基于双尺度非均匀传声器阵列的大型装备声学故障诊断技术研究

项目名称： 基于双尺度非均匀传声器阵列的大型装备声学故障诊断技术研究

项目编号： No.51275099

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 机械、仪表工业

项目作者： 张春良

作者单位： 广州大学

项目金额： 80万元

中文摘要： 大型设备尺寸庞大、结构复杂，已有声像技术无法在有限空间与成本下重建大型设备的高分辨率声场，导致难以进行准确的故障诊断。本申请考虑到大型设备关键部位与普通部位成像分辨率要求不同等特点，针对性地提出了双尺度非均匀传声器阵列并将其用于大型设备的故障诊断。该阵列通过引入大间隔使得设备多个关键部位位于各子阵的轴线方向，以获得更高的局部分辨率。采用最小方差信号无畸变响应法、旋转不变信号参数估计法，应用双尺度非均匀传声器阵列对设备关键声源进行定位；在获得关键声源后，通过远场波束成形及局部近场声全息技术分别获取设备关键声源附近的高频与低频信息，并重建声场进行特征提取，最终应用隐马尔可夫模型、支持向量机等智能诊断方法进行故障诊断。基于双尺度非均匀传声器阵列的大型装备故障诊断方法通过对传声器资源的优化配置，重建大型设备关键部位的高分辨率声场进行故障诊断，有望提供一种新型的适合大型设备的声学故障诊断理论与方法。

中文关键词： 声学故障诊断；波达方向估计；近场声全息；传声器阵列；形态分量分析

英文摘要： Considering the special dimensions and complex structures of a large equipment, it is difficult to rebuild a high-resolution sound field for the equipment in a limited space under reasonable budget using well-known existing audio-visual technology.Based on the idea that the key and common components of a large equipment require different image resolutions, a fault diagnosis system for large equipments using two-scale non-uniform microphone array is proposed in this project. The proposed fault diagnosis system creatively introduces large intervals to ensure the key components of the equipment align in the axial direction of the sub-arrays to gain higher local resolutions. The diagnositc methodology proposed in the project is detailed as follows: Firstly, the key noise sources are located by the Minimum Variance Distortionless signal Response (MVDR) or Estimation Signal Parameters via Rotational Invariance Techniques (ESPRIT) using the signals from a two-scale non-uniform microphone array. Secondly, the high-frequency sound field information near the key noise sources is obtained by the far-field beam forming using MVDR,and the low-frequency information near the key noise sources is computed by the Patch Near-field Acoustic Holography(Patch-NAH) method. The Hidden Markov Model (HMM), Support Vector Machine (SVM)

英文关键词： Acoustic fault diagnosis；DOA estimation；Near-field acoustic holography；Microphone array；Morphological component analysis