基于神经网络的利乐包装设备零件寿命的预测

以可靠性为中心的维修思想为指导,整理、利用某工厂5台利乐液体包装设备近10年零件更换和工作条件的历史数据,根据设备维修实践,提出了零件剩余寿命率的概念,设计实现了BP神经网络,预测设备主要零件的剩余寿命率,得到了较为满意的预测结果.该方法可作为利乐设备预防性维护系统(TPMS)的补充方法,对利乐设备维护管理有较强的实际指导意义,给操作和维修人员及时提供准备更换零件的信息,从而保证乳品生产的可靠性,有效降低生产成本和设备维护成本.

Components Life of Package Equipment Predict Based on Neural Network

In the paper,using the reliability-centered maintenance ideology as a guide,we organized,did research on the historical data of replacement and working conditions based on the parts of five tetra pak liquid packaging equipments of a factory in the past 10 years.In addition,we put forward the concept of residual life of parts and designed the BP neural network in accordance with equipment maintenance practice.Moreover,we achieved the goal of forecasting residual life of the main components of equipments.Owing to the satisfactory results,it can be used as alternative method of the Tetra Pak equipment preventive maintenance system.Furthermore,it can be used as supplementary method of the Tetra Pak equipment maintenance.Besides,it will provide operators and maintenance staff with timely information of preparations and the replacement of parts to ensure the reliability of dairy production and effectively reduce production and equipment maintenance costs.