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Head Gimbal Assembly circuit with vision technique and Fuzzy C-Means Clustering

机译:具有视觉技术的头部万向节装配电路和模糊C-MERIAL聚类

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In Hard Disk Drive (HDD) Industry, the automation system is the one key for manufacturing process. Head Gimbal Assembly (HGA) is a part of HDD which have the reader and writer circuit. The HGA circuit is very important for read/write process. This research proposes the new vision technique and clustering by Fuzzy C-Means algorithm for HGA circuit inspection in 3 groups. HGA circuits in 3 groups are good, bridging, and missing group. The bridging and missing groups are the defect group. Blob analysis is the one of vision technique that it can measure the properties of image. The measurement properties from blob analysis are used in clustering technique. Fuzzy C-Means Clustering is the clustering technique which is grouped the measurement data into the cluster group based on the natural grouping of data. From the experiment results of this research, the clustering performance from Fuzzy C-Means Clustering is 99.11% accuracy based on the measurement properties in blob analysis with 225 samples.
机译:在硬盘驱动器(HDD)行业中,自动化系统是制造过程的一个键。头部万向节组件(HGA)是具有读者和作者电路的HDD的一部分。 HGA电路对于读/写过程非常重要。本研究提出了新的视觉技术和集群通过模糊C型算法在3组中的HGA电路检测中的模糊C型算法。 3组中的HGA电路是好的,桥接和缺失的群体。桥接和缺失群体是缺陷组。 BLOB分析是它可以测量图像的属性的视觉技术之一。来自BLOB分析的测量特性用于聚类技术。模糊C-Means群集是基于数据的自然分组将测量数据分组为群集组的聚类技术。从本研究的实验结果来看,基于225个样品的BLOB分析中的测量性能,从模糊C均值聚类的聚类性能为99.11%。

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