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Identifying glass defects through machine visual has a vital importance for the efficient production of high quality glass. In this paper, a method based on the combination of Non-negative Matrix Factorization (NMF) and Sparse Representation Classification (SRC) was proposed for the identification of glass defects. According to the properties of glass defect image, NMF algorithm is used to decompose...
A novel approach to extract fault feature parameters is put forward. First, the time signal is transformed to time-frequency signals which keep same length as that of the original signal by using the convolution type of wavelet packet transformation.Second, considering time-frequency signals as the matrix reflect feature of system, singular value decomposition (SVD) is used to convert the multi-dimension...
Strip rolling is a very complicated nonlinear process. Automatic flatness control (AFC) and automatic gauge control (AGC) are nonlinear, interacted and coupled each other. A novel PID neural network control method of AFC-AGC is developed, in which Smith predictor is designed by using two wavelet networks whose structures and parameters are identical. Because inputs of network are independent of time...
A multi-scale de-noising algorithm based on the convolution type of wavelet packet transformation is presented. This algorithm overcomes shortcomings of the classical wavelet packet transformation, in which the length of sequences obtained always decreases by decomposition scales. The new algorithm improves estimated method of white noise standard deviation at each scale and thus keeps the main edges...
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