冷喷涂工艺通常采用较热喷涂更细小粒径的金属粉末,而且粉末颗粒在喷涂中没有经历熔化过程,所以较热喷涂颗粒中的氧化物夹杂少。正因如此,有必要对工业、研发用冷喷涂工艺中的粉尘爆炸和燃烧特性进行研究,这不仅是为了防止粉末在喷涂中...冷喷涂工艺通常采用较热喷涂更细小粒径的金属粉末,而且粉末颗粒在喷涂中没有经历熔化过程,所以较热喷涂颗粒中的氧化物夹杂少。正因如此,有必要对工业、研发用冷喷涂工艺中的粉尘爆炸和燃烧特性进行研究,这不仅是为了防止粉末在喷涂中爆炸或燃烧,更为保护工人的健康和安全。为使冷喷涂在工业上得到很好的应用,有必要在风险评估的基础上对其进行风险管理,然而关于此风险评估的研究鲜有报道。本文依据JIS Z 8818-《可燃粉尘的最低浓度限度测试方法》、IEC61241-2-3(1994-09)第三节-《粉尘/空气混合物的最小点火能量测定方法》和JIS Z 8817-《可燃粉尘的爆炸压力及压力上升速率的测试方法》来测定冷喷涂用铝基、钛基、锌基、铁基合金粉末的粉尘爆炸特性。展开更多
Multivariate analysis and filtering techniques are widely applied to simultaneous and/or selective determination of multicomponent systems. Many methods among them are based on the principle of linear addition, while ...Multivariate analysis and filtering techniques are widely applied to simultaneous and/or selective determination of multicomponent systems. Many methods among them are based on the principle of linear addition, while this principle does not always hold due to various physical and chemical factors. Using quite a different way, neural network (NN) based on a given learning rule, such as back propagation (BP) model, needs neither knowing nor using any form of input/output relationship. Particularly, NN can resolve various problems such as those with casual relation, those with fuzzy backgrounds, and those with uncertain inferential processes. NN was used by us to investigate quantitative struc-展开更多
文摘冷喷涂工艺通常采用较热喷涂更细小粒径的金属粉末,而且粉末颗粒在喷涂中没有经历熔化过程,所以较热喷涂颗粒中的氧化物夹杂少。正因如此,有必要对工业、研发用冷喷涂工艺中的粉尘爆炸和燃烧特性进行研究,这不仅是为了防止粉末在喷涂中爆炸或燃烧,更为保护工人的健康和安全。为使冷喷涂在工业上得到很好的应用,有必要在风险评估的基础上对其进行风险管理,然而关于此风险评估的研究鲜有报道。本文依据JIS Z 8818-《可燃粉尘的最低浓度限度测试方法》、IEC61241-2-3(1994-09)第三节-《粉尘/空气混合物的最小点火能量测定方法》和JIS Z 8817-《可燃粉尘的爆炸压力及压力上升速率的测试方法》来测定冷喷涂用铝基、钛基、锌基、铁基合金粉末的粉尘爆炸特性。
基金Project supported by the Japanese Ministry of Education,CultureScience(Monbusho),the Ministry of Mechanical Industry of China(MMIC),the State Education Commission of China(SECC)the National Natural Science Foundation of China(NSFC).
文摘Multivariate analysis and filtering techniques are widely applied to simultaneous and/or selective determination of multicomponent systems. Many methods among them are based on the principle of linear addition, while this principle does not always hold due to various physical and chemical factors. Using quite a different way, neural network (NN) based on a given learning rule, such as back propagation (BP) model, needs neither knowing nor using any form of input/output relationship. Particularly, NN can resolve various problems such as those with casual relation, those with fuzzy backgrounds, and those with uncertain inferential processes. NN was used by us to investigate quantitative struc-
