Application of adaptive network based fuzzy inference system for model reconstruction in reverse engineering
Combining fuzzy neural network and laser surface data measurement, a novel model reconstruction methodology is presented. This model reconstruction scheme includes two main parts, one is surface data measurement system, and the other one is model reconstruction algorithm. The surface data me...
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| 第一著者: | |
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| フォーマット: | Book Section |
| 言語: | English |
| 出版事項: |
World Scientific Publishing
2004
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| 主題: | |
| オンライン･アクセス: | http://eprints.intimal.edu.my/320/1/1.pdf http://eprints.intimal.edu.my/320/ |
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| 要約: | Combining fuzzy neural network and
laser surface data measurement, a novel
model reconstruction methodology is
presented. This model reconstruction
scheme includes two main parts, one is
surface data measurement system, and
the other one is model reconstruction
algorithm. The surface data
measurement system consists of a vision
system with a smart laser camera and a PC computer. The system is developed
to measure data for freeform surface
with complex shape. Using an Adaptive
Network based Fuzzy Inference System
(ANFIS), the model reconstruction
algorithm is designed. For demonstrating
the effectiveness of the presented
scheme, a group points cloud data with
good accuracy. This is measured by the
presented data measurement system for
an existing part and is taken as data
sample for training the ANFIS. The
trained ANFIS is taken as surface data
model. By comparing the surface data,
which is from trained ANFIS, with the
data sample value, it can be found that
the ANFIS model can match the real
surface very well. |
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