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| 1 | Effect of Thermal Cycle on Microstructure and Fracture Morphology in HAZ of HQ130 Steel显示文摘The effect of different peak temperature(T_P) and cooling time(t_(8/5)) on microstructure,hardness,impact toughness and fracture morphology in the heat-affected zone(HAZ) of HQ130 steel was studied by using weld thermo-simulation test.Experimental results indicate that the impact toughness and hardness decrease with the decrease of T_P or increase of t_(8/5) under the condition of a single thermal cycle.There is a brittle zone in the vicinity of T_P = 800 ℃,where the impact toughness is considerably low.There is a softened zone in the vicinity of T_P = 700℃,where the hardness decreases but the toughness increases.In the practical application of multi-layer and multipass welding,the welding heat input should be strictly limited(t_(8/5)≤20s) so as to reduce the softness and brittleness in the HAZ of HQ130 steel. | Li Yajiang Zou Zengda Cheng Zhunian Wei Xing Jiang Quanchang | 1996 | Journal of Iron and Steel Research(International)1996，3，2： | 3 |
| 2 | Experimental investigation of the effects of diesel injection strategy on gasoline/diesel dual-fuel combustion显示文摘 | Shuaiying Ma Zunqing Zheng Haifeng Liu Quanchang Zhang Mingfa Yao | 2013 | Applied Energy2013，，： | 3 |
| 3 | Experimental study of n-butanol addition on performance and emissions with diesel low temperature combustion显示文摘 | Quanchang Zhang Mingfa Yao Zunqing Zheng Haifeng Liu Jia Xu | 2012 | Energy2012，，1： | 1 |
| 4 | Synthesis and crystal structure of a novel charge transfer salt, (TMT-TTF) 4 [HPMo 12 O 40 ]显示文摘 | Xuemei Liu Xinzhong Lu Feng Fu Bin Liu Huaiming Hu Quanchang Gao Jiwu Wang Ganglin Xue | 2005 | Journal of Molecular Structure2005，，1： | 1 |
| 5 | Combustion and emissions of 2,5-dimethylfuran addition on a diesel engine with low temperature combustion显示文摘 | Quanchang Zhang Guisheng Chen Zunqing Zheng Haifeng Liu Jia Xu Mingfa Yao | 2013 | Fuel2013，，： | 1 |
| 6 | Fabrication of ZnO Nanorods and Nanotubes in Aqueous Solutions显示文摘 | Li Quanchang Vageesh Kumar Li Yan | 2005 | Chemistry of Materials2005，17，5： | 1 |
| 7 | Reduning Injection prevents carrageenan-induced inflammation in rats by serum and urine metabolomics analysis显示文摘Objective:To elucidate the anti-inflammatory mechanism of Reduning Injection(RDN)by analyzing the potential biomarkers and metabolic pathways of the carrageenan-induced inflammatory model from the overall metabolic level.Methods:Rat inflammatory model was established by carrageenan.UPLC-Q-TOF/MS was used to detect and analyze changes of endogenous metabolites in the serum and urine of carrageenan-induced inflammatory rats.Combined with multivariate analysis and databases analysis,inflammatory-related potential biomarkers were screened and identified to analyze possible metabolic pathways.The reliability and biological significance of these biomarkers was verified by metabolic network analysis and correlation analysis with pharmacodynamic indicators.Results:A total of 16 potential biomarkers were screened and identified by multivariate analysis and metabolite databases,among which 13 species could be adjusted by RDN.The metabolism pathway analysis revealed that histidine metabolism,sphingolipid metabolism,and tyrosine metabolism were greatly disturbed.Their biomarkers involved urocanic acid,sphingosine,and norepinephrine,all of which showed a callback trend after RDN treatment.The three biomarkers had a certain correlation with some known inflammatory-related small molecules(histamine,arachidonic acid,Leukotriene B4,and PGE2)and pharmacodynamic indicators(IL-6,IL-1β,PGE2and TNF-a),which indicated that the selected biomarkers had certain reliability and biological significance.Conclusion:RDN has a good regulation of the metabolic disorder of endogenous components in carrageenan-induced inflammatory rats.And its anti-inflammatory mechanism is mainly related to the regulation of amino acid and lipid metabolism.This research method is conducive to the interpretation of the overall pharmacological mechanism of Chinese medicine. | Xia Gao Jiajia Wang Xialin Chen Shanli Wang Chaojie Huang Quanchang Zhang Liang Cao Zhenzhong Wang Wei Xiao | 2022 | Chinese Herbal Medicines2022，14，4： | 1 |
| 8 | Experimental study of n-butanol addition on perform ance and emissions with diesel low temperature com bustion显示文摘 | Quanchang Zhang Mingfa Yao Zunqing Zheng | 2012 | Energy2012，47，： | 1 |
| 9 | Experimental study of effects of oxygen concentration on combustion and emissions of diesel engine显示文摘Effects of oxygen concentration on combustion and emissions of diesel engine are investigated by experiment.The intake oxygen concentration is controlled by adjusting CO2.The results show that very low levels of both soot and NOx emissions can be achieved by modulating the injection pressure,tim-ing,and boost pressure at the low levels of oxygen concentration.However,both CO and HC emissions and fuel consumption distinctly increase at the low levels of oxygen concentration.The results also indicate that NOx emissions strongly depend on oxygen concentration,while soot emissions strongly depend on injection pressure.Decreasing oxygen concentration is the most effective method to control NOx emissions.High injection pressure is necessary to reduce smoke emissions.High injection pres-sure can also decrease the CO and HC emissions and improve engine efficiency.With the increase of intake pressure,both NOx and smoke emissions decrease.However,it is necessary to use the appro-priate intake pressure in order to get the low HC and CO emissions with high efficiency. | YAO MingFa ZHANG QuanChang ZHENG ZunQin ZHANG Pang | 2009 | Science China(Technological Sciences)2009，52，6： | 1 |
| 10 | Experimental study of n-butanol addition on perf?ormance and emissions with diesel low temperature combustion显示文摘 | Zhang Quanchang Yao Mingfa Zheng Zunqing | 2012 | Energy2012，470，： | 1 |
| 11 | Experimental investigation of the effects of diesel injection strategy on gasoline/diesel dual-fuel combustion显示文摘 | Shuaiying Ma Zunqing Zheng Haifeng Liu Quanchang Zhang Mingfa Yao | 2013 | Applied Energy2013，，： | 1 |
| 12 | Experimental study on combustion and emission characteristics of a diesel engine fueled with 2,5- dimethylfuran-diesel, n-butanol-diesel and gasoline- diesel blends 显示文摘 | Chen Guisheng Shen Yinggang Zhang Quanchang | 2013 | Energy2013，54，： | 1 |
| 13 | Exploration of technical route for China heavy-duty diesel engine with EGR显示文摘 | ChenGuisheng Lin Tiejian Zhang Quanchang | 2012 | Chinese Internal Combustion Engine Engineering2012，33，5： | 1 |
| 14 | Bearings Intelligent Fault Diagnosis by 1-D Adder Neural Networks显示文摘Integrated with sensors,processors,and radio frequency(RF)communication modules,intelligent bearing could achieve the autonomous perception and autonomous decision-making,guarantying the safety and reliability during their use.However,because of the resource limitations of the end device,processors in the intelligent bearing are unable to carry the computational load of deep learning models like convolutional neural network(CNN),which involves a great amount of multiplicative operations.To minimize the computation cost of the conventional CNN,based on the idea of AdderNet,a 1-D adder neural network with a wide first-layer kernel(WAddNN)suitable for bearing fault diagnosis is proposed in this paper.The proposed method uses the l1-norm distance between filters and input features as the output response,thus making the whole network almost free of multiplicative operations.The whole model takes the original signal as the input,uses a wide kernel in the first adder layer to extract features and suppress the high frequency noise,and then uses two layers of small kernels for nonlinear mapping.Through experimental comparison with CNN models of the same structure,WAddNN is able to achieve a similar accuracy as CNN models with significantly reduced computational cost.The proposed model provides a new fault diagnosis method for intelligent bearings with limited resources. | Jian Tang Chao Wei Quanchang Li Yinjun Wang Xiaoxi Ding Wenbin Huang | 2022 | Journal of Dynamics, Monitoring and Diagnostics2022，1，3： | 0 |
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