Analytic Wavelet-Based Ultrasonic Pulse Differentiation for Injection Mold Cavity Pressure Measurement

[+] Author and Article Information
Li Zhang

Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA 01003

Charles B. Theurer

Pervasive Decisioning Systems Lab, GE Global Research Center, Niskayuna, NY 12309

Robert X. Gao1

Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA 01003gao@ecs.umass.edu

David O. Kazmer

Department of Plastics Engineering, University of Massachusetts, Lowell, MA 01854


To whom correspondence should be addressed.

J. Manuf. Sci. Eng 128(1), 370-374 (Jul 20, 2005) (5 pages) doi:10.1115/1.2123048 History: Received June 15, 2004; Revised July 20, 2005

A new signal-processing technique based on analytic wavelet transform has been developed for detecting and differentiating temporally overlapped ultrasonic pulse trains that carry spatially distributed pressure information across an injection mold cavity. Compared to conventional wavelets that have a constant relative bandwidth at all the scales, the analytic wavelets investigated in this paper feature variable relative bandwidth, making it possible to simultaneously match the frequency characteristics of the ultrasonic pulse trains transmitted from the mold-embedded pressure sensors. As a result, more accurate detection and differentiation of the temporal and spectral information embedded within the ultrasonic pulse trains could be achieved. Theoretical framework for the analytic wavelet transform was established, and a multichannel ultrasonic pulse detector based on the complex Morlet wavelet was designed and experimentally investigated. The results have confirmed the effectiveness of the new signal-processing technique for on-line pressure sensing for injection molding process monitoring.

Copyright © 2006 by American Society of Mechanical Engineers
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Figure 1

Sensing principle and the sensor array arrangement in an injection mold

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Figure 2

Limitation of a one-dimensional enveloping technique

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Figure 3

Analysis windows for STFT, conventional CWT, and wavelet transforms with variable relative bandwidth

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Figure 4

Multichannel pulse detector based on the complex Morlet wavelet

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Figure 5

Detection and differentiation of six timely and spectrally adjacent pulse trains

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Figure 6

Detection and differentiation of two pulse trains that are timely overlapped and spectrally adjacent and two pulse trains that are timely adjacent but spectrally identical

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Figure 7

Experimental detection of ultrasonic pulse trains having the same center frequency

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Figure 8

Experimental detection and differentiation of temporally overlapped and spectrally adjacent ultrasonic pulse trains generated by three transmitters




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