DETECTION OF LEAKAGE SOUND BY USING MODULAR NEURAL NETWORKS |
|---|
| M. Kotani, K. Akazawa, S. Ozawa, H. Matsumoto |
- Abstract:
- It is important to detect the leakage of the gas to be flammable or poisonous from the cracks in pipes of petroleum refining plants or chemical plants. We examined the application of modular neural networks to the acoustic diagnosis technique for the leakage sound. The modular neural network has the ability to adapt its structure according to the environment. Experiments were performed for an artificial gas leakage device with various experimental conditions to imitate the change of environment for a long term. The discrimination accuracy with the proposed network was observed to be about 93%, which was better than 83% with the simple network. From the results, we confirmed the effectiveness for the application of the modular neural network to the detection of the leakage sound for the practical use.
- Keywords:
- acoustic diagnosis, leakage sound, neural networks
- Download:
- IMEKO-WC-2000-AI-P593.pdf
- DOI:
- -
- Event details
- Event name:
- XVI IMEKO World Congress
- Title:
Measurement - Supports Science - Improves Technology - Protects Environment ... and Provides Employment - Now and in the Future
- Place:
- Vienna, AUSTRIA
- Time:
- 25 September 2000 - 28 September 2000