scholarly journals Video coding using a deformation compensation algorithm based on adaptive matching pursuit image decompositions

Author(s):  
O. Divorra Escoda ◽  
P. Vandergheynst
2019 ◽  
Vol 141 (2) ◽  
Author(s):  
Wenjun Wu ◽  
Yuemin Wang

Due to the multimodal and dispersive characteristics of guided waves, guided wave testing signals are always overlapped and difficult to separate for correct interpretations. To this end, a simplified dispersion compensation algorithm is put forward in this paper. The dispersion elimination is accomplished by compensating the second-order nonlinear phase shift of guided wave signals, which is the cause of the dispersion when narrow band exciting signals are used. This algorithm is easy to implement and has no need of prior knowledge of the guided wave dispersion relationship. Considering that the center frequency, which is a key parameter for this algorithm, is nearly impossible to determine accurately in practical applications, the effect of the center frequency deviation on the algorithm is further studied. Both theoretical analysis and numerical simulation indicate the insensitivity of the algorithm to the deviation of the center frequency, and hence, there is no need to determine the center frequency accurately, facilitating the practical use of the algorithm. Based on this simplified dispersion compensation algorithm and in cooperation with the matching pursuit method, the mode separation is further performed for interpreting of overlapped guided wave signals. Dispersion compensation is first applied to the testing signal with respect to a certain mode which will compress the waveform of the mode while the others still spread. Then, this compressed waveform is separated with the Gabor based matching pursuit method. Both simulation and experiment are designed to demonstrate the effectiveness of the proposed methods.


2018 ◽  
Vol 9 (1) ◽  
pp. 65 ◽  
Author(s):  
Guozhi Li ◽  
Fuhai Zhang ◽  
Yili Fu ◽  
Shuguo Wang

As the application of industrial robots is limited by low stiffness that causes low precision, a joint stiffness identification algorithm for serial robots is presented. In addition, a deformation compensation algorithm is proposed for the accuracy improvement. Both of these algorithms are formulated by dual quaternion algebra, which offers a compact, efficient, and singularity-free way in robot analysis. The joint stiffness identification algorithm is derived from stiffness modeling, which is the combination of the principle of virtual work and dual quaternion algebra. To validate the effectiveness of the proposed identification algorithm and deformation compensation algorithm, an experiment was conducted on a dual arm industrial robot SDA5F. The robot performed a drilling operation during the experiment, and the forces and torques that acted on the end-effector (EE) of both arms were measured in order to apply the deformation compensation algorithm. The results of the experiment show that the proposed identification algorithm is able to identify the joint stiffness parameters of serial industrial robots, and the deformation compensation algorithm can improve the accuracy of the position and orientation of the EE. Furthermore, the performance of the forces and torques that acted on the EE during the operation were improved as well.


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