To meet the command of real-time performance in industrial field, a method has been researched for fast detecting texture defects in X-ray tyre image. Based on the principle of X-ray imaging, the gray level at the cen...
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To meet the command of real-time performance in industrial field, a method has been researched for fast detecting texture defects in X-ray tyre image. Based on the principle of X-ray imaging, the gray level at the center of texton is the least in local area. A difference method was adopted to find local extreme points. The skeleton of texture was acquired through searching and recognizing these points. The run-length coding method was adopted to vectorize the texture skeleton. In texture vector graph, the character description model was founded, and through this model, texture defects were detected and recognized. The experiment results showed that structure defects in tyre texture were fast detected and recognized, and the detection time was reduced 70%.
The cutting vibration generated by cutting forces is critical to the accuracy and efficiency of face-hobbed hypoid gears. However, few relevant works are currently on cutting dynamics modeling for the face-hobbing pro...
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The cutting vibration generated by cutting forces is critical to the accuracy and efficiency of face-hobbed hypoid gears. However, few relevant works are currently on cutting dynamics modeling for the face-hobbing process due to its complex spatial relationships. This study developed an efficient cutting dynamics model considering comprehensive characteristics of the non-generated face-hobbed hypoid gear machining process. A concise and efficient analytical solution to cutting dynamics modeling for face-hobbing of hypoid gears is obtained by using a vectorization method to characterize chip regenerating mechanisms. The machine tool vibration caused by cutting forces is predicted and validated according to an industrial case study. The proposed cutting dynamic model is 36.11% more efficient than the semi-analytical dynamic model derived from other cutting force prediction methods, and its accuracy is also improved with an error of less than 15%. Furthermore, the proposed vectorization solution to face-hobbing cutting dynamics modeling will be a practicable and effective method for analyzing the chatter in the machining of complex surfaces.
Ordinary least squares estimator (OLSE), best linear unbiased estimator (BLUE), and best linear unbiased predictor (BLUP) in the general linear model with new observations are generalized to the general multivariate l...
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Ordinary least squares estimator (OLSE), best linear unbiased estimator (BLUE), and best linear unbiased predictor (BLUP) in the general linear model with new observations are generalized to the general multivariate linear model. The fundamental equations of BLUE and BLUP in the multivariate linear model are derived by two methods, including the vectorization method and projection method. By using the matrix rank method, some new results of linear BLUE-sufficiency, linear BLUP-sufficiency, and the equality of OLSE, BLUE, and BLUP are given in the multivariate linear model.
SIMD (Single Instruction Multiple Data) extensions are acceleration components integrated in general processor, aiming at extracting instruction and data level parallelism of multimedia and scientific calculation prog...
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ISBN:
(纸本)9781509050819
SIMD (Single Instruction Multiple Data) extensions are acceleration components integrated in general processor, aiming at extracting instruction and data level parallelism of multimedia and scientific calculation programs. Currently, most of the automatic vectorization methods for SIMD architectures are based on innermost loops. Inner loop vectorization is the common approach for auto-vectorization. This method has been used for many years and its efficiency is widely accepted by people. In this paper, we put forward a better method than inner loop vectorization for some loop nests, which is outer loop vectorization. Outer loop vectorization method means vectorizing the outer loop directly. It can extract more data level parallelism and make the most use of the spatial locality to improve the program efficiency than the inner one which is more suitable for some loop nests. This paper presents the realization. In this paper, we first revisit the preliminary analysis of outer loop vectorization based on Open64 complier. And then, data type conversion and code generation is presented in detail. Finally, we propose two optimization methods, capable of boosting the performance of outer loop vectorization to achieve the acceleration of 20% on average, 50% at most.
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