Recovery of temperature measuring points based on compressed sensing

In the process of online 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.