A study of sound recognition algorithm for power plant equipment fusing MFCC and IMFCC features

Hao Zhang; Zengtao Zhao; Fanqi Huang; Liehao Hu

doi:10.1117/12.2681350

8 June 2023 A study of sound recognition algorithm for power plant equipment fusing MFCC and IMFCC features

Hao Zhang, Zengtao Zhao, Fanqi Huang, Liehao Hu

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127073A (2023) https://doi.org/10.1117/12.2681350
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

The current traditional deep learning-based sound recognition algorithm achieves the classification and recognition of sound by constructing MLP models, which leads to a large computational effort and low sound recognition rate due to the lack of dimensionality reduction processing of sound signal features. In this regard, we propose the study of sound recognition algorithm for power plant equipment by fusing MFCC and IMFCC features. Pre-processing such as pre-emphasis, normalization and framing of the sound signal is performed, and a decentralized approach is used to realize the dimensionality reduction of the sound signal features and achieve the recognition of power plant equipment sounds. In the experiments, the average recognition rate of the proposed algorithm is verified. The analysis of the experimental results shows that the sound recognition algorithm constructed by the proposed method has a high average recognition rate and a good recognition effect.

Citation Download Citation

Hao Zhang, Zengtao Zhao, Fanqi Huang, and Liehao Hu "A study of sound recognition algorithm for power plant equipment fusing MFCC and IMFCC features", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127073A (8 June 2023); https://doi.org/10.1117/12.2681350

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