基于改进Split Bregman的电容层析成像滑油监测研究

Lubricating Oil Monitoring Based on Improved Split Bregman of Electrical Capacitance Tomography

关键词:  滑油监测  电容层析成像  滑油系统  图像重建算法  L_p范数

Key words:  Lubricating oil monitoring  Electrical capacitance tomography  Lubricating oil system  Image reconstruction algorithm  L_p norm

摘要:

针对电容层析成像（Electrical capacitance tomography，ECT）技术应用于滑油系统磨粒在线监测时，其图像重建过程中存在的不适定性问题，提出了一种基于迭代p阈值函数的Split Bregman（SB）图像重建算法。首先，建立基于SB算法的ECT图像重建模型。其次，建立基于L_p范数的SB模型。最后，为更方便求解L_p范数的阈值迭代形式，引入了p阈值函数。通过灵活选取p值，提高了SB算法的精度和适用性。仿真实验结果表明，与Landweber，Tikhonov正则化和SB算法相比，改进SB算法图像误差降低了约30%，相关系数高达0.96，成像速度与Landweber成像速度相近。实验结果表明，改进SB算法能够胜任滑油系统磨粒监测任务，并提高了成像质量。

Abstract:

Aiming at the ill-posedness in the image reconstruction process of Electrical Capacitance Tomography （ECT）， when it is applied to the online wear debris monitoring in the lubricating oil system， a Split Bregman （SB） image reconstruction algorithm based on iterative p-threshold function is proposed. Firstly，the ECT image reconstruction model based on SB algorithm is established.Secondly，the SB model based on L_p norm is established.Finally，in order to more conveniently solve the threshold iteration form of L_p regularization，a p-threshold function is introduced.By choosing the p value flexibly，the accuracy and applicability of the SB algorithm are improved. Simulation results show that compared with Landweber，Tikhonov regularization and SB algorithm，the image error of improved SB algorithm is reduced by about 30%，the correlation coefficient is up to 0.96，and the imaging speed is similar to that of Landweber.The experimental results show that the improved SB algorithm can be competent for the image reconstruction task and improves the imaging quality.