Journal of Jilin University (Information Science Edition) ›› 2025, Vol. 43 ›› Issue (2): 309-316.
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ZHANG Zhao
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Abstract: In order to ensure the normal operation of the ventilator, an intelligent monitoring method for the operating status of the ventilator based on the HHT(Hilbert-Huang Transform) algorithm is proposed. Firstly,wavelet neural network is used to denoise the running signal of the ventilator; Secondly, combined with the HHT algorithm, the denoised ventilator operation signal is decomposed by EMD(Empirical Mode Decomposition), and the decomposed IMF( Intrinsic Mode Functions) component is transformed by Hilbert spectrum to obtain the signal spectrum as the signal feature. Finally, the obtained signal spectrum is placed in the MLP neural network classifier, and the backpropagation algorithm is used to train the MLP neural network to achieve recognition of the operating status of the ventilator. The experimental results show that the proposed method has a good denoising effect, and the monitored results are consistent with the actual spectrum. At the same time, the sensitivity of monitoring is above 96% , and the accuracy of operating status recognition is above 95% . This indicates that the proposed method can effectively monitor the operating status of the ventilator and has good monitoring performance.
Key words: Hilbert-Huang transform(HHT) algorithm, the operating status of the ventilator, wavelet neural network, empirical mode decompostion ( EMD), Hilbert spectral transformation, multi-layer perceptron(MLP) neural network classifier
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ZHANG Zhao. Intelligent Monitoring Method for Ventilator Operation Status Based on HHT Algorithm[J].Journal of Jilin University (Information Science Edition), 2025, 43(2): 309-316.
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http://xuebao.jlu.edu.cn/xxb/EN/Y2025/V43/I2/309
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