The fatigue resistance of casting polyurethane(CPU)is crucial in various sectors,such as construction,healthcare,and the automotive industry.Despite its importance,no studies have reported on the fatigue threshold of ...The fatigue resistance of casting polyurethane(CPU)is crucial in various sectors,such as construction,healthcare,and the automotive industry.Despite its importance,no studies have reported on the fatigue threshold of CPU.This study employed an advanced Intrinsic Strength Analyzer(ISA)to evaluate the fatigue threshold of CPUs,systematically exploring the effects of three types of isocyanates(PPDI,NDI,TDI)that contribute to hard segment structures based on the cutting method.Employing multiple advanced characterization techniques(XRD,TEM,DSC,AFM),the results indicate that PPDI-based polyurethane exhibits the highest fatigue threshold(182.89 J/m^(2))due to a highest phase separation and a densely packed spherulitic structure,although the hydrogen bonding degree is the lowest(48.3%).Conversely,NDI-based polyurethane,despite having the high hydrogen bonding degree(53.6%),exhibits moderate fatigue performance(122.52 J/m^(2)),likely due to a more scattered microstructure.TDI-based polyurethane,with the highest hydrogen bonding degree(59.1%)but absence of spherulitic structure,shows the lowest fatigue threshold(46.43 J/m^(2)).Compared to common rubbers(NR,NBR,EPDM,BR),the superior fatigue performance of CPU is attributed to its well-organized microstructure,polyurethane possesses a higher fatigue threshold due to its high phase separation degree and orderly and dense spherulitic structure which enhances energy dissipation and reduces crack propagation.展开更多
The aeroengine casing ring forgings have complex cross-section shapes,when the conventional ultrasonic or phased array is applied to detect such curved surfaces,the inspection images always have low resolution and eve...The aeroengine casing ring forgings have complex cross-section shapes,when the conventional ultrasonic or phased array is applied to detect such curved surfaces,the inspection images always have low resolution and even artifacts due to the distortion of the wave beam.In this article,taking a type of aeroengine casing ring forging as an example,the Total Focusing Method(TFM)algorithms for curved surfaces are investigated.First,the Acoustic Field Threshold Segmentation(AFTS)algorithm is proposed to reduce background noise and data calculation.Furthermore,the Vector Coherence Factor(VCF)is adopted to improve the lateral resolution of the TFM imaging.Finally,a series of 0.8 mm diameter Side-Drilled Holes(SDHs)are machined below convex and concave surfaces of the specimen.The quantitative comparison of the detection images using the conventional TFM,AFTS-TFM,VCF-TFM,and AFTS-VCF-TFM is implemented in terms of data volume,imaging Signal-to-Noise Ratio(SNR),and defect echo width.The results show that compared with conventional TFM,the data volume of AFTS-VCF-TFM algorithm for convex and concave is decreased by 32.39%and 73.40%,respectively.Moreover,the average SNR of the AFTS-VCF-TFM is gained up to 40.0 dB,while the average 6 dB-drop echo width of defects is reduced to 0.74 mm.展开更多
The purpose of this study is to apply different thresholding in mammogram images, and then we will determine which technique is the best in thresholding (extraction) malignant and benign tumors from the rest breast ti...The purpose of this study is to apply different thresholding in mammogram images, and then we will determine which technique is the best in thresholding (extraction) malignant and benign tumors from the rest breast tissues. The used technique is Otsu method, because it is one of the most effective methods for most real world views with regard to uniformity and shape measures. Also, we present all the thresholding methods that used the concept of between class variance. We found from the experimental results that all the used thresholding techniques work well in detection normal breast tissues. But in abnormal tissues (breast tumors), we found that only neighborhood valley emphasis method gave best detection of malignant tumors. Also, the results demonstrate that variance and intensity contrast technique is the best in extraction the micro calcifications which represent the first signs of breast cancer.展开更多
To overcome the shortcoming that the traditional minimum error threshold method can obtain satisfactory image segmentation results only when the object and background of the image strictly obey a certain type of proba...To overcome the shortcoming that the traditional minimum error threshold method can obtain satisfactory image segmentation results only when the object and background of the image strictly obey a certain type of probability distribution,one proposes the regularized minimum error threshold method and treats the traditional minimum error threshold method as its special case.Then one constructs the discrete probability distribution by using the separation between segmentation threshold and the average gray-scale values of the object and background of the image so as to compute the information energy of the probability distribution.The impact of the regularized parameter selection on the optimal segmentation threshold of the regularized minimum error threshold method is investigated.To verify the effectiveness of the proposed regularized minimum error threshold method,one selects typical grey-scale images and performs segmentation tests.The segmentation results obtained by the regularized minimum error threshold method are compared with those obtained with the traditional minimum error threshold method.The segmentation results and their analysis show that the regularized minimum error threshold method is feasible and produces more satisfactory segmentation results than the minimum error threshold method.It does not exert much impact on object acquisition in case of the addition of a certain noise to an image.Therefore,the method can meet the requirements for extracting a real object in the noisy environment.展开更多
Two dimensional(2 D) entropy method has to pay the price of time when applied to image segmentation. So the genetic algorithm is introduced to improve the computational efficiency of the 2 D entropy method. The pro...Two dimensional(2 D) entropy method has to pay the price of time when applied to image segmentation. So the genetic algorithm is introduced to improve the computational efficiency of the 2 D entropy method. The proposed method uses both the gray value of a pixel and the local average gray value of an image. At the same time, the simple genetic algorithm is improved by using better reproduction and crossover operators. Thus the proposed method makes up the 2 D entropy method’s drawback of being time consuming, and yields satisfactory segmentation results. Experimental results show that the proposed method can save computational time when it provides good quality segmentation.展开更多
In this paper, a comprehensive energy function is used to formulate the three most popular objective functions:Kapur's, Otsu and Tsalli's functions for performing effective multilevel color image thresholding....In this paper, a comprehensive energy function is used to formulate the three most popular objective functions:Kapur's, Otsu and Tsalli's functions for performing effective multilevel color image thresholding. These new energy based objective criterions are further combined with the proficient search capability of swarm based algorithms to improve the efficiency and robustness. The proposed multilevel thresholding approach accurately determines the optimal threshold values by using generated energy curve, and acutely distinguishes different objects within the multi-channel complex images. The performance evaluation indices and experiments on different test images illustrate that Kapur's entropy aided with differential evolution and bacterial foraging optimization algorithm generates the most accurate and visually pleasing segmented images.展开更多
Among all segmentation techniques, Otsu thresholding method is widely used. Line intercept histogram based Otsu thresholding method(LIH Otsu method) can be more resistant to Gaussian noise, highly efficient in computi...Among all segmentation techniques, Otsu thresholding method is widely used. Line intercept histogram based Otsu thresholding method(LIH Otsu method) can be more resistant to Gaussian noise, highly efficient in computing time, and can be easily extended to multilevel thresholding. But when images contain salt-and-pepper noise, LIH Otsu method performs poorly. An improved LIH Otsu method(ILIH Otsu method) is presented, which can be more resistant to Gaussian noise and salt-and-pepper noise. Moreover, it can be easily extended to multilevel thresholding. In order to improve the efficiency, the optimization algorithm based on the kinetic-molecular theory(KMTOA) is used to determine the optimal thresholds. The experimental results show that ILIH Otsu method has stronger anti-noise ability than two-dimensional Otsu thresholding method(2-D Otsu method), LIH Otsu method, K-means clustering algorithm and fuzzy clustering algorithm.展开更多
基金financially supported by the National Natural Science Foundation of China(No.52473228).
文摘The fatigue resistance of casting polyurethane(CPU)is crucial in various sectors,such as construction,healthcare,and the automotive industry.Despite its importance,no studies have reported on the fatigue threshold of CPU.This study employed an advanced Intrinsic Strength Analyzer(ISA)to evaluate the fatigue threshold of CPUs,systematically exploring the effects of three types of isocyanates(PPDI,NDI,TDI)that contribute to hard segment structures based on the cutting method.Employing multiple advanced characterization techniques(XRD,TEM,DSC,AFM),the results indicate that PPDI-based polyurethane exhibits the highest fatigue threshold(182.89 J/m^(2))due to a highest phase separation and a densely packed spherulitic structure,although the hydrogen bonding degree is the lowest(48.3%).Conversely,NDI-based polyurethane,despite having the high hydrogen bonding degree(53.6%),exhibits moderate fatigue performance(122.52 J/m^(2)),likely due to a more scattered microstructure.TDI-based polyurethane,with the highest hydrogen bonding degree(59.1%)but absence of spherulitic structure,shows the lowest fatigue threshold(46.43 J/m^(2)).Compared to common rubbers(NR,NBR,EPDM,BR),the superior fatigue performance of CPU is attributed to its well-organized microstructure,polyurethane possesses a higher fatigue threshold due to its high phase separation degree and orderly and dense spherulitic structure which enhances energy dissipation and reduces crack propagation.
基金supported by the National Key Research and Development Program of China(No.2019YFB1704500)the National Natural Science Foundation of China(No.51875428)+3 种基金the Key Research and Development Program of Hubei Province,China(No.2020BAB144)the Excellent Youth Foundation of Hubei Province,China(No.2019CFA041)the Innovative Research Team Development Program of Ministry of Education of China(No.IRT_17R83)the 111 Project of China(No.B17034)。
文摘The aeroengine casing ring forgings have complex cross-section shapes,when the conventional ultrasonic or phased array is applied to detect such curved surfaces,the inspection images always have low resolution and even artifacts due to the distortion of the wave beam.In this article,taking a type of aeroengine casing ring forging as an example,the Total Focusing Method(TFM)algorithms for curved surfaces are investigated.First,the Acoustic Field Threshold Segmentation(AFTS)algorithm is proposed to reduce background noise and data calculation.Furthermore,the Vector Coherence Factor(VCF)is adopted to improve the lateral resolution of the TFM imaging.Finally,a series of 0.8 mm diameter Side-Drilled Holes(SDHs)are machined below convex and concave surfaces of the specimen.The quantitative comparison of the detection images using the conventional TFM,AFTS-TFM,VCF-TFM,and AFTS-VCF-TFM is implemented in terms of data volume,imaging Signal-to-Noise Ratio(SNR),and defect echo width.The results show that compared with conventional TFM,the data volume of AFTS-VCF-TFM algorithm for convex and concave is decreased by 32.39%and 73.40%,respectively.Moreover,the average SNR of the AFTS-VCF-TFM is gained up to 40.0 dB,while the average 6 dB-drop echo width of defects is reduced to 0.74 mm.
文摘The purpose of this study is to apply different thresholding in mammogram images, and then we will determine which technique is the best in thresholding (extraction) malignant and benign tumors from the rest breast tissues. The used technique is Otsu method, because it is one of the most effective methods for most real world views with regard to uniformity and shape measures. Also, we present all the thresholding methods that used the concept of between class variance. We found from the experimental results that all the used thresholding techniques work well in detection normal breast tissues. But in abnormal tissues (breast tumors), we found that only neighborhood valley emphasis method gave best detection of malignant tumors. Also, the results demonstrate that variance and intensity contrast technique is the best in extraction the micro calcifications which represent the first signs of breast cancer.
基金supported by the National Natural Science Foundations of China(Nos.61136002,61472324)the Natural Science Foundation of Shanxi Province(No.2014JM8331)
文摘To overcome the shortcoming that the traditional minimum error threshold method can obtain satisfactory image segmentation results only when the object and background of the image strictly obey a certain type of probability distribution,one proposes the regularized minimum error threshold method and treats the traditional minimum error threshold method as its special case.Then one constructs the discrete probability distribution by using the separation between segmentation threshold and the average gray-scale values of the object and background of the image so as to compute the information energy of the probability distribution.The impact of the regularized parameter selection on the optimal segmentation threshold of the regularized minimum error threshold method is investigated.To verify the effectiveness of the proposed regularized minimum error threshold method,one selects typical grey-scale images and performs segmentation tests.The segmentation results obtained by the regularized minimum error threshold method are compared with those obtained with the traditional minimum error threshold method.The segmentation results and their analysis show that the regularized minimum error threshold method is feasible and produces more satisfactory segmentation results than the minimum error threshold method.It does not exert much impact on object acquisition in case of the addition of a certain noise to an image.Therefore,the method can meet the requirements for extracting a real object in the noisy environment.
文摘Two dimensional(2 D) entropy method has to pay the price of time when applied to image segmentation. So the genetic algorithm is introduced to improve the computational efficiency of the 2 D entropy method. The proposed method uses both the gray value of a pixel and the local average gray value of an image. At the same time, the simple genetic algorithm is improved by using better reproduction and crossover operators. Thus the proposed method makes up the 2 D entropy method’s drawback of being time consuming, and yields satisfactory segmentation results. Experimental results show that the proposed method can save computational time when it provides good quality segmentation.
文摘In this paper, a comprehensive energy function is used to formulate the three most popular objective functions:Kapur's, Otsu and Tsalli's functions for performing effective multilevel color image thresholding. These new energy based objective criterions are further combined with the proficient search capability of swarm based algorithms to improve the efficiency and robustness. The proposed multilevel thresholding approach accurately determines the optimal threshold values by using generated energy curve, and acutely distinguishes different objects within the multi-channel complex images. The performance evaluation indices and experiments on different test images illustrate that Kapur's entropy aided with differential evolution and bacterial foraging optimization algorithm generates the most accurate and visually pleasing segmented images.
基金Project(61440026)supported by the National Natural Science Foundation of ChinaProject(11KZ|KZ08062)supported by Doctoral Research Project of Xiangtan University,China
文摘Among all segmentation techniques, Otsu thresholding method is widely used. Line intercept histogram based Otsu thresholding method(LIH Otsu method) can be more resistant to Gaussian noise, highly efficient in computing time, and can be easily extended to multilevel thresholding. But when images contain salt-and-pepper noise, LIH Otsu method performs poorly. An improved LIH Otsu method(ILIH Otsu method) is presented, which can be more resistant to Gaussian noise and salt-and-pepper noise. Moreover, it can be easily extended to multilevel thresholding. In order to improve the efficiency, the optimization algorithm based on the kinetic-molecular theory(KMTOA) is used to determine the optimal thresholds. The experimental results show that ILIH Otsu method has stronger anti-noise ability than two-dimensional Otsu thresholding method(2-D Otsu method), LIH Otsu method, K-means clustering algorithm and fuzzy clustering algorithm.
