Compressed sampling of gearbox oil temperature signal based on an improved intrinsic mode function basis mixed-dictionary

• Published in: Measurement : journal of the International Measurement Confederation 2023-08, Vol.218, p.113138, Article 113138
• Main Authors: Lei, Wei, Zhe, Cheng, Junsheng, Cheng, Niaoqing, Hu, Yi, Yang
• Format: Article
• Language: English
• Subjects: Aperiodic gearbox oil temperature signal; Compressed sensing; Improved mixed-dictionary K-SVD; Intrinsic mode function basis; Measurement matrix
• ISSN: 0263-2241
• DOI: 10.1016/j.measurement.2023.113138

•The IMDK-SVD for the compressed sampling of signal under variable working states is proposed.•A dual-scale similarities competitive agglomeration (CA) algorithm is used for the clustering of the signal segment.•A measurement matrix with variable-step sampling is designed.•Simulation and experimental results show the effectiveness of the method. The oil temperature signal of gearbox is always redundant in long-term use, which will occupy a lot of computer storage space. An improved intrinsic mode function basis mixed-dictionary K-singular value decomposition (IMDK-SVD) algorithm for compressed sampling of the aperiodic oil temperature signal is proposed. Firstly, an improved mixed-dictionary is designed for sparse representation of the aperiodic oil temperature signal, this mixed-dictionary is composed of a class-specific dictionary that extracts the commonness of the same group of data and a shared dictionary that extracts the difference of the different group of data. Secondly, the measurement matrix with variable-step sampling is proposed, and the sampling points is adaptively determined by the information entropy index of signal. Benefitting from these improvements, the advantages of high reconstruction accuracy and saving sampling points as possible are achieved, and the effectiveness of proposed method is verified based on the simulation signal and the experimental signal.