Outputs (4)

A review of ultrasonic sensing and machine learning methods to monitor industrial processes (2022)
Journal Article
Bowler, A. L., Pound, M. P., & Watson, N. J. (2022). A review of ultrasonic sensing and machine learning methods to monitor industrial processes. Ultrasonics, 124, Article 106776. https://doi.org/10.1016/j.ultras.2022.106776

Supervised machine learning techniques are increasingly being combined with ultrasonic sensor measurements owing to their strong performance. These techniques also offer advantages over calibration procedures of more complex fitting, improved general... Read More about A review of ultrasonic sensing and machine learning methods to monitor industrial processes.

Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation (2021)
Journal Article
Bowler, A. L., Pound, M. P., & Watson, N. J. (2021). Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation. Fermentation, 7(4), Article 253. https://doi.org/10.3390/fermentation7040253

Beer fermentation processes are traditionally monitored through sampling and off-line wort density measurements. In-line and on-line sensors would provide real-time data on the fermentation progress whilst minimising human involvement, enabling ident... Read More about Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation.

Convolutional feature extraction for process monitoring using ultrasonic sensors (2021)
Journal Article
Bowler, A., Pound, M., & Watson, N. (2021). Convolutional feature extraction for process monitoring using ultrasonic sensors. Computers and Chemical Engineering, 155, Article 107508. https://doi.org/10.1016/j.compchemeng.2021.107508

Ultrasonic sensors are a low-cost and in-line technique and can be combined with machine learning for industrial process monitoring. However, training accurate machine learning models for process monitoring using sensor data is dependant on the featu... Read More about Convolutional feature extraction for process monitoring using ultrasonic sensors.

Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning (2021)
Journal Article
Bowler, A., Escrig, J., Pound, M., & Watson, N. (2021). Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning. Fermentation, 7(1), Article 34. https://doi.org/10.3390/fermentation7010034

Beer fermentation is typically monitored by periodic sampling and off-line analysis. In-line sensors would remove the need for time-consuming manual operation and provide real-time evaluation of the fermenting media. This work uses a low-cost ultraso... Read More about Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning.