Reliability Theory And Methods Of Mine Ventilation System Based On Rough Sets - Neural Network

The research on reliability theory and technique in mine ventilation system is put forward, and it mainly aims at resolving the problems in this field. The purpose is to increase the reliability level of mine ventilation system, to decrease the building cost and maintenance cost of it, to prevent and reduce the happening of the disaster and accident in it, and to ensure the fulfilling high yield and high efficiency of mine. So it is the key to advance the rationality, actual effect quality, expanding quality and applying quality that more perfecting and improving reliability theory mechanism of mine ventilation system in existence, renovating the technical and administrant means. And so is one of the important tasks to optimize mine ventilation design and to accelerate safe production.In this text, the author aiming at the reliability research practice about mine ventilation system, and basing on the analysis and summary of the predecessor's production, combined the theory of network stream, ANN technique and the rough set theory with system reliability theory, set up the analytic model and imitated model about the reliability evaluation of the mine ventilated system basing on the theory of network stream and ANN respectively, and set up the reliability early-warning model based on rough set and artificial neuron network theory. At same time, basing on the system cell's speciality, the author designed the mine ventilation reliability, and investigated the method of the failures characteristic's picking and the reliability distribute in reliability design deeply. Primary research work as follows:a. Mine ventilation system reliability research based on network stream theoryBasing on the characteristics of mine ventilated system oneself, it can be considered as a repairable system made up of two subsystem of the ventilated network system and main fanner system. Making use of the network stream theory, aiming at the topological structure of the mine ventilated network and the speciality of ventilated buildings, the author set up the ventilated network reliability evaluation model with functional style, and brought forward the minimizing path sets arithmetic to solve network reliability indexes; in allusion to the repairable specialities of the main fanner subsystem, applying Markov process theory, basing on the repairable theory of cold reserve, the author set up reliability model of the main fanner subsystem used in mine.b. Research on mine ventilation system reliability based on artificial neuron network theoryBecause of the mine ventilated system is a more taches, dynamical, random, and time-changing large system, the factors affecting the system reliability are very complicated and numerous, and sometimes the influence factors relations one another and taking on very strong coupling specialty. So after completely analyzing factors that influence the reliability of mine ventilated system, the author set up an evaluating imitated model about ventilation system reliability based on BP neuron network technique; The Weibull process model is adopted to analyze the process of the ventilated system's failures. The fixed amount describe of the mine ventilated system failures' improvement and worsen basing on the influence factors' attributes is broughtup; Demonstrating the relations about the improvement or worsen with the failures intensity and the cumulated failures intensity during the ventilated system failures' process; The characteristic parameter model about the mean time between failures and the first failures time was deduced.c. Research on ventilation system reliability early-warning based on rough set and artificial neuron network theoryForm the reliability early-warning imitating to mine ventilated system with artificial neuron network technique, we have found that the much more characteristic parameters make the ANN scale too large, train time too long, the redundancy of the system rule databases and so on, and it result in the practicability function of the imitated model lower. So the author p...