Abstract

Mine ventilation system is a repairable system, with the characters of time-varied and randomness. It made us encounter some difficulties when we discussed the system failure evolution process and its operational reliability, as well as when we sought the system reliability parameters developing trends following with ventilation system operation time variation and air adjustment. Firstly, according to the reliability theory, the failure process characteristic values, which affect the ventilation system, were defined. And then, by mean of the analysis of the failure process deterioration of mine ventilation system, the deterioration and its amelioration discriminants are given basing on two parameters’ Weibull process. Finally, on the basis of adaptive neural network technology, the ventilation system failure processes were simulated, the failure process characteristic parameters were determined, and the failure curves were drawn accordingly. The results show that the failure process of the experiment mine ventilation system is a Non-homogeneous Poisson Process; the mean time between failures of the ventilation system is between 160h and 170h; the failure ratio curves present the trends of concave or convex variation when the system failure process deterioration or amelioration.

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