Temperature-Effect Compensation for Leak Detectors by Using Machine Learning Techniques

Autor: Andoni Bilbao, Xabier Oregui Biain, Zelmar Etxegoien, Juan Luis Ferrando Chacón, Ander García Gangoiti, Eneko Fernandez

Publikováno v: 16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021) ISBN: 9783030878689
SOCO

Although Differential Pressure Decay Testing (DPDT) is less influenced by external environment than pressure decay testing, the different temperatures involved in the process still affect the leak measurements, particularly in quick changing conditio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3ab1d23bd990310aa487dfc9fa811e0a
https://doi.org/10.1007/978-3-030-87869-6_51