Data driven prediction and sensing of smelly gases

Purpose and goal: ** Denna text är maskinöversatt **

The project has reached its objective to, in the area of gas measurements, develop and evaluate sensor techniques and data analysis methods that can be used in the process industry to increase safety and optimize processes. The project´s results have also achieved its objective of strengthening knowledge about digitalisation of the process industry. In the long term, it will contribute to the development of a sustainable and resource-efficient industry.

Expected results and effects: ** Denna text är maskinöversatt **

The project has shown that it is technically possible to develop gas sensors with high sensitivity for the detection of odorous sulfur gases at a relatively low cost. The project has also shown that an AI-based multi-sensor system can be used to detect gases with high precision. The system and models have been evaluated against these gases, but with different sensors there are possibilities to detect other gases.

The path from demo to full implementation is a long one and requires a comprehensive approach to handle process engineering and safety aspects. Approach and implementation:

The project has been conducted in a number of work packages, where sensor and system development have been conducted in parallel. Initially, the implementation was disrupted by the pandemic, which caused problems with planned recruitments, laboratory work and access to infrastructure. Through the exchange of a partner, the focus of the project shifted more towards the measurement of sulfur and less towards applications for biorefinery.

Technical and safety challenges in the implementation in the production resulted in challenges that were not calculated in the project plan.