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The Fault Diagnosis of Automotive Airbag Assembly Process Based on Self-Organizing Feature Mapping Network SOM

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Automotive airbag assembly process is complex and nonlinear, and one of its characteristics is that the accuracy of making the threshold comparison for fault diagnosis using field multi-sensor measured value is not high. In this article, adopt self-organizing feature mapping network SOM to realize the fault diagnosis of automotive airbag assembly process, constitute the field function of SOM through wavelet functions, form sub-excitatory neuron to update weights, avoid SOM local optimum, and so improve the accuracy of fault diagnosis of automotive airbag assembly process.
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Keywords: EXTENSION RULE; PARALLEL ALGORITM; THEOREM PROVING

Document Type: Research Article

Publication date: 2012-03-01

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