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According to the construction drawings of the assembly building, various prefabricated components are transported from the factory to the construction site. This study provides definitions of the construction units, building units, ordinary vehicles, motor vehicles, transportation shifts and transportation completion and quantitatively describes the collocation correlation between prefabricated components, construction units and building units and the substitution correlation between motor and ordinary vehicles. Subsequently, a transport vehicle deployment problem was proposed for prefabricated components. The objective of the optimization was to maximize the degree of completion of transportation. The constraint of the collocation correlation between prefabricated components and the substitution correlation between transport vehicles is proposed as a substitution equilibrium point method to deploy transportation vehicles. Simulation experiments showed that considering the matching correlation between prefabricated components and the substitution correlation of transport vehicles, the transport completion of prefabricated components could be increased. The substitution equilibrium point method proposed in this study exhibited a lower time complexity than the integer programming branch-and-bound method.

Facing a great deal of Lifelog data and complex information, how to extract valuable information and making it easily understood for users is the most urgent and important issue. This paper introduces a method to find personal trajectories from a Lifelog dataset named informative lifelogging which the author collected over the past 8 years. After introducing the Lifelog system and the data structure, this paper propose a method to find personal trajectory in the dataset. Experiment result in the last chapter shows the correctness of this method. The method proposed in this paper provides some way of managing and retrieving the Lifelog data efficiently.

The authors began collecting personal informative lifelogging data in 2011. The data collected in this article is a discontinuous data set, each of which includes one or more images, a GPS message, a description of a location, and a description of the text, we call this informative lifelogging. However, for the purposes automatically building a story from a huge collection of unstructured egocentric data presents major challenges. This paper first introduces the structure and characteristics of the collected data and uses the DB-scan algorithm to classify the data. Then a model for generating a story is proposed, and a model of story generation based on a story template is proposed in the model. The author implemented a complete software system through code, described a story generation model, and gave the key algorithm to generate stories. Through this system, 418 stories were generated automatically, of which 62% of the stories were particularly accurate. The experimental results verify that it is feasible to automatically generate stories based on personal Informative lifelogging data.

The high temperature of the grinding area at the engineering ceramic materials processing is one of the main factors affecting the quality of processing and the performance of parts. In order to reveal the law of temperature distribution of silicon, nitride ceramic grinding and its mechanism of action on surface quality. The process of machining silicon nitride ceramic material is simulated based on the established molecular dynamics model of the nanometric grinding of silicon nitride. The influence of grinding parameters on the nanometric grinding process is studied from the variation law of grinding temperature and the evolution of system energy, as well as the formation of grinding surface and metamorphic layer during machining. And the results of the experiment were compared with the theoretical research. With the increasing of grinding depth and speed of diamond grains, the energy released during the deformation and amorphous phase change of the atomic lattice get increased, and the grinding temperature get increased. The high grinding temperature will cause amorphous phase change in silicon nitride ceramics, and the amorphous atoms are recombined with the atomic bonds of the processed surface to form a metamorphic layer of the processed surface. The effect of grinding parameters on temperature changes from large to small is grinding wheel line speed, workpiece feeding speed, and grinding depth. There is an important effect on improving the surface machining quality and the service life of parts of engineering ceramics such as silicon nitride from the results of this paper, and it also plays an important role in reducing the effect of grinding temperature on the surface quality.

Si3N4-GCr15 (silicon nitride-bearing steel) friction pair is often used in high-speed bearings. The molecular dynamics model of graphene additive lubricating oil (mixed oil) is developed to study the effect of graphene as a nano lubricant additive on the thermal conductivity of the lubricating oil. With the research temperature range of 298~532 K, the results of internal molecular dynamics simulation show that the thermal conductivity of mixed oil increases with the increase in the graphene mass fraction at 298 K. When the temperature is higher than 298 K, the thermal conductivity of the mixed oil increases first and then decreases with the increase of the graphene mass fraction. When the mass fraction of graphene is constant, the thermal conductivity of the mixed oil increases first and then decreases with the increase of temperature. An experiment was designed to investigate the heat transfer coefficient for mixed lubricating oil at test specimen surface. Experiments show that an appropriate amount of graphene is added to improve the convective heat transfer between the lubricating oil and the test piece. However, as the amount of graphene added increases, the viscosity of the mixed oil increases, thereby inhibiting the fluid flow behaviour, resulting in a decrease in the convective heat transfer coefficient. This shows that only an appropriate amount of graphene additive has a cooling effect on Si3N4-GCr15 friction pair.

This study focuses on the radiation noise of ceramic angular contact ball bearings for motorised spindles. The differential equations of the vibrations for each bearing component are established, and the characteristics of various sound sources are analysed. Then, a multi-sound source method for calculating the radiation noise of a ceramic angular contact ball bearing is developed. The accuracy and validity of the proposed method are verified through numerical calculations and a corresponding experiment. Subsequently, the frequency spectrum characteristics of the radiation noise of the bearing components are discussed in detail according to the multi-sound source method. The radiation noise of each bearing component varies nonlinearly with the rotation speed, and the variation is consistent with the total radiation noise of the bearing. The eigenfrequency noise of each component appears clearly in the noise frequency spectrum. The results show that the proposed method can well predict the radiation noise of a ceramic angular contact ball bearing and provide a theoretical reference for the study of silent ceramic angular contact ball bearings for motorised spindles.

This paper focuses on the distribution characteristics of the radiation noise for a full-ceramic angular contact ball bearing (FCACBB). A model for calculating the radiation noise of a FCACBB was established based on the bearing dynamic characteristics and sound radiation theory, and the effectiveness and accuracy of the method were verified by corresponding experiments. The variation of the radiation noise for a FCACBB with the rotational speed was analyzed. The directivity of the sound field in the circumferential direction was found. The variation trends of the radiation noise in the friction load zone and the impact load zone were discussed. The attenuation of the radiation noise in the radial direction and in the axial direction was investigated. The directivity angle and the degree of directivity of the sound field were explored at different radial and axial distances. The results show that the inhomogeneous contacts between the bearing components in the circumferential direction result in different degrees of friction and impact vibration at different locations, which makes the radiation noise of the FCACBB have a larger component in the radial direction than in the axial direction. The conclusions can provide a reference for predicting the radiation noise of FCACBBs and further optimizing the sound field.

A thermal deformation prediction model of a high-speed motorized spindle is important for improving machining accuracy and reducing the thermal error in the spindle. The convective heat transfer coefficient reflects the internal heat exchange capacity of a motorized spindle. In the finite element thermal analysis of a motorized spindle, the heat transfer coefficient is used as the boundary condition to calculate the temperature field and thermal deformation. The accuracy of the convective heat transfer coefficient has the most evident effect on the thermal deformation prediction of the motorized spindle. In this paper, a method for optimizing the heat transfer coefficient based on the biogeography optimization algorithm is proposed for the 100MD60Y4 motorized spindle. The proposed method is used to develop a thermal deformation prediction model of an intelligent accurate motorized spindle. Accurate prediction of the thermal deformation of the motorized spindle is realized using the experimental data of the surface temperature of the motorized spindle. Experimental results show that the average prediction error after the optimization of the spindle bearing temperature is 0.22 °C. The average prediction error in the thermal deformation of the spindle is 0.72 μm. The developed model is more accurate compared with the conventional thermal deformation prediction model of the motorized spindle.

The thermal deformation of motorized spindle has a great influence on the precision of numerical control (NC) machine tools. Thus, it is crucial to predict the thermal deformation in the design and operation control phase by numerical simulation and improve the precision of NC machine tools. In order to achieve this, an accurate thermal deformation prediction model for motorized spindle is required. In this paper, a model for predicting the thermal error of motorized spindle based on finite element method and parameter optimization is proposed. Levenberg-Marquardt (LM) method is applied to optimize the heat transfer coefficient of motorized spindle by using surface temperature data measured. The optimized heat transfer coefficient is then taken as one of the boundary condition of the finite element model. The boundary conditions about heat of the finite element model are obtained by energy loss experiment. The proposed model is validated by experimental results, and the results have shown well correlation.