Motion process monitoring using optical flow–based principal component analysis-independent component analysis method

Abstract

In this article, for the first time, the optical flow and principal component analysis followed independent component analysis are combined for monitoring the motion process of robotic-arm-based system. Two kinds of optical flow, namely dense optical flow and sparse optical flow, extracted from each two successive frames of motion process in forms of video stream are used as the samples of motion-related variables of principal component analysis-independent component analysis algorithm. Relative work illustrates the effectiveness of principal component analysis-independent component analysis method for non-Gaussian process monitoring. The proposed dense optical flow-principal component analysis-independent component analysis and sparse optical flow-principal component analysis-independent component analysis algorithms use three-way array as their data which follows non-Gaussian distribution. Data unfolding, data normalization, and proper definition of the control limit are introduced. Based on dense optical flow-principal component analysis-independent component analysis and sparse optical flow-principal component analysis-independent component analysis algorithms, the corresponding motion process monitoring scheme is developed, and a case study of roboticarm-based marking system is taken to evaluate the performance of these methods. The results demonstrate the capability and efficiency of the proposed methods.

Efficient evaluation model of beam pumping unit based on principal component regression analysis

“…The principal component loads are shown in Table 8. 9,16 Establishment of a scoring model According to the main component load of Table 8, the analysis of the seven principal components is as follows ( Table 9 to Table 15).…”

“…In general, when the question involves many variables, and the information contained in the variables overlaps, that is, there is a clear correlation between the variables, then principal component analysis can be considered, which can more easily capture the main contradiction of things and simplify the problem. 8,9 Parameter selection and data acquisition that affect the efficiency of the beam pumping unit…”

Practical problem solving in manufacturing technologies

“…The results demonstrated the proposed method with good capability and efficiency. 9 The selected papers allow readers to have an inspired idea of ongoing research in this field and motivate further work toward the development of new techniques for practical problem solving in manufacturing technologies.…”

Safety Monitoring by a Graph-Regularized Semi-Supervised Nonnegative Matrix Factorization With Applications to a Vision-Based Marking Process

“…As a result, robots have been widely used in the fields of aerospace, automobile manufacturing and iron and steel metallurgy. For the safety concern, workers should keep a safe distance from the robots [1], [2]. Compared with the traditional safety monitoring methods, the vision-based safety monitoring methods can provide a more intuitive monitoring result, which takes advantage of digital imaging techniques to monitor the work zone of robots and alerts the workers who suffer from safety risks.…”