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Babji Srinivasan
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Babji Srinivasan
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Babji Srinivasan
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Srinivasan, Babji
Babji, S.
Srinivasan, B.
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4 results
Now showing 1 - 4 of 4
- PublicationQuantifying situation awareness of control room operators using eye-gaze behavior(01-01-2017)
;Bhavsar, Punitkumar; In an attempt to improve process safety, today's plants deploy sophisticated automation and control strategies. Despite these, accidents continue to occur. Statistics indicate that human error is the predominant contributor to accidents today. Traditionally, human error is only considered during process hazard analysis. However, this discounts the role of operators in abnormal situation management. Recently, with the goal to develop proactive strategies to prevent human error, we utilized eye tracking to understand the situation awareness of control room operators. Our previous studies reveal the existence of specific eye gaze patterns that reveal operators’ cognitive processes. This paper further develops this cognitive engineering based approach and proposes novel quantitative measures of operators’ situation awareness. The proposed measures are based on eye gaze dynamics and have been evaluated using experimental studies. Results demonstrate that the proposed measures reliably identify the situation awareness of the participants during various phases of abnormal situation management. - PublicationDynamic assessment of control room operator's cognitive workload using Electroencephalography (EEG)(04-10-2020)
;Iqbal, Mohd Umair; 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 SƟ(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 SƟ(ω) is positively correlated with workload and hence can be used for assessing the cognitive workload of operators in process industries. - PublicationToward Preventing Accidents in Process Industries by Inferring the Cognitive State of Control Room Operators through Eye Tracking(05-02-2018)
;Das, Laya ;Iqbal, Mohd Umair ;Bhavsar, Punitkumar; While modern chemical plants have numerous layers of protection to ensure safety, the human operator is often the final arbiter, especially during abnormal situations. It is therefore not surprising that when operators lose control over the plant, undesirable consequences including property damage, injury, and sometimes loss of lives follow. It is therefore important to continuously monitor the plant operators' situation awareness based on their cognitive state. In this study, we make the first known attempt to infer the cognitive state of control room operators and its evolution over the course of carrying out tasks in a control room. First, we study the operator's actions to distinguish consistent actions from inconsistent ones that allows us to identify major events in the evolution of their cognitive state. Next, we conduct experimental studies with human participants and explore the evolution of their cognitive state through patterns in their eye tracking data. Our studies reveal that two eye tracking measures, fixation duration and saccade duration, are sensitive to the cognitive state and can be used to monitor control room operators and thus prevent human error. - PublicationKalman-based strategies for Fault Detection and Identification (FDI): Extensions and critical evaluation for a buffer tank system(11-05-2011)
;Villez, Kris; ; ; Venkatasubramanian, VenkatThis paper is concerned with the application of Kalman filter based methods for Fault Detection and Identification (FDI). The original Kalman based method, formulated for bias faults only, is extended for three more fault types, namely the actuator or sensor being stuck, sticky or drifting. To benchmark the proposed method, a nonlinear buffer tank system is simulated as well as its linearized version. This method based on the Kalman filter delivers good results for the linear version of the system and much worse for the nonlinear version, as expected. To alleviate this problem, the Extended Kalman Filter (EKF) is investigated as a better alternative to the Kalman filter. Next to the evaluation of detection and diagnosis performance for several faults, the effect of dynamics on fault identification and diagnosis as well as the effect of including the time of fault occurrence as a parameter in the diagnosis task are investigated. © 2011 Elsevier Ltd.