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Detection of Oil in Compressed Air (DOCA) (DOCA)
Date du début: 1 sept. 2012, Date de fin: 31 déc. 2014 PROJET  TERMINÉ 

The project aims to solve a major problem plaguing the industry regarding the detection of oil contaminants in high purity compressed air. It aims to develop an online sensor that will detect oil contaminants in all its forms (liquid, aerosol and vapor) with an extremely high sensitivity in accordance with ISO-8573 Class 1 standards. The lack of any reliable, highly sensitive, online sensor system has forced critical industries to rely on manual sampling and laboratory analysis which is labour intensive, inefficient, and cannot guarantee the conformance of the compressed air system to mandatory or industry adopted regulatory norms. The sensor system will benefit a large category of industries that require high purity compressed air including, hospitals, pharmaceutical, automotive, chemical, textiles, electronics, clean rooms and other related industries. The ability to detect contaminants online, will significantly enhance the capabilities of these companies to guarantee the quality of their products and eliminate a number of risks and civil liabilities that are associated with non-conformance.To achieve the project results, a consortium of 3 competent SMEs with an interest in the area of sensor development partnered with 3 leading research partners for the development of this project proposal. The major requirement for the sensor element is extremely high sensitivity, repeatability, robustness to interference, and stable calibration. It was decided after much deliberation that optical spectroscopy is the most promising technology for the development of such a sensor. We have dedicated 3 work packages (WP4, 5, and 6) for the development of 3 key components that are vital for the development of the sensor - namely development of the sampling system, development of the optical spectroscopy unit and development of electronics and software. The entire project will deliver a marketable sensor system in 2 years.

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