基于FDSAF的离心泵振动信号流体噪声剔除方法研究

蒋文涛; 岳鑫; 孙亮洁; 蔡创雄; 梁荣健; 王超群; 杨群; 邹杨

doi:10.3724/j.0253-3219.2026.hjs.49.250374

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基于FDSAF的离心泵振动信号流体噪声剔除方法研究

中国核学会研究堆与新堆分会第二届学术年会优秀论文专刊 | 更新时间：2026-07-29

- 基于FDSAF的离心泵振动信号流体噪声剔除方法研究
- Fluid noise elimination in centrifugal pump vibration signals using the frequency domain spline adaptive filter
- 核技术 2026年49卷第7期文章编号：071115
- 作者机构：
  
  1.中国科学院上海应用物理研究所上海 201800
  2.中国科学院大学北京 100049
- 作者简介：
  
  蒋文涛，男，1999年出生，2021年毕业于昆明理工大学，现为博士研究生，研究领域为事故预测与风险分析
  杨群，E-mail：yangqun@sinap.ac.cn
- 基金信息：
  
  钍铀燃料循环的若干关键科学问题研究(E455890101)
- DOI：10.3724/j.0253-3219.2026.hjs.49.250374
  中图分类号： TB533.1;TN911.7
- 收稿：2025-09-29，
  
  修回：2026-01-21，
  
  网络首发：2026-07-29，
  
  纸质出版：2026-07-15
- 稿件说明：
移动端阅览
蒋文涛,岳鑫,孙亮洁等.基于FDSAF的离心泵振动信号流体噪声剔除方法研究[J].核技术,2026,49(07):071115.

JIANG Wentao,YUE Xin,SUN Liangjie,et al.Fluid noise elimination in centrifugal pump vibration signals using the frequency domain spline adaptive filter[J]. NUCLEAR TECHNIQUES,2026,49(07):071115.
蒋文涛,岳鑫,孙亮洁等.基于FDSAF的离心泵振动信号流体噪声剔除方法研究[J].核技术,2026,49(07):071115. DOI： 10.3724/j.0253-3219.2026.hjs.49.250374. CSTR： 32193.14.hjs.CN31-1342/TL.2026.49.250374.

JIANG Wentao,YUE Xin,SUN Liangjie,et al.Fluid noise elimination in centrifugal pump vibration signals using the frequency domain spline adaptive filter[J]. NUCLEAR TECHNIQUES,2026,49(07):071115. DOI： 10.3724/j.0253-3219.2026.hjs.49.250374. CSTR： 32193.14.hjs.CN31-1342/TL.2026.49.250374.

摘要

实际的离心泵信号中包含复杂的流体激励噪声，给结构故障诊断带来困难。针对离心泵振动信号中流体噪声的抑制问题，提出一种结合计算流体力学（Computational Fluid Dynamics，CFD）与频域样条自适应滤波（Frequency Domain Spline Adaptive Filter，FDSAF）的降噪方法，并进行实验验证。首先计算分析离心泵内部特定监测点的压力脉动信号，根据分析结果确定了参考噪声源与振动测点，并在测点位置采集泵壳的振动加速度信号。然后将参考噪声源的压力脉动信号作为FDSAF滤波器的参考噪声输入，剔除实测振动信号中的流体激励噪声。结果表明：所提出的结合CFD与FDSAF的降噪方法能够有效抑制振动信号中的流体激励噪声，提高结构振动特征的辨识度，为离心泵故障诊断中的数据预处理提供了一种新途径。

Abstract

Background

Vibration signals of centrifugal pumps are often contaminated by complex fluid-induced noise

which complicates structural fault diagnosis.

Purpose

This study aims to address the suppression of fluid-induced noise in centrifugal pump vibration signals by proposing and experimentally validating a noise reduction method that integrates computational fluid dynamics (CFD) with the frequency domain spline adaptive filter (FDSAF).

Methods

Firstly

vibration acceleration signals of the pump casing were collected under rated operating conditions using a centrifugal pump vibration test rig. Pressure pulsation signals in key regions inside the pump were then calculated and extracted through CFD simulations

and the correlation between vibration signals and fluid pressure pulsation signals was analyzed. Subsequently

pressure pulsation signals were employed as reference inputs for the FDSAF filter to selectively eliminate fluid-induced noise from the measured vibration signals. Finally

comparative analysis between simulation and experimental results was conducted to valid the effectiveness of the proposed method.

Results

Comparison results show that the abovementioned approach effectively suppresses fluid-induced noise in vibration signals

thereby enhancing the distinguishability of structural vibration features. After denoising

the power spectral energy near the rotational frequency (49.1 Hz) is increased by 1.85 times

while the energy near the blade-passing frequency (294.6 Hz) is reduced to 26.7% of its original value

with its amplitude decreased by 64.5%.

Conclusions

The proposed CFD-FDSAF-based method in this study provides a new pathway for data preprocessing in centrifugal pump fault diagnosis by enabling more reliable extraction of fault-related vibration features.

关键词

Keywords

references

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