Advanced Engineering Forum Vols. 2-3

Abstract: This paper briefly introduce the concept and characteristic and form of machine vision inspecting system, elaborate its application in industry, the present status and development prospects of the application in geometry measurement are described in detail, and deal with emphatically its critical technical points and the corresponding solutions.

Abstract: Aiming at dealing with the existing noise of triaxial flight simulation turntable, the paper design digital filter low-pass transmitters and generalized minimum variance control filter to process signal for random disturbance, and have test study based on outside box control system of triaxial flight simulation turntable. The test results show that we can get better control effect by adopting generalized minimum variance control rates to denoise for measured signal on triaxial flight simulation turntable, and that is much helpful to improve the noise control accuracy.

Abstract: The natural properties of flexible beam is measured by using machine vision in which the image of vibrate flexible Beam is acquired continuously. Different from the previous contact measurement methods, the binary processing method and centroid method is utilized to binarize the image and extracts the position of marked point. Gathering and calculating the position information preprocessed in MATLAB indicates the natural properties of flexible beam. Furthermore, the test results compared with the theoretical analysis verifies the validity of the proposed method.

Abstract: The Ta₂O₅/SiO₂ Multi-layer Antireflection Coating Is Prepared on K9 Glass by RF Magnetron Sputtering Technology in the Experiment. the Growth Parameters Are Changed to Get Multi-layer Antireflection Film with Good Optical Properties. in the Technical Research, the Influence of Various Growth Parameters, Including Working Pressure, Oxygen Content, Substrate Temperature, Etc., on the Optical Properties and Structures of the Coatings Are Studied. Optical Properties and Morphological Features such as Surface, Structure Are Investigated by UV-VIS Spectrophotometer and AFM, Respectively. the Detecting Results Further Verify the Important Influences of Proper Growth Parameters on Optical Properties of Antireflection Coating.

Abstract: How to explore higher efficient and more credible fire-detection system by rapid development of computer and image processing techniques has aroused public’s extensive attention. To achieve fully automatic surveillance of fires, an intelligent fire detection method based on a multi-stage decision strategy of image processing is proposed. Both static and dynamic characteristics of the fire images sequence are considered. First of all time difference is used to process the gray-scale image to obtain the moving region in the scene, secondly apply color segmentation to get the ROI of fire region, thirdly shape features such as randomness of area size, edge likelihood are calculated to avoid some interference, at last the polygonal and irregular characters of flame like sharp corners and circularity are used to identified the fire. Experimental result shows the Fire-detection method presented in this paper could detect fire in the image sequence effectively, and it is capable of distinguishing Environmental light changes, background color interference and light false identification. Multi-stage decision strategy can improve the algorithm performance and reduce false-alarm rate. The proposed method has broad application prospects in the important military, social security, forest-fire alarm, commercial applications, and so on.

Abstract: Two de-noising methods, named as the averaging method in Gabor transform domain (AMGTD) and the adaptive filtering method in Gabor transform domain (AFMGTD), are presented in this paper. These two methods are established based on the correlativity of the source signals and the background noise in time domain and Gabor transform domain, that is to say, the uncorrelated source signals and background noise in time domain would still be uncorrelated in Gabor transform domain. The construction and computation scheme of these two methods are investigated. The de-noising performances are illustrated by some simulation signals, and the wavelet transform is used to compare with these two new de-noising methods. The results show that these two methods have better de-noising performance than the wavelet transform, and could reduce the background noise in the vibration signal more effectively.

Abstract: Stereo matching methods often use rank transform to deal with image distortions and brightness differences prior to matching but a pixel in the rank transformed image may look more similar to its neighbor, which would cause matching ambiguity. We tackle this problem with two proposals. Firstly, instead of using two values 0 and 1,we increase the discriminative power of the rank transform by using a linear, smooth transition zone between 0 and 1 for intensities that are close together. Secondly, we propose a new Bayesian stereo matching model by not only considering the similarity between left and right image pixels but also considering the ambiguity level of them in their own image independently. We test our algorithm on both intensity and color images with brightnesss differences. Corresponding 2D disparity maps and 3D reconstruction results verify the effectiveness of our method.

Abstract: In signal denoise method to nonlinear time series based on principle manifold learning, reduction target dimension is chosen at random, which cause low efficiency. Local low dimensional manifold is obtained by the eigenvalue decomposition to the covariance matrix, but covariance belongs to the second order statistics and cannot reflect the nonlinear essential structure of signal, these reduce denoise efficiency and effect. In order to solve these problem, a new denoise algorithm based on the higher order cumulant and local tangent space mean reconstruction is proposed in this reserch. First, the signal's intrinsic dimension is obtained as dimension of reduction targets by maximum likelihood estimation. And then making use of restraining character to colored noise of high order cumulan,covariance matrix is constructed by high order cumulant function instead of second order moment function. The data outside intrinsic dimension space will be regarded as noise signal to be eliminated. Finanly the process of global array by affine transformation will be replaced by mean reconstruction,the data after denoise may be obtained in the inverse process of the phase space reconstruction. The effectiveness of the algorithm is verified through the denoise experiment in fan vibration signal with noise.

Abstract: To solve the problem of difficult to extract fault features from the early weak AE signal, a method combining lifting wavelet with EMD is proposed. Firstly, the lifting wavelet is used to de-noise the AE signal, then the signal after de-noising is decomposed by EMD, and gets all kinds of different frequency IMFS. Finally, the most relevant IMF with the original signal depends on the size of the correlation coefficients, and the fault characteristic signal is extracted via combining time- frequency analysis and envelope spectrum analysis. The result of simulation and test signal shows that this method can effectively extracts the failure characteristics from early AE signal.

Abstract: KPCA is a commonly used method for feature extraction, for the problems of kernel function and its parameters have a great influence on performance of KPCA feature extraction but the optimal parameters are difficult to select. This paper applied the bacterial foraging algorithm on KPCA feature extraction and the method of KPCA feature extraction based on bacterial foraging algorithm was proposed. The experiment of bearing feature extraction shows that the method which proposed in this paper is effective.