ZhangYang,GuoJun,AnLiang,et al.Leakage Noise Detection in Urban Water Supply Pipelines Based on Fine-tuning Qwen Multimodal Large Model[J].China Water & Wastewater,2026,42(17):41-47.
Leakage Noise Detection in Urban Water Supply Pipelines Based on Fine-tuning Qwen Multimodal Large Model
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第42卷
Number:
第17期
Page:
41-47
Column:
Date of publication:
2026-09-01
- Keywords:
- water supply pipeline; leakage detection; large language model; model fine-tuning; adaptive filtering; time-frequency analysis
- Abstract:
- With the acceleration of urbanization, the problem of leakage in urban water supply pipelines has become increasingly severe. Traditional acoustic detection methods suffer from low efficiency, high false-alarm rates, and a lack of transparent analysis procedures. The large language model has intelligent analysis and discrimination capabilities, therefore a water supply pipeline leakage noise intelligent detection method based on fine-tuning the Qwen multimodal large-scale model is proposed. An adaptive line spectral enhancement algorithm is applied to the raw noise signals for filtering and preprocessing, which effectively suppresses environmental interference. The filtered signals are then converted into short-time Fourier transform (STFT) time-frequency spectrograms, and combined with the five-dimensional leakage-noise feature vectors to construct a multimodal dataset. Experimental results demonstrated that the accuracy of model after fine-tuning reached 77.75%, and the specificity was improved from 0.36% to 86.12%, significantly optimizing the discrimination between leakage and environmental noise. This method selected the Qwen2-7B multimodal large model with fewer parameters and employed the LoRA technique for fine-tuning to effectively enhance the classification accuracy of leakage noise. Simultaneously, it could output a detailed analytical process, providing interpretable decision support for technicians.
Last Update:
2026-09-01