带式输送机托辊轴承声信号增强方法

游卿华; 伍鹏; 马波

doi:10.13272/j.issn.1671-251x.2024120083

带式输送机托辊轴承声信号增强方法

游卿华^{1, 2,},
伍鹏^{1, 2},
马波^{1, 2}

1.
北京化工大学机电工程学院，北京　100029
2.
北京化工大学高端机械装备健康监控与自愈化北京市重点实验室，北京　100029

基金项目:

国家自然科学基金项目（62273025）。

详细信息

作者简介:
游卿华（1999—），男，河南开封人，硕士研究生，主要研究方向为设备状态监测与诊断，E-mail：13126635083@163.com

中图分类号: TD634.1
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- 文章访问数: 30
- HTML全文浏览量: 4
- PDF下载量: 4
出版历程
- 收稿日期: 2024-12-30
- 修回日期: 2025-03-04
- 网络出版日期: 2025-02-27
- 刊出日期: 2025-03-14

Acoustic signal enhancement method for belt conveyor idler bearings

YOU Qinghua^{1, 2,},
WU Peng^{1, 2},
MA Bo^{1, 2}

1.
College of Mechanical and Electrical, Beijing University of Chemical Technology, Beijing 100029, China
2.
Beijing Key Laboratory of Health Monitoring and Self-Recovery for High-End Mechanical Equipment, Beijing University of Chemical Technology, Beijing 100029, China

摘要

摘要:
针对目前带式输送机托辊轴承声信号增强方法存在过度降噪导致信号失真、适应性差，提取复杂声场特征效果较差等问题，提出一种基于直方图噪声估计和维纳滤波的带式输送机托辊轴承声信号增强方法。首先，计算轴承声信号各频带功率谱，构建功率谱直方图进行噪声谱估计，并对噪声谱进行一阶递归平滑；其次，利用噪声谱估计计算维纳滤波增益函数，得到维纳滤波降噪后的声信号；然后，对降噪后的声信号进行包络谱分析，通过对比实际测得的故障特征频率和理论的故障特征频率，实现对带式输送机托辊轴承故障诊断。实验和现场测试结果表明：基于直方图噪声估计和维纳滤波的带式输送机托辊轴承声信号增强方法得到的包络谱中含有明显的故障频率及其倍频成分，实验数据信噪比至少提升了1.14 dB，现场数据信噪比至少提升了1.04 dB，轴承故障特征提取效果较好，可实现环境噪声干扰严重下的带式输送机托辊轴承声信号增强。
- 带式输送机 /
- 托辊轴承 /
- 声信号增强 /
- 直方图噪声估计 /
- 维纳滤波
Abstract:
To address the issues in existing acoustic signal enhancement methods for belt conveyor idler bearings, such as excessive noise reduction leading to signal distortion, poor adaptability, and ineffective extraction of complex sound field characteristics, a method based on histogram noise estimation and Wiener filtering was proposed. First, the power spectrum of each frequency band of acoustic signal was computed, and a power spectrum histogram was constructed to estimate the noise spectrum, followed by first-order recursive smoothing of the noise spectrum. Next, the estimated noise spectrum was used to calculate the Wiener filter gain function, obtaining the noise-reduced acoustic signal. Then, envelope spectrum analysis was performed on the denoised acoustic signal. By comparing the measured fault characteristic frequencies with theoretical fault characteristic frequencies, fault diagnosis of the belt conveyor idler bearing was achieved. Experimental and field test results show that the proposed acoustic signal enhancement method, based on histogram noise estimation and Wiener filtering, produces an envelope spectrum containing distinct fault characteristic frequencies and their harmonic components. The signal-to-noise ratio (SNR) of the experimental data improved by at least 1.14 dB, while the SNR of the field data improved by at least 1.04 dB. The method demonstrates good performance in extracting bearing fault features and can effectively enhance acoustic signals for belt conveyor idler bearings under severe environmental noise interference.
- belt conveyor /
- idler bearing /
- acoustic signal enhancement /
- histogram noise estimation /
- Wiener filtering

HTML全文

图 1 基于直方图噪声估计和维纳滤波的带式输送机托辊轴承故障诊断流程

Figure 1. Process of belt conveyor idler bearing fault diagnosis based on histogram noise estimation and Wiener filtering

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图 2 带式输送机托辊轴承故障诊断实验台

Figure 2. Test bench for fault diagnosis of belt conveyor idler bearing

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图 3 实验台和麦克风阵列示意图

Figure 3. Schematic of the test bench and microphone array

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图 4 内圈故障原始波形

Figure 4. Original waveform of inner ring fault

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图 5 内圈故障降噪后波形

Figure 5. Waveform of inner ring fault after noise reduction

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图 6 内圈故障原始包络谱

Figure 6. Original envelope spectrum of inner ring fault

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图 7 内圈故障降噪后包络谱

Figure 7. Envelope spectrum of inner ring fault after noise reduction

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图 8 文献[8]方法处理后的内圈故障包络谱

Figure 8. Envelope spectrum of inner ring fault after processing with method in reference [8]

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图 9 文献[9]方法处理后的内圈故障包络谱

Figure 9. Envelope spectrum of inner ring fault after processing with method in reference [9]

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图 10 文献[13]方法处理后的内圈故障包络谱

Figure 10. Envelope spectrum of inner ring fault after processing with method in reference [13]

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图 11 现场信号原始包络谱

Figure 11. Original envelope spectrum of on-site signal

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图 12 现场信号降噪后包络谱

Figure 12. Envelope spectrum of on-site signal after noise reduction

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表 1 故障模拟实验参数

Table 1 Parameters of fault simulation test

参数	数值	参数	数值
输入转速/（r·min⁻¹）	360	麦克风间距/m	2
采样频率/Hz	128 00	麦克风高度/m	0.35
采样点数/个	8 192	阵列距托辊垂直距离/m	1.2
阵列麦克风数量/个	5

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表 2 轴承加工缺陷和故障信息

Table 2 Bearing manufacturing defects and fault information

故障类型	缺陷数量/条	缺陷尺寸/mm	缺陷频率/Hz
外圈故障	4	1×1	18.44
内圈故障	2	1×1	29.57

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表 3 实验数据降噪后信号和原始信号的信噪比

Table 3 Signal-to-noise ratio of denoised and original signals in test data

组别	信噪比/dB
组别	本文方法	文献[8]方法	文献[9]方法	文献[13]方法	原始信号
1	2.46	2.19	2.25	1.97	1.32
2	2.38	1.94	2.18	1.89	1.25
3	2.55	2.25	2.21	2.07	1.48

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表 4 现场数据降噪后信号和原始信号的信噪比

Table 4 Signal-to-noise ratio of denoised and original signals in on-site data

组别		信噪比/dB
组别	本文方法	文献[8]方法	文献[9]方法	文献[13]方法	原始信号
1	2.91	2.58	2.76	2.44	1.92
2	2.73	2.53	2.55	2.48	1.84
3	2.80	2.61	2.63	2.51	1.76

下载: 导出CSV

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