Research On Uncertainty Information Processing And Risk Assessment In Safety Monitoring Of Tailings Dam

The safety of tailings dam, as a largest artificial hazard in entire mining enterprises, has agrave impact on people’s life and property as well as social security and stability, which drawsgreat attention of the society from all walks of life. But owing to strong interference ofenvironment influence, limitations of monitoring sensor itself, imperfection of monitoringmethod and dynamic of dam structure, monitoring information and risk modal information areoften imperfect, and these information have random, fuzzy and incomplete uncertainty,leading to complex and changeable mapping relation of monitoring information and riskstates information, which severely restricts assessment effect of monitoring systems.Therefore, the ways of uncertainty analysis for monitoring information and risk statesinformation, and establishment of the mapping relationship are the key role to solve lesseffective and difficult risk assessment.Possibility theory is a new mathematical tool to deal with uncertainty and can be used todescribe the possibility of future events without any prior knowledge. It has the advantagesthat diversity of uncertainty characterization, coexistence of uncertainty processing, variety ofmapping relationship and processing for small sample information, which have common withinformation processing needs of tailings dam. So taken upstream fine grained tailings dam asobjects and possibility theory combined with other uncertainty processing methods as themeans, risk assessment problem of tailings dam is solved.The main works are introduced as follows:(i)The uncertainty of information and its processing method are discussed in safetymonitoring of tailings dam. Existing uncertainty information processing method are generallydetermined by uncertainty types, and the processing method is different as the change ofuncertainty types. So finding appropriate method to deal with all kinds of uncertainty is abreakthrough in multiple source information processing field. Based on expounding sourcesand classification of uncertainty information, this paper analyzes influential factors and typesof uncertainty for tailings dam monitoring information deeply, and researches characterization of all kinds of uncertainty to solve the limitations of existing methods in processing variousuncertainties. Based upon the above research, other works are developed as follows.(ii)Possibility distributions of monitoring indexes and risk modal information areconstructed. According to the characteristics of monitoring indexes such as reservoir waterlevel, phreatic line, length of dry, beach dam displacement and video image, small samplesconstruction and possibility median are employed to construct possibility distribution of eachindex. Risk modal of tailings dam is defined. Failure mechanism of tailings dam are studiedbased on rheology and mutation theory. Combined with inherent frequency of dam, riskmodal is characterized and the boundary fuzziness of adjacent modal is researched, whichprovides a new method to solve coexist risk modal.(iii)The complex and changeable mapping relationship between information ofmonitoring indexes and risk modal are set up. Possibility distributions are transformed intoshadow sets by cut-set, then the complex mapping law is reveal by studying fuzzy inferencebetween shadow sets and the complex and changeable mapping relationship is established.Possibility set-valued mappings are simulated under different cut-sets. The results show thatthe mutual changes of cut-sets between distributions can provide theoretical basis to establishthe complex and changeable mapping relationship between information of monitoring indexesand risk modal.(iv)A multi-attribute risk evaluation model with concentrated modal is proposed based onmatching degree of distributions. Taken the mapping between index and risk modalinformation as evaluation index, risk assessment problem is regarded as risk modal selectionin order to solve the problem that existing methods can not judge risk modal effectively whenthe modals are concentrate.The matching degrees of evaluation index and risk modal aredetermined and matching matrix is builded by researching the relationship between evaluationindex and risk modal class.The weights of each evaluation index are obtained bycomprehensive weight method then matching matrix is fused to obtain matching degrees ofeach modal. The optimal matching modal is selected. The effectiveness of the proposedmethod is validated by simulation.(v)Information fusion risk assessment model with coexistence risk modal is proposed byflexible similarity measure. Flexible similarity measure between the distributions andevidence theory are used in risk assessment to solve evaluation problem of coexist risk modaland improve the effect of evaluation precision. On the basis of generalized fuzzy numbers, the generalized nonlinear fuzzy number is defined, and the calculation method of flexiblesimilarity measure is given. Its basic properties are proved, and its effectiveness andrationality is verified compared with other similar measures. The basic belief distributionfunction of evaluation index is generated by inducing function,and then the assessment resultis obtained by D-S combination rules. The effectiveness of the proposed method is validatedby simulation.(vi)The effectiveness of the proposed methods have been validated by Huo Gudu andHuang Meishan tailings dam as two examples. The basic situation of the tailings dams areanalyzed, and the symptoms and loss in dam collapse are introduced. The information ischaracterized by analyzing the monitoring information and dam risk modal information within amonth before dam collapse.The complex mapping relationship between the both is established,and the risk modal of the dams are inverted by using the proposed risk assessment methods.The results show that two kinds of risk assessment methods can both make accurate judgmenton dam risk modal.