To alleviate the heavy load of massive alarm on operators, alarm threshold in chemical processes was optimized with principal component analysis(PCA) weight and Johnson transformation in this paper. First, few variabl...To alleviate the heavy load of massive alarm on operators, alarm threshold in chemical processes was optimized with principal component analysis(PCA) weight and Johnson transformation in this paper. First, few variables that have high PCA weight factors are chosen as key variables. Given a total alarm frequency to these variables initially, the allowed alarm number for each variable is determined according to their sampling time and weight factors. Their alarm threshold and then control limit percentage are determined successively. The control limit percentage of non-key variables is determined with 3σ method alternatively. Second, raw data are transformed into normal distribution data with Johnson function for all variables before updating their alarm thresholds via inverse transformation of obtained control limit percentage. Alarm thresholds are optimized by iterating this process until the calculated alarm frequency reaches standard level(normally one alarm per minute). Finally,variables and their alarm thresholds are visualized in parallel coordinate to depict their variation trends concisely and clearly. Case studies on a simulated industrial atmospheric-vacuum crude distillation demonstrate that the proposed alarm threshold optimization strategy can effectively reduce false alarm rate in chemical processes.展开更多
During the operation of complex process, such as oil production or refming, abnormal situations may occur, leading to an alarm flooding. Alarm flooding is the signalling of a large number of alarms in a few minutes, i...During the operation of complex process, such as oil production or refming, abnormal situations may occur, leading to an alarm flooding. Alarm flooding is the signalling of a large number of alarms in a few minutes, in such a way that it is impossible for the operator to attend to all alarms. On these occasions, it is usual that the operator leaves the alarm summary list and gets an analysis of the plant through the screens of the DCS （digital control system）, seeking to understand the situation. The alarm summary list ceases to be a useful tool. In such cases, the operator might have the aid of a filter that would present the highest priority alarms and other information associated with them, enabling him to gain a better knowledge of the situation. This paper describes the interface of a system aimed to help the operator to have a more comprehensive knowledge of the process （a better situational awareness） during process upsets that cause alarm flooding, recovering the utility of the alarm layer to the safety of industrial processes.展开更多
基金Supported by the National Natural Science Foundation of China(21576143)
文摘To alleviate the heavy load of massive alarm on operators, alarm threshold in chemical processes was optimized with principal component analysis(PCA) weight and Johnson transformation in this paper. First, few variables that have high PCA weight factors are chosen as key variables. Given a total alarm frequency to these variables initially, the allowed alarm number for each variable is determined according to their sampling time and weight factors. Their alarm threshold and then control limit percentage are determined successively. The control limit percentage of non-key variables is determined with 3σ method alternatively. Second, raw data are transformed into normal distribution data with Johnson function for all variables before updating their alarm thresholds via inverse transformation of obtained control limit percentage. Alarm thresholds are optimized by iterating this process until the calculated alarm frequency reaches standard level(normally one alarm per minute). Finally,variables and their alarm thresholds are visualized in parallel coordinate to depict their variation trends concisely and clearly. Case studies on a simulated industrial atmospheric-vacuum crude distillation demonstrate that the proposed alarm threshold optimization strategy can effectively reduce false alarm rate in chemical processes.
文摘During the operation of complex process, such as oil production or refming, abnormal situations may occur, leading to an alarm flooding. Alarm flooding is the signalling of a large number of alarms in a few minutes, in such a way that it is impossible for the operator to attend to all alarms. On these occasions, it is usual that the operator leaves the alarm summary list and gets an analysis of the plant through the screens of the DCS （digital control system）, seeking to understand the situation. The alarm summary list ceases to be a useful tool. In such cases, the operator might have the aid of a filter that would present the highest priority alarms and other information associated with them, enabling him to gain a better knowledge of the situation. This paper describes the interface of a system aimed to help the operator to have a more comprehensive knowledge of the process （a better situational awareness） during process upsets that cause alarm flooding, recovering the utility of the alarm layer to the safety of industrial processes.
