Intelligent data base for grinding processes

本研究的目的是建立一个智能学习模型，可以模仿熟练的操作人员的决策过程，以设定磨削参数。该系统的功能是提供修整条件和磨削条件，以达到所需的表面粗糙度和比磨削能。比磨削能对磨削烧伤的发生有决定性的影响。为了建立这种智能学习模型，我们采用神经网络来模拟算子的联想记忆。操作员必须采用他在经验中可以获得成功结果的磨削条件。在我们的系统中，通过应用两种不同类型的神经网络来模拟这种过程，即，传统的前馈网络和盒子里的大脑状态网络。这两个网络被组合成一个混合网络来模仿操作员的联想记忆。该系统能够提供一个组合的修整和磨削条件，可以满足所需的表面粗糙度。通过一系列的计算机仿真实验，验证了该系统的有效性。为了实现这样的功能，我们应用了遗传算法和模糊规则。该系统通过实际操作可以学习磨削过程中输入与输出之间的因果关系。该系统可建立磨削数据库。通过计算机仿真和实际磨削实验验证了系统的有效性。

The purpose of this study is to establish an intelligent learning model which can imitate the decision making process of skilled operators for setting up the grinding parameters. The function of the system is to provide both the dressing condition and the grinding condition which can achieve the required surface roughness and the specific grinding energy. The specific grinding energy has a decisive influence on the occurrence of grinding burn. Therefore, it is an important output to be observed.In order to establish such intelligent learning model, we employs the neural network to imitate the associative memory of operators. The operator must adopt the grinding conditions with which he could achieve successful results in his experiences. Such process is imitated in our system by applying two different types of neural network i.e., a conventional Feed Forward Network and a Brain-State-in-a-Box Network. These two networks were combined into a hybrid network to imitate the associative memory of operators. The system is able to provide a combination of dressing and grinding condition which can meet the required surface roughness. The effectiveness of the proposed system was confirmed through a series of computer simulations.The second system proposed has an ability to imitate the learning function of operators. In order to achieve such function, we applied a genetic algorithm and a fuzzy rule. The system can learn causalities between the input and the output in the grinding process through practical operations. The system can, consequently, establish a grinding data base. The availability of the system was confirmed through both the computer simulations and the practical grinding experiments.