The invention relates to the technical field of fault diagnosis, in particular to a tuning region fault diagnosis method based on multi-feature fusion and improved logistic regression, which comprises the following steps of: extracting time domain features from a fault signal by utilizing multi-time window analysis; a Welch algorithm is adopted to calculate a power spectrum and extract frequency domain features; fusing the time domain and frequency domain features by using an mRMR algorithm; and sending the fusion features into the improved classification model, and carrying out fault diagnosis. The method solves the problems of single fault feature type, to-be-improved feature characterization performance and high diagnosis algorithm cost during analysis of an existing method.
本发明涉及故障诊断技术领域,尤其涉及一种多特征融合及改进逻辑回归的调谐区故障诊断方法,包括:利用多时窗分析对故障信号提取时域特征;采用Welch算法计算功率谱并提取频域特征;利用mRMR算法对时域、频域特征进行融合;将融合特征送入改进分类模型中,进行故障诊断。本发明解决现有方法分析时故障特征类型单一、特征表征性能有待提升、诊断算法代价高的问题。
Tuning area fault diagnosis method based on multi-feature fusion and improved logistic regression
一种多特征融合及改进逻辑回归的调谐区故障诊断方法
2023-08-22
Patent
Electronic Resource
Chinese
Fault diagnosis system and method combining convolution auto-encoder and logistic regression
European Patent Office | 2020
|Study on Fault Diagnosis for Engine Based on Feature Fusion
Online Contents | 2010
|Elevator safety fault diagnosis method based on multi-source information fusion
European Patent Office | 2024
|