摘要
针对废旧铅蓄电池回收生产线制氧站在生产过程用氧量下降时排氧量过多,导致大量电能浪费的情况,提出了一种节能改进技术。首先根据制氧站中罗茨风机的工作特点,引入变频器实现风机的无级调速,同时利用神经网络算法来实现进风风机与排风风机之间一个最优的速度组合,最后在MATLAB仿真环境与实际工厂环境下对该方法进行了实验。实验结果表明,本文提出的改进方法能够有效地减少制氧站的电能浪费同时,还能保证整个回收生产线的正常工作。
The improvement of energy saving technology was proposed, which considered the produc- tion process with oxygen decrease when the oxygen discharge too much lead to waste a lot of energy, based on the oxygen generation station of waste lead--acid battery recycling production line. First ac- cording to the features of roots blower in the oxygen station, bring in the frequency transformer to real- ize stepless speed regulation, at the same time using the neural network algorithm to achieve the speed of an optimal combination between the ventilation fan and exhaust fan, finally do experiment in the MAT- LAB simulation and the actual environment. The experimental results show that the proposed method can effectively reduce the oxygen station electric energy waste and can guarantee the normal work of the whole recycling line.
出处
《河南机电高等专科学校学报》
CAS
2015年第4期8-11,共4页
Journal of Henan Mechanical and Electrical Engineering College
基金
2012年河南省重点科技攻关计划项目"废旧铅酸蓄电池回收生产线制氧站综合节能技术研究"(122102210256)
关键词
制氧站
罗茨风机
变频调速
神经网络
oxygen generation station
roots blower
frequency control of motor speed
neural net-work