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Research for the Intelligent RMB Sorter Based on ANN

机译:基于人工神经网络的人民币智能分拣机研究

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摘要

A smart and cost-effective intelligent RMB (Ren Min Bi) sorting system is built by theoretical approaches and technical facilities integrated of electrics,magnetics,optics,maths,mechanics.It can be used to identify authenticity,denomination,orientation version of RMB,whether RMB is new or old,and count the number of sheets and the amount.Real money and false money can be distinguished by three detection facilities including fluorescence detection of forgery,infrared detection of forgery,and magnetic detection of forgery during every working process of the sorter. Test shows that the accuracy rate is 100 %.In above process,Once false coin is detected,the system immediately provides sound-light alarm,then false money is sent to the lower output (real money is sent to the higher output) simultaneously without interruption of the operation at that time,which is the feature of the sorter.Classified identification intelligence technology and picture identification processing technology based on ANN (Artificial Neural Network) are Skillfully combined with four relevant algorithms including BP (Back Propagation)-ANN,LVQ (Learning Vector Quantization)ANN,Kalman,Genetics,then highly automation and intelligence of the sorting system are successfully realized,which is another feature of the sorter.
机译:通过集电气,磁学,光学,数学,机械等方面的理论方法和技术设施于一体,构建了智能,高性价比的人民币智能分拣系统,可用于识别人民币的真实性,面额,方向等。人民币是新的还是旧的,并计算张数和金额。真钞和伪钞可以通过三种检测设施进行区分,包括荧光伪造检测,红外伪造检测和磁性伪造检测。分拣机。测试表明准确率是100%。在上述过程中,一旦检测到假币,系统会立即发出声光报警,然后将假币同时发送到较低的输出(真实货币发送到较高的输出),而不会分拣机的特点就是分类操作。基于人工神经网络的分类识别智能技术和图片识别处理技术巧妙地结合了BP(反向传播)-ANN,LVQ等四种相关算法(学习矢量量化)ANN,Kalman,Genetics,然后成功实现了分拣系统的高度自动化和智能化,这是分拣机的另一个功能。

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