School of Engineering Science, LUT University, Yliopistonkatu 34, 53850 Lappeenranta, Finland.
Institute of Applied Computer Science, Lodz University of Technology, 90/924 Lodz, Poland.
Sensors (Basel). 2021 Oct 20;21(21):6958. doi: 10.3390/s21216958.
In the present research work, an electrical resistance tomography (ERT) system is utilized as a means for real-time fault detection and diagnosis (FDD) during a reactive crystallization process. The calcium carbonate crystallization is part of the carbon capture and utilization scheme where process monitoring and malfunction diagnostics strategies are presented. The graphical logic representation of the fault tree analysis methodology is used to develop the system failure states. The measurement consistency due to the use of a single electrode from a set of ERT electrodes for malfunction identification is experimentally and quantitatively investigated based on the sensor sensitivity and standard deviation criteria. Electrical current measurements are employed to develop a LabVIEW-based process automation program by using the process-specific knowledge and historical process data. Averaged electrical current is correlated to the mechanical failure of the stirrer through standard deviation evaluation, and slopes of the measured data are used to monitor the pump and concentrations status. The performance of the implemented methodology for detecting the induced faults and abnormalities is tested at different operating conditions, and a basic signal-based alarming technique is developed.
在本研究工作中，采用电阻层析成像（ERT）系统作为实时故障检测和诊断（FDD）手段，应用于反相结晶过程。碳酸钙结晶是碳捕获和利用方案的一部分，提出了过程监测和故障诊断策略。故障树分析方法的图形逻辑表示用于开发系统故障状态。基于传感器灵敏度和标准偏差标准，通过实验和定量研究，使用 ERT 电极组中的单个电极进行故障识别，从而实现测量一致性。通过使用特定于过程的知识和历史过程数据，采用电流测量来开发基于 LabVIEW 的过程自动化程序。通过标准偏差评估将平均电流与搅拌器的机械故障相关联，并使用测量数据的斜率来监测泵和浓度状态。在不同的操作条件下测试了所采用的方法检测诱导故障和异常的性能，并开发了基本的基于信号的报警技术。
