CHENJiong-xi,WANGQi,ZHANFan,et al.A Method for Identifying Leakage Acoustic Signals in Water Supply Network Based on CNN with MFCC[J].China Water & Wastewater,2024,40(23):13-19.
A Method for Identifying Leakage Acoustic Signals in Water Supply Network Based on CNN with MFCC
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第40卷
Number:
第23期
Page:
13-19
Column:
Date of publication:
2024-12-01
- Keywords:
- water supply network; leakage identification; acoustic signal; convolutional neural network; MFCC
- Abstract:
- Aiming at the problems of low efficiency and strong dependence on artificial experience in leakage identification of water supply network, a leakage acoustic signal identification method of water supply network was proposed based on convolutional neural network (CNN) and Mel frequency cepstral coefficient (MFCC). MFCC and its first- and second-order differences were extracted from the leakage sound signals collected by noise recorders and water sound sensors as leakage sound signal features. Feature images containing leakage features were obtained and input into a CNN model. After hyperparameter optimization, the leakage identification model was finally obtained. The results showed that using the combination of MFCC and its first-order differential feature parameters as input features to train the model yielded the best identification performance, with a test set accuracy of 95.26% and an F1 score of 89.22%, demonstrating excellent leakage identification ability.
Last Update:
2024-12-01