State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring

Haotian Zheng; Zhixi Zhang; Guangyan Wang; Yatao Wang; Jun Liang; Weiyi Su; Yuqi Hu; Xiong Yu; Chunli Li; Honghai Wang

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State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring

Updated：2026-01-06

- State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring
- State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring
- 中国化学工程学报（英文版） 2025年77卷第1期页码：248-258
- Affiliations：
  
  1. School of Chemical Engineering and Technology, National-Local Joint Engineering Laboratory for Energy Conservation in Chemical Process Integration and Resources Utilization, Hebei University of Technology,Tianjin,China,300130
  2. School of Information Engineering, Tianjin University of Commerce,Tianjin,China,300134
  3. Coal Chemical R&D Center of Kailuan Group,Tangshan,China,063007
- Author bio：
- Funds：
- DOI：
  中图分类号：
- 纸质出版：2025
- Accepted：
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Haotian Zheng, Zhixi Zhang, Guangyan Wang, 等. State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring[J]. 中国化学工程学报（英文版）, 2025,77(1):248-258.

Haotian Zheng, Zhixi Zhang, Guangyan Wang, Yatao Wang, Jun Liang, Weiyi Su, Yuqi Hu, Xiong Yu, Chunli Li, Honghai Wang. State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring[J]. Chinese Journal of Chemical Engineering, 2025, 77(1): 248-258.
Haotian Zheng, Zhixi Zhang, Guangyan Wang, 等. State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring[J]. 中国化学工程学报（英文版）, 2025,77(1):248-258. DOI：

Haotian Zheng, Zhixi Zhang, Guangyan Wang, Yatao Wang, Jun Liang, Weiyi Su, Yuqi Hu, Xiong Yu, Chunli Li, Honghai Wang. State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring[J]. Chinese Journal of Chemical Engineering, 2025, 77(1): 248-258. DOI：

摘要

Abstract

The operational state of distillation columns significantly impacts product quality and production efficiency. However

due to the complex operation and diverse influencing factors

ensuring the safety and efficient operation of the distillation columns becomes paramount. This research combines passive acoustic monitoring with artificial intelligence techniques

proposed a technology based on residual network (ResNet)

which involves the transformation of the acoustic signals emitted by three distillation columns under different operating states. The acoustic signals were initially in one-dimensional waveform format and then converted into two-dimensional Mel-Frequency Cepstral Coefficients spectrogram database using fast Fourier transform. Ultimately

this database was employed to train a ResNet for the purpose of identifying the operational states of the distillation columns. Through this approach

the operational states of distillation columns were monitored. Various faults

including flooding

entrainment

dry-tray

etc

were diagnosed with an accuracy of 98.91%. Moreover

an intermediate transitional state between normal operation and fault was identified and accurately recognized by the proposed method. Under the transitional state

the acoustic signals achieved an accuracy of 97.85% on the ResNet

which enables early warnings before faults occur

enhancing the safety of chemical production processes. The approach presents a powerful tool for the mon

itoring and diagnosis of chemical equipment

particularly distillation columns

ensuring the safety and efficiency.

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