Online Inspection for Glass Fiber Forming

[+] Author and Article Information
Paul P. Lin

Department of Mechanical Engineering, Cleveland State University, Cleveland, OH 44115-2214p.lin@csuohio.edu

Qing Guo

Department of Mechanical Engineering, Cleveland State University, Cleveland, OH 44115-2214

Xiaolong Li

Department of Biomedical and Chemical Engineering, Cleveland State University, Cleveland, OH 44115-2214

J. Manuf. Sci. Eng 129(1), 164-171 (Aug 31, 2006) (8 pages) doi:10.1115/1.2375138 History: Received June 23, 2005; Revised August 31, 2006

Glass fiber forming is a complicated process in which many factors could affect the quality of fibers. The forming machine has many fiber-forming tubes that are close to each other and arranged in several layers. The closeness results in inadequate lighting and unwanted video signals. An anti-causal zero-phase filter was employed to remove noise with insignificant pixel location shift or distortion. In addition to the noise, the unwanted video signals constantly moving from one place to another also presented a challenge in image analysis. These signals were identified by a trained neural network that classified patterns. The unwanted signal identification through instant pattern classification made online inspection possible. During the fiber drawing process, the diameters of glass forming tubes and the profiles of glass melting cones were closely monitored and measured online in order to control the final fiber diameter. The accurate diameter measurements were accomplished by the noise removal along with a subpixel-resolution based edge detection technique. The results thus obtained for noise removal and unwanted video signals identification were quite good. The fiber diameter measurements were performed online, and the entire inspection process was automated with the aid of a programmable logic controller.

Copyright © 2007 by American Society of Mechanical Engineers
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Figure 1

The glass forming inspection system

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Figure 2

Array of forming tubes and forming cones

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Figure 3

The top view of glass forming tubes and camera

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Figure 4

Tube with inadequate lighting and an unwanted cone

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Figure 5

Tube with better lighting and an unwanted cone

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Figure 6

Intensity profile of a scanned image line

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Figure 7

Processing scheme of Z transform

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Figure 8

Intensity profile comparison before and after applying the FIR and ACZP filters

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Figure 9

Three types of crest

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Figure 10

Three types of trough

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Figure 11

Valley modeled by a triangle

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Figure 12

The forming tube with key positions

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Figure 13

Left and right edges of the glass forming tube

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Figure 14

(a) Light intensity across an edge; (b) light intensity difference across an edge

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Figure 15

Example of edge detection

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Figure 16

Intensity profile with two valleys and one peak

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Figure 17

Intensity profile with two valleys and three peaks

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Figure 18

An array of glass melting cones

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Figure 19

Four sections of the cone image



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