Generally,one of the most difficult works at scheduling is to estimate the duration of activities and linkages between them because the possibility that the duration and linkages could be exposed to the uncertainties ...Generally,one of the most difficult works at scheduling is to estimate the duration of activities and linkages between them because the possibility that the duration and linkages could be exposed to the uncertainties is very high.When estimating project duration,therefore,the probabilistic estimation of the duration as well as the probabilistic estimation of the linkages between activities should be considered concurrently.The Project Evaluation and Review Technique(PERT)that is considered to be one of the most popular techniques applied for the probabilistic estimation of a project duration cannot consider the uncertainties of the linkages because it only estimates the probabilistic duration limited to“FS0”relationship.The purpose of this study is to propose the new method,the Probabilistic Linkage Evaluation Technique(PLET),for probabilistically estimating the project duration based on the probabilistic estimation of the BDM’s relationships,and also provide more wide and various probabilistic information about the project duration.展开更多
Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between moni...Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between monitoring variables can characterize the operation state of the system. In this study,we present a straightforward and fast computational method, the multivariable linkage coarse graining(MLCG) algorithm, which converts the linkage fluctuation relationship of multivariate time series into a directed and weighted complex network. The directed and weighted complex network thus constructed inherits several properties of the series in its structure. Thereby, periodic series convert into regular networks, and random series convert into random networks. Moreover, chaotic time series convert into scale-free networks. It demonstrates that the MLCG algorithm permits us to distinguish, identify, and describe in detail various time series. Finally, we apply the MLCG algorithm to practical observations series, the monitoring time series from a compressor unit, and identify its dynamic characteristics. Empirical results demonstrate that the MLCG algorithm is suitable for analyzing the multivariable linkage fluctuation relationship in complex electromechanical system. This method can be used to detect specific or abnormal operation condition, which is relevant to condition identification and information quality control of complex electromechanical system in the process industry.展开更多
Comprehensive research methods such as literature research,theoretical analysis,numerical simulations and field monitoring have been used to analyze the disasters and characteristics caused by the linkage failure and ...Comprehensive research methods such as literature research,theoretical analysis,numerical simulations and field monitoring have been used to analyze the disasters and characteristics caused by the linkage failure and instability of the residual coal pillars-rock strata in multi-seam mining.The effective monitoring area and monitoring design method of linkage instability of residual coal pillar-rock strata in multi-seam mining have been identified.The evaluation index and the risk assessment method of disaster risk have been established and the project cases have been applied and validated.The results show that:①The coal pillar will not only cause disaster in singleseam mining,but also more easily cause disaster in multi-seam mining.The instability of coal pillars can cause not only dynamical disasters such as rock falls and mine earthquakes,but also cause surface subsidence and other disasters.②When monitoring the linkage instability of residual coal pillar-rock strata,it is not only necessary to consider the monitoring of the apply load body(key block),the transition body(residual coal pillar)and the carrier body(interlayer rock and working face),but also to strengthen the monitoring of the fracture development height(linkage body).③According to the principles of objectivity,easy access and quantification,combined with investigation,analysis,and production and geological characteristics of this mining area,the main evaluation indexes of the degree of disaster caused by linkage instability of residual coal pillar-rock strata are determined as:microseismic energy,residual coal pillar damage degree,fracture development height.And the evaluation index classification table was also given.④According to the measured value of the evaluation index,the fuzzy comprehensive evaluation method was used to calculate the disaster risk degree in the studied mine belongs to class III,that is,medium risk level.The corresponding pressure relief technology was adopted on site,which achieved a good control effect,and also verified the accuracy and effectiveness of the risk evaluation results.展开更多
文摘Generally,one of the most difficult works at scheduling is to estimate the duration of activities and linkages between them because the possibility that the duration and linkages could be exposed to the uncertainties is very high.When estimating project duration,therefore,the probabilistic estimation of the duration as well as the probabilistic estimation of the linkages between activities should be considered concurrently.The Project Evaluation and Review Technique(PERT)that is considered to be one of the most popular techniques applied for the probabilistic estimation of a project duration cannot consider the uncertainties of the linkages because it only estimates the probabilistic duration limited to“FS0”relationship.The purpose of this study is to propose the new method,the Probabilistic Linkage Evaluation Technique(PLET),for probabilistically estimating the project duration based on the probabilistic estimation of the BDM’s relationships,and also provide more wide and various probabilistic information about the project duration.
基金supported by the National Natural Science Foundation of China(Grant No.51375375)
文摘Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between monitoring variables can characterize the operation state of the system. In this study,we present a straightforward and fast computational method, the multivariable linkage coarse graining(MLCG) algorithm, which converts the linkage fluctuation relationship of multivariate time series into a directed and weighted complex network. The directed and weighted complex network thus constructed inherits several properties of the series in its structure. Thereby, periodic series convert into regular networks, and random series convert into random networks. Moreover, chaotic time series convert into scale-free networks. It demonstrates that the MLCG algorithm permits us to distinguish, identify, and describe in detail various time series. Finally, we apply the MLCG algorithm to practical observations series, the monitoring time series from a compressor unit, and identify its dynamic characteristics. Empirical results demonstrate that the MLCG algorithm is suitable for analyzing the multivariable linkage fluctuation relationship in complex electromechanical system. This method can be used to detect specific or abnormal operation condition, which is relevant to condition identification and information quality control of complex electromechanical system in the process industry.
基金the financial support by the National Natural Science Foundation of China(Nos.52304093,52074168,52079068,41941019)Shandong Province Key Research and Development Program(No.2019SDZY02)+4 种基金Shandong Taishan Scholars Climbing Program(No.tspd20210313)State Key Laboratory of Hydroscience and Engineering foundation(No.2021-KY-04)Natural Science Foundation of Shandong Province Outstanding Youth Fund project(No.ZQ2022YQ49)the Taishan Scholars Project Special Fund(No.tsqn202211150)the Anhui Engineering Research Center of Exploitation and Utilization of Closed/Abandoned Mine Resources(No.EUCMR202205).
文摘Comprehensive research methods such as literature research,theoretical analysis,numerical simulations and field monitoring have been used to analyze the disasters and characteristics caused by the linkage failure and instability of the residual coal pillars-rock strata in multi-seam mining.The effective monitoring area and monitoring design method of linkage instability of residual coal pillar-rock strata in multi-seam mining have been identified.The evaluation index and the risk assessment method of disaster risk have been established and the project cases have been applied and validated.The results show that:①The coal pillar will not only cause disaster in singleseam mining,but also more easily cause disaster in multi-seam mining.The instability of coal pillars can cause not only dynamical disasters such as rock falls and mine earthquakes,but also cause surface subsidence and other disasters.②When monitoring the linkage instability of residual coal pillar-rock strata,it is not only necessary to consider the monitoring of the apply load body(key block),the transition body(residual coal pillar)and the carrier body(interlayer rock and working face),but also to strengthen the monitoring of the fracture development height(linkage body).③According to the principles of objectivity,easy access and quantification,combined with investigation,analysis,and production and geological characteristics of this mining area,the main evaluation indexes of the degree of disaster caused by linkage instability of residual coal pillar-rock strata are determined as:microseismic energy,residual coal pillar damage degree,fracture development height.And the evaluation index classification table was also given.④According to the measured value of the evaluation index,the fuzzy comprehensive evaluation method was used to calculate the disaster risk degree in the studied mine belongs to class III,that is,medium risk level.The corresponding pressure relief technology was adopted on site,which achieved a good control effect,and also verified the accuracy and effectiveness of the risk evaluation results.
