
provides significant savings in maintenance and
replacement costs.
On earth, ABB’s FTIR is also used in other
applications such as refineries, semiconductor
factories and chemical plants to measure chemical
compounds in liquids because it can meet up to 99
percent reliability and provide stable measurements
over extended periods of time, allowing
identification of long-term trends.