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Research Papers

Optimal Sensor Location in Laminated Die System

[+] Author and Article Information
Jaho Seo, Amir Khajepour

Jan P. Huissoon

Department of Mechanical and Mechatronics Engineering,  University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada N2L 3G1jph@mecheng1.uwaterloo.ca

J. Dyn. Sys., Meas., Control 134(2), 021013 (Jan 12, 2012) (15 pages) doi:10.1115/1.4005035 History: Received February 25, 2010; Revised June 09, 2011; Published January 11, 2012; Online January 12, 2012

The objective of this research is to identify optimal temperature sensor locations in a laminated die system for the purpose of predicting the temperature distribution throughout the die to control heating and cooling rates. Potential locations (referred to as target nodes) are grouped based on the similarity of their thermal response using both K-means and a proposed temperature ratio clustering method. A sensitivity analysis of the temperature distribution for these groups of target nodes identifies the sensor location for each cluster that exhibits the highest sensitivity to variable inputs. A comparison of sensor locations identified by each clustering method with the sensitivity analysis is presented and is used to evaluate the optimal sensor location in terms of consistency in generating these sensor locations, the degree of sensitivity, the mutual interaction through principal component analysis, limiting the number of sensors, and the accuracy in estimating the temperature distribution.

Copyright © 2012 by American Society of Mechanical Engineers
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References

Figures

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Figure 21

Experimental validation results (error between Yfea and Yexp)

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Figure 18

Experimental setup

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Figure 17

Schematic of NARX model

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Figure 16

Randomly chosen sensor locations (Type 1 and Type 2) used for temperature estimation ((a): top view and (b): rear view)

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Figure 15

Nodes requiring the estimation of temperature response using sensor locations ((a): top view and (b): rear view)

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Figure 14

Optimal sensor locations with temperature ratio in the cases of k = 6 (a) and k = 8 (b)

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Figure 8

Temperature distributions with +5% and −5% change in the water temperature (a) and sensitivity coefficient value of temperature to the water temperature (b) at node B

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Figure 7

Temperature distributions with +5% and −5% change in the flow rate (a) and sensitivity coefficient value of temperature to the flow rate (b) at node B

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Figure 6

Temperature distributions through the first FEA at node A and B

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Figure 5

Monitored nodes of mould (side view (a) and top view (b))

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Figure 4

Input conditions for the first FEA

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Figure 3

Mesh model for mould with conformal cooling channel

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Figure 2

Half view of a laminated die (a) with conformal cooling channel (b)

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Figure 1

Laminated object manufacturing

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Figure 20

Experimental validation results (comparison between FEA model (Yfea) and actual outputs (Yexp))

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Figure 19

Input conditions (flow rate change) for experimental test

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Figure 13

Optimal sensor locations with temperature ratio in the cases of k = 2 (a) and k = 4 (b)

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Figure 12

Optimal sensor locations with K-means in the cases of k = 6 (a) and k = 8 (b)

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Figure 11

Optimal sensor locations with K-means in the cases of k = 2 (a) and k = 4 (b)

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Figure 10

Silhouette plots in the cases of k = 6 (a) and k = 8 (b)

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Figure 9

Silhouette plots in the cases of k = 2 (a) and k = 4 (b)

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