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A novel integrated framework for fault diagnosis with application to process safety
Process Safety and Environmental Protection ( IF 6.9 ) Pub Date : 2021-08-11 , DOI: 10.1016/j.psep.2021.08.008
Lahouari Cheded 1 , Rajamani Doraiswami 2, 3
Affiliation  

A novel integrated framework for Fault Detection and Isolation(FDI) is proposed, with applications to process safety, by sequentially integrating model-free(MFA) and model-based(MBA) approaches. The MFA includes Limit Checking/Visual and Plausibility analysis, Artificial Neural Network and Fuzzy Logic, Adaptive Neuro-Fuzzy Inference System. The MBA uses a Linear Parameter-Varying model to handle a wide class of generally-nonlinear physical systems. The adaptive Kalman filter(KF) residuals are used for FDI in the MBA. Novel emulators, cascaded with the system during off-line data acquisition, system identification and Bayes’measure of belief computation for each FDI scheme, have their parameters perturbed at each operating point, to mimic unforeseen operational scenarios, thus covering all operating regions. Critical information about the presence/absence of a fault is quickly gained via the faster FDI scheme. A more accurate subsystem’s status is unfolded sequentially by the slower FDI scheme. The final decision on the fault status is obtained using a weighted Bayes classifier fusion scheme meeting the critical requirements of high(low) probability of correct decision (false alarm). Implications of FDI in process safety/environment protection are discussed. This framework is successfully evaluated on simulated and physical systems, including benchmarked laboratory-scale two-tank system, by detecting and isolating sensor, actuator and leakage faults.



中文翻译:

一种应用于过程安全的新型故障诊断集成框架

通过顺序集成无模型(MFA)和基于模型的(MBA)方法,提出了一种新的故障检测和隔离(FDI)集成框架,应用于过程安全。MFA 包括极限检查/视觉和合理性分析、人工神经网络和模糊逻辑、自适应神经模糊推理系统。MBA 使用线性参数变化模型来处理广泛的一般非线性物理系统。自适应卡尔曼滤波器 (KF) 残差用于 MBA 中的 FDI。新型仿真器在离线数据采集、系统识别和每个 FDI 方案的贝叶斯置信度计算期间与系统级联,在每个操作点扰动其参数,以模拟不可预见的操作场景,从而覆盖所有操作区域。通过更快的 FDI 方案可以快速获取有关故障存在/不存在的关键信息。较慢的 FDI 计划按顺序展开更准确的子系统状态。使用满足正确决策(误报)高(低)概率的关键要求的加权贝叶斯分类器融合方案获得关于故障状态的最终决定。讨论了 FDI 在过程安全/环境保护方面的影响。通过检测和隔离传感器、执行器和泄漏故障,在模拟和物理系统上成功评估了该框架,包括基准实验室规模的两罐系统。使用满足正确决策(误报)高(低)概率的关键要求的加权贝叶斯分类器融合方案获得关于故障状态的最终决定。讨论了 FDI 在过程安全/环境保护方面的影响。通过检测和隔离传感器、执行器和泄漏故障,在模拟和物理系统上成功评估了该框架,包括基准实验室规模的两罐系统。使用满足正确决策(误报)高(低)概率的关键要求的加权贝叶斯分类器融合方案获得关于故障状态的最终决定。讨论了 FDI 在过程安全/环境保护方面的影响。通过检测和隔离传感器、执行器和泄漏故障,在模拟和物理系统上成功评估了该框架,包括基准实验室规模的两罐系统。

更新日期:2021-08-29
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