关 键 词：

JC37 砂轮 磨损 智能 监测 研究 图纸

资源描述：

JC37-砂轮磨损的智能监测的研究带图纸,JC37,砂轮,磨损,智能,监测,研究,图纸

内容简介：

盐城工学院机械工程系毕业论文摘 要 本文研究了自动化加工过程中对砂轮磨损状态进行智能识别的一种新方法，即在磨削过程中利用多路传感器获取多路信号，输入计算机提取特征向量，利用自适应共振神经网络-ART2建立的模型对数据进行融合并对砂轮状态进行智能识别。文中介绍了ART2网络的特点、工作原理和对通过多路传感器所获得的实验数据进行融合的方法及数据处理的步骤，并给出了具体的实现过程；同时对ART2网络结构作了讨论，为了保证网络在应用中的稳定性，给出了一种新型的网络结构和算法。研究结果表明，应用改进后的ART网络对砂轮磨损状态进行智能监测是可行的，该网络具有较强的信号模式识别能力，实验中识别率可以达到92%以上。关键词： ART2神经网络 砂轮磨损 状态识别 人工智能多传感器数据融合 AbstractIn this paper, a new method is introduced to study the artificial intelligent recognition of the grinding wheels state in automatic manufacturing process, i.e. input the multi-signal data which got by the multi-sensors into computer and abstract the special features, meanwhile fuse the data, recognize intelligently by erecting ART2 model and then give the grinding wheels state. The character, mechanism of ART2 and the method of fusing data got by multi-sensors are analyzed, at the same time the step of achieving the system is also got. Because of the born default of ART2 network, another structure is raised to overcome it by using new algorithm and frame. The result of this paper indicated that the artificial intelligent recognition to the grinding wheels state via the ART2 neural network is workable, this network has a stronger ability to recognize the signals, and the probability is up to 92%.Keywords: ART2 Neural NetworkGri