BibMon: An open source Python']Python package for process monitoring, soft sensing, and fault diagnosis

被引:1
|
作者
Melo, Afranio [1 ,2 ]
Lemos, Tiago S. M. [1 ,3 ]
Soares, Rafael M. [1 ]
Spina, Deris [1 ]
Clavijo, Nayher [1 ]
Campos, Luiz Felipe de O. [1 ,4 ]
Camara, Mauricio Melo [1 ,4 ]
Feital, Thiago [1 ]
Anzai, Thiago K. [2 ]
Thompson, Pedro H. [2 ]
Diehl, Fabio C. [2 ]
Pinto, Jose Carlos [1 ]
机构
[1] Univ Fed Rio de Janeiro, Programa Engn Quim, COPPE, BR-21941972 Rio De Janeiro, RJ, Brazil
[2] PETROBRAS Petr Brasileiro SA, CENPES, Ctr Pesquisas Leopoldo Miguez Mello, BR-21941915 Rio De Janeiro, RJ, Brazil
[3] Petrobras Petr Brasileiro SA, Gestao Parcerias & Proc Exploracao & Prod GPP E&P, BR-20231030 Rio De Janeiro, Brazil
[4] OPTIMATECH Ltda, BR-22410905 Rio De Janeiro, RJ, Brazil
来源
关键词
Process monitoring; Fault detection and diagnosis; Soft sensor; Machine learning; Open source;
D O I
10.1016/j.dche.2024.100182
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This paper introduces BibMon, a Python package that provides predictive models for data-driven fault detection and diagnosis, soft sensing, and process condition monitoring. Key features include regression and reconstruction models, preprocessing pipelines, alarms, and visualization through control charts and diagnostic maps. BibMon also includes real and simulated datasets for benchmarking, comparative performance analysis of different models, and hyperparameter tuning. The package is designed to be highly extensible, allowing for easy integration of new models and methodologies through its object-oriented implementation. Currently, BibMon is in production at Petrobras, a major player in the energy industry, monitoring numerous industrial assets and enabling real-time detection and diagnosis of equipment and process faults. The software is open source and available at: https://github.com/petrobras/bibmon.
引用
收藏
页数:9
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