Baosteel＇ s No. 8 air separation unit（ASU） is the first domestically-integrated 60 000 m^3/h ASU. This paper describes the mechanical equipment, the design and the configuration characteristics of this unit. The po...Baosteel＇ s No. 8 air separation unit（ASU） is the first domestically-integrated 60 000 m^3/h ASU. This paper describes the mechanical equipment, the design and the configuration characteristics of this unit. The potential failure modes of the mechanical devices are deduced via analyses on the failure history of similar devices in other ASUs. Finally, this paper also brings up suggestions on daily maintenance, overhaul and purchases of spare parts.展开更多
Due to the fact that in ship maintena n ce process,the method of determining the number of spare parts is not scientific and the actual operation is complicated,this paper analyzes four major facto rs affecting the nu...Due to the fact that in ship maintena n ce process,the method of determining the number of spare parts is not scientific and the actual operation is complicated,this paper analyzes four major facto rs affecting the number of ship spare parts,including number of main planned op eration s,total times of disassembling in maintenance,accumulated working time and mea n t ime between failures.It also establishes a spare parts demand forecast model b ased on the affecting factors and radial-basis function(RBF) neural network.F inally,the paper provide s forecast examples and makes a comparison between the examples and back propaga tion(BP) neura l network forecast result.The comparison results s how that the forecast based on RBF neural network is simple and the forecast res ult fits the actual situa tion and fitting effect is better than that based on BP.展开更多
文摘Baosteel＇ s No. 8 air separation unit（ASU） is the first domestically-integrated 60 000 m^3/h ASU. This paper describes the mechanical equipment, the design and the configuration characteristics of this unit. The potential failure modes of the mechanical devices are deduced via analyses on the failure history of similar devices in other ASUs. Finally, this paper also brings up suggestions on daily maintenance, overhaul and purchases of spare parts.
文摘Due to the fact that in ship maintena n ce process,the method of determining the number of spare parts is not scientific and the actual operation is complicated,this paper analyzes four major facto rs affecting the number of ship spare parts,including number of main planned op eration s,total times of disassembling in maintenance,accumulated working time and mea n t ime between failures.It also establishes a spare parts demand forecast model b ased on the affecting factors and radial-basis function(RBF) neural network.F inally,the paper provide s forecast examples and makes a comparison between the examples and back propaga tion(BP) neura l network forecast result.The comparison results s how that the forecast based on RBF neural network is simple and the forecast res ult fits the actual situa tion and fitting effect is better than that based on BP.
