在使用深度自动编码器的酸气清除单元中检测和识别故障
Tan Kaiyun Kathlyn1,2, Haslinda Zabiri1,3, Chris Aldrich4
1Department of Chemical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610 Perak, Malaysia.
ACS omega
|June 12, 2023
概括
在酸性气体清除装置 (AGRU) 中早期检测故障对于天然气加工至关重要. 这项研究表明,具有微调的深度稀疏自动编码器可以准确地检测出常见的AGRU故障,如发泡,损坏的托盘和污垢.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 过程控制 过程控制
- 人工智能的人工智能
背景情况:
- 酸性气体去除装置 (AGRU) 在天然气加工中对于去除CO2和H2S至关重要.
- 泡,损坏的托盘和污染是常见的AGRU故障,但尚未研究.
- 早期检测故障对于防止财务损失和运营中断至关重要.
研究的目的:
- 用SoftMax研究浅层和深层稀疏自动编码器的有效性,以早期检测AGRU故障.
- 将自动编码器模型的性能与主要组件分析模型进行比较.
- 为 AGRU 确定最准确的故障诊断模型.
主要方法:
- 在故障条件下模拟AGRU的动态过程变量,使用Aspen HYSYS Dynamics.
- 开发和比较五种故障诊断模型:PCA,浅层稀疏自编码器 (有/没有微调) 和深层稀疏自编码器 (有/没有微调).
- 利用自动编码器的功能可视化来分析模型性能和AGRU动态.
主要成果:
- 所有测试的模型都显示出合理的故障区分能力.
- 微调的深度稀疏自动编码器在故障检测中实现了最高的精度.
- 发泡为检测带来了最大的挑战,但微调深度自动编码器的功能有助于可视化监控.
结论:
- 稀有的自动编码器,特别是深度微调版本,为AGRU的早期故障检测提供了强大的工具.
- 开发的模型可以显著提高运营效率,减少天然气加工的财务损失.
- 自动编码器的功能可视化为开发自动化的AGRU监控系统提供了宝贵的见解.
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