In modern plants with high levels of automation, acquiring an adequate mental model of the process has become a challenge for operators. Studies indicate that sub-optimal decisions occur when there is a mismatch between the demands of the process and the human's capability. This mismatch leads to high cognitive workload in human operators, often a precursor for poor performance. Recently, researchers in various safety critical domains (aviation, driving, marine, NPP, etc.) have started to explore the use of physiological measurements from humans to understand their cognitive workload and its effect. In this work, we evaluate the potential of EEG to measure cognitive workload of human operators in chemical process control room. We propose a single dry electrode EEG based methodology for identifying the similarities and mismatch between the operators’ mental model of the process and the actual process behaviour during abnormal situations. Our results reveal that S^Ɵ(ω), the power spectral density of theta (ɵ) waves (frequency range 4–7 Hz) in the EEG signal has the potential to identify such mismatches. Results indicate that S^Ɵ(ω) is positively correlated with workload and hence can be used for assessing the cognitive workload of operators in process industries.

在自动化程度很高的现代化工厂中，获得适当的过程思维模型已成为操作员的挑战。研究表明，当流程的需求与人的能力之间存在不匹配时，就会出现次优决策。这种不匹配导致操作人员认知工作量大，通常是表现不佳的先兆。最近，各种安全关键领域（航空，驾驶，海洋，NPP等）的研究人员已开始探索使用人类的生理测量方法来了解他们的认知工作量及其作用。在这项工作中，我们评估了脑电图测量化学过程控制室中操作员的认知工作量的潜力。我们提出了一种基于干电极EEG的方法，用于识别异常情况下操作员的过程心理模型与实际过程行为之间的相似性和不匹配性。我们的结果表明小号^Ɵ（ω），θ-（的功率谱密度ɵ在EEG信号）波（频率范围4-7赫兹）具有识别这种不匹配的可能性。结果表明小号^Ɵ（ω）是积极与工作量相关，因此可以用于评估在过程工业运营商的认知工作量。