基于机械声场时空全息诊断模型的弱故障特征提取研究

项目名称： 基于机械声场时空全息诊断模型的弱故障特征提取研究

项目编号： No.51505433

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 机械、仪表工业

项目作者： 侯俊剑

作者单位： 郑州轻工业学院

项目金额： 20万元

中文摘要： 噪声诊断由于其非接触测量的优点，成为故障诊断技术重要分支之一。然而，目前基于单点测试的常规声诊断技术和基于阵列测试的声像诊断技术都仅以声场某个点和某个面为研究对象，对于一些机械局部弱故障工况存在信号信噪比和诊断鲁棒性差等问题。针对这些问题，本项目通过构建声场全息诊断模型和提取声场动态时空特征，实现机械微弱故障的有效诊断。首先通过对机械声场采用阵列测量和近场声全息技术，把源像相位信息映射到时空域，获得时空序列声像样本空间，并综合考虑序列声像的信息量、相关性和信息熵等信息冗余指标，选定最优时空分辨率，构建蕴含时空关联信息的声场全息诊断模型；然后基于声场模型的时空属性，引入视频和地质空间领域数据处理分析技术，如主成分、空间谱、时空切片流形和空间张量分析等，提取蕴含时空关联信息的声场弱故障特征进行诊断。本项目直接以高维全息声场信息进行诊断，融合多维度特征提升诊断鲁棒性，为声诊断技术提供新的思路。

中文关键词： 声学故障诊断；时空特征；数据融合；近场声全息；主成分分析

英文摘要： The acoustic-based diagnosis (ABD) technique is an important developing tendency of fault diagnosis technology. Sound field is a three-dimensional space which contains the temporal-spatial attributes. The conventional ABD technique uses the information at one point in the sound field for fault diagnosis, and the new developed acoustic image based fault diagnosis uses the local characteristics on the source surface for fault diagnosis, by which the sound field characteristics are not fully utilized and poor robustness are obtained in some local weak fault conditions. In order to improve the problems, the sound field containing temporal-spatial attributes is modeled and its high dimensional characteristics are applied to diagnostic analysis directly. The array measurement and the near field acoustic holography (NAH) techniques are employed in the sound field. The phase information at the source surface is mapped to time-space domain, and a series of dynamic time-space sequence image models with different temporal-spatial resolutions are obtained. The optimum temporal-spatial resolution is selected by considering the information redundancy index of the sequence image, such as information content, correlation and information entropy. And then the high dimensional sound field diagnosis model containing the temporal-spatial correlation information is constructed. The feature processing techniques in video and spatial fields are adopted to extract the temporal-spatial characteristics of the sound field diagnosis model, such as principal components analysis (PCA), spatial spectrum, temporal-spatial slice manifold and space tensor. Since the changes of sound pressure distribution and temporal-spatial correlation information are considered altogether, the diagnosis robustness is improved. And due to the application of temporal-spatial characteristics, the acoustic diagnosis procedure is replaced by space target recognition, which expands the application scope of acoustic imaging technique and provides a new idea and option for ABD.

英文关键词： Acoustic-Based Diagnosis Technique;Temporal-Spatial Characteristics;Data Fusion;Near Field Acoustic Holography; Principal Components Analysis