对Pd/AC催化剂上对苯二甲酸(TA)加氢精制过程中的对羧基苯甲醛(4-CBA)加氢反应进行了研究。考察了氢分压、反应温度、催化剂颗粒大小对4-CBA消逝速率的影响,结果表明:在高于0.35 M Pa时,氢分压对4-CBA加氢反应速率的影响很小,而温度和...对Pd/AC催化剂上对苯二甲酸(TA)加氢精制过程中的对羧基苯甲醛(4-CBA)加氢反应进行了研究。考察了氢分压、反应温度、催化剂颗粒大小对4-CBA消逝速率的影响,结果表明:在高于0.35 M Pa时,氢分压对4-CBA加氢反应速率的影响很小,而温度和催化剂粒度大小对加氢反应的影响显著。同时,工业条件下的TA加氢精制过程存在着严重的内外扩散。采用幂函数动力学模型方程利用M atlab拟合得到了不同粒度催化剂上的表观动力学方程。展开更多
In the past few years, support vector machines (SVMs) have been applied to many fields, such as pattern recognition and data mining, etc. However there still exist some problems to be solved. One of them is that the S...In the past few years, support vector machines (SVMs) have been applied to many fields, such as pattern recognition and data mining, etc. However there still exist some problems to be solved. One of them is that the SVM is very sensitive to outliers or noises because of over-fitting problem. In this paper, a fuzzy support vector regression (FSVR) method is presented to deal with this problem. Strategies based on k nearest neighbor (kNN) and support vector data description (SVDD) are adopted to set the fuzzy membership values of data points in FSVR.The proposed FSVR soft sensor models based on kNN and SVDD are employed to predict the concentration of 4-carboxy-benzaldehyde (4-CBA) in purified terephthalic acid (PTA) oxidation process. Simulation results indicate that the proposed method indeed reduces the effect of outliers and yields higher accuracy.展开更多
文摘对Pd/AC催化剂上对苯二甲酸(TA)加氢精制过程中的对羧基苯甲醛(4-CBA)加氢反应进行了研究。考察了氢分压、反应温度、催化剂颗粒大小对4-CBA消逝速率的影响,结果表明:在高于0.35 M Pa时,氢分压对4-CBA加氢反应速率的影响很小,而温度和催化剂粒度大小对加氢反应的影响显著。同时,工业条件下的TA加氢精制过程存在着严重的内外扩散。采用幂函数动力学模型方程利用M atlab拟合得到了不同粒度催化剂上的表观动力学方程。
基金National Key Technologies Research and Development Program in the 10th five-year plan，国家杰出青年科学基金
文摘In the past few years, support vector machines (SVMs) have been applied to many fields, such as pattern recognition and data mining, etc. However there still exist some problems to be solved. One of them is that the SVM is very sensitive to outliers or noises because of over-fitting problem. In this paper, a fuzzy support vector regression (FSVR) method is presented to deal with this problem. Strategies based on k nearest neighbor (kNN) and support vector data description (SVDD) are adopted to set the fuzzy membership values of data points in FSVR.The proposed FSVR soft sensor models based on kNN and SVDD are employed to predict the concentration of 4-carboxy-benzaldehyde (4-CBA) in purified terephthalic acid (PTA) oxidation process. Simulation results indicate that the proposed method indeed reduces the effect of outliers and yields higher accuracy.
