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Neural Network Based egg breakage detection

Author: ZuoChangXin
Tutor: HuangYaoZhi
School: Fuzhou University
Course: Mechanical Manufacturing and Automation
Keywords: Egg breakage detection Pattern Recognition More Incentives Signal Processing Neural Network
CLC: TP183
Type: Master's thesis
Year: 2002
Downloads: 67
Quote: 3
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Abstract


In this paper, the production of egg egg breakage detection process automation has been studied and discussed. Vibration modes of the system and the structure of the relationship as well as neural networks in pattern recognition combined using a computer to complete the egg instead of doing classification model and implementation. Firstly, on the current production of eggs in egg breakage detection profile , and then determine the content of this study , methods and purposes. This produced a driver apparatus for generating a sound signal excitation egg , made ​​according to different frequency components of the sound excitation methods to identify eggs . Egg excite sound mainly concentrated in low frequency , so choose the low frequency with a good frequency response characteristics of the microphone and the amplifier circuit ; amplified output signal through the A / D acquisition board is converted into a corresponding voltage value of the signal into the computer , the discrete fourier transform of the signal data to get it to the band spectrum and energy distribution ; while after the energy distribution characteristic data as a neural network input value , so that the good eggs and broken egg model is established . The author VB6.0 programming language neural network programming and interface design , neural network algorithm uses a wider application of BP algorithm . BP algorithm thesis expounded the advantages and disadvantages , and how to accelerate the training and avoid falling into the local minimum to do some discussion . Finally learning model using two egg weights and use the proceeds to achieve classification .

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Artificial Neural Networks and Computing
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