As anticipated from studies of ophiolite complexes,direct investigations of the oceanic crust confirm that basaltic dikes are an integral part of the upper 2 km of the oceanic crust.Currently available information sug...As anticipated from studies of ophiolite complexes,direct investigations of the oceanic crust confirm that basaltic dikes are an integral part of the upper 2 km of the oceanic crust.Currently available information suggests展开更多
Interpretative structural model(ISM) can transform a multivariate problem into several sub-variable problems to analyze a complex industrial structure in a more efficient way by building a multi-level hierarchical str...Interpretative structural model(ISM) can transform a multivariate problem into several sub-variable problems to analyze a complex industrial structure in a more efficient way by building a multi-level hierarchical structure model. To build an ISM of a production system, the partial correlation coefficient method is proposed to obtain the adjacency matrix, which can be transformed to ISM. According to estimation of correlation coefficient, the result can give actual variable correlations and eliminate effects of intermediate variables. Furthermore, this paper proposes an effective approach using ISM to analyze the main factors and basic mechanisms that affect the energy consumption in an ethylene production system. The case study shows that the proposed energy consumption analysis method is valid and efficient in improvement of energy efficiency in ethylene production.展开更多
Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalizati...Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarm priority and reduce the blindness of alarm handling. As a case study, the Tennessee Eastman process is utilized to show the effectiveness and validity of proposed approach. Alarm system performance comparison shows that our rationalization methodology can reduce the alarm flood to some extent and improve the performance.展开更多
文摘As anticipated from studies of ophiolite complexes,direct investigations of the oceanic crust confirm that basaltic dikes are an integral part of the upper 2 km of the oceanic crust.Currently available information suggests
基金Supported by the National Natural Science Foundation of China(61374166,6153303)the Doctoral Fund of Ministry of Education of China(20120010110010)the Fundamental Research Funds for the Central Universities(YS1404,JD1413,ZY1502)
文摘Interpretative structural model(ISM) can transform a multivariate problem into several sub-variable problems to analyze a complex industrial structure in a more efficient way by building a multi-level hierarchical structure model. To build an ISM of a production system, the partial correlation coefficient method is proposed to obtain the adjacency matrix, which can be transformed to ISM. According to estimation of correlation coefficient, the result can give actual variable correlations and eliminate effects of intermediate variables. Furthermore, this paper proposes an effective approach using ISM to analyze the main factors and basic mechanisms that affect the energy consumption in an ethylene production system. The case study shows that the proposed energy consumption analysis method is valid and efficient in improvement of energy efficiency in ethylene production.
基金Supported by the National Natural Science Foundation of China(61473026,61104131)the Fundamental Research Funds for the Central Universities(JD1413)
文摘Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarm priority and reduce the blindness of alarm handling. As a case study, the Tennessee Eastman process is utilized to show the effectiveness and validity of proposed approach. Alarm system performance comparison shows that our rationalization methodology can reduce the alarm flood to some extent and improve the performance.
