Automated Diagnosis of Faults in Rotating Machinery using Adaptive Network Based Fuzzy Inference

基于自适应网络模糊推理的旋转机械故障自动诊断工程资产的长期完整性取决于它们的维护质量，在澳大利亚，维护质量每年高达数十亿美元。该项目旨在开发一种新的基础自动化技术，用于检测和诊断机械故障。创新之处在于该技术不依赖于离散小波包分析中故障分量的知识。迄今为止开展的所有其他工作取决于对这些组成部分及其位置的了解。这项工作的结果将极大地改善工厂和工业资产维护中昂贵的基于人工的诊断程序。

Automated Diagnosis of Faults in Rotating Machinery using Adaptive Network Based Fuzzy Inference. The long-term integrity of engineering assets depends on the quality of their maintenance which runs into billions of dollars per year in Australia. This project aims to develop a new fundamental automated technique for the detection and diagnosis of machinery faults. The innovation lies in the ability of this technique to not depend on knowledge of fault components in the discrete wavelet packet analysis. All other work conducted to date depends on knowledge of these components and their location. The results of this work will vastly improve the costly manually based diagnostics procedures in the maintenance of plant and industrial assets.