Paper Info
Title
Recovery Of Temperature Measuring Points Based On Compressed Sensing
Abstract
In the process of on-line monitoring the temperature measuring points of CNC machine tools, the sensing data are usually missing or abnormal because of sensor or transmission failure. To recover the abnormal temperature measuring points, a recovery method based on compressed sensing is proposed. The method uses K-SVD algorithm to carry out dictionary learning with the large amount of temperature monitoring data to obtain the over-complete dictionary, and then the mutual coherence is used to constructs the observation matrix that is suitable for the data type. Finally the OMP algorithm is used to realize the recovery of the temperature measuring points. In this paper, the method is applied to the recovery of spindle temperature measuring points of heavy CNC machine tools. Experiments under different working conditions show that the method can achieve good recovery results.
Year
Venue
Keywords
2018
2018 IEEE 15TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC)
compressed sensing, recovery of temperature measuring points, K-SVD algorithm, OMP algorithm
Field
DocType
ISSN
Numerical control,Computer science,Sensing data,Control engineering,Real-time computing,Data type,Observation matrix,Temperature measurement,Mutual coherence,Compressed sensing,Sparse matrix
Conference
1810-7869
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Xue-Mei Jiang1254.03
Ya Xu200.68
Xiaomei Zhang3179.13
Junwei Yan401.01
Jiwei Hu5265.82
Ping Lou655.54