Key Engineering Materials Vols. 375-376

Abstract: Laser cutting error has large influence on the beam width of intravascular stents. Minor random variation in beam width of stents may significantly impact the expansion uniformity. In this paper, the relevant factors that may affect the beam width during the manufacture are investigated. Based on the randomization model, the pattern how the factors affect expansion uniformity is explored, and the method for calculating uniformity index is proposed. A detailed computation is made on the width randomization for the two expansion elements. The results show that with the increase of the value range of beam width, probability of uniformity index decreases gradually; the strengthening factor has large effect on the expansion uniformity. The method is meaningful for studying how the processing error affects expansion uniformity.

Abstract: Ultrasonic vibration aided electrical discharge machining (UEDM) in gas is a new machining technology developed in recent years. This technology uses air or oxygen as dielectric and ultrasonic vibration is applied to the workpiece during machining. UEDM in gas can avoid environment pollution, the most serious disadvantage of conventional EDM in kerosene-based oil or other dielectric fluids, and it is environmental-friendly. The technology also has virtues of wide applications, high machining efficiency, and simple tool electrodes and so on. In this paper, the formation and transformation of the spark plasma and the mechanism of material removal during a single pulse discharge are introduced.

Abstract: In this paper, a micro milling model is brought forward. The influences of different metal phases and the minimum chip thickness are considered in the model. The cutting forces and the surface generation in the micro milling process are predicted. Through the experiment validation, the results correlate to the model very well.

Abstract: The present work puts forward a generalized simulation model to evaluate the topography of ball-end milled surfaces by considering both the tool deflection and the tool runout. Firstly, a solid ball-end mill with S-shaped cutting edges is modeled as the basis. Then the tool tip trajectory is derived from the tool runout as well as the cutting forces induced tool deflection. And consequently the topography and scallop height of the machined surface are estimated by the numerical calculations of the matrix equations. With good expandibility, the proposed model can incorporate more machining information such as the movements of rotatory axes and tool wear, and hence, can be used to optimize the cutting conditions and parameters in 5-axis ball-end milling process.

Abstract: The theory and the algorithm of Particle swarm optimization (PSO) based for neural network training were applied in the research of the modeling of milling force in high speed machining. The PSO was used to train connection weights of multi-layer feed forward neural network until the fitness error tended to be stable. Then BP algorithm was adopted to accomplish cutting force forecasting based on optimized initial weights, which take full use of the global optimization of PSO and local accurate searching of BP. The results of simulation showed that with comparison with other BP algorithms, PSO-BP not only effectively shortens the time of training networks, but also greatly improves the accuracy of prediction and universal approximation. PSO technique can act as an alternative training algorithm for ANNs.

Abstract: This paper studies the grinding temperature field of non-quenched and tempered steels grind-hardening technology using experiments and finite simulation. A mathematical model of grind-hardening temperature field is established to investigate steel 48MnV which is used for making crankshaft. The grinding temperature field is simulated and the hardened depth is forecasted by finite-element method with the triangular shape of the heat source model based on the ANSYS software. The experimental results show that the simulative temperature and estimating hardened depth are comparatively close to the measuring ones. The model could be utilized to forecast the distribution and variation characteristics of the grinding temperature field and the hardened layer depth.

Abstract: The uniform distribution and the stability of the substrate temperature are the most important factors that deeply affect the quality and the growth rate of diamond films. In this paper, cemented carbide cutters were chosen for substrates, the 3D finite element (FE) model of filaments and substrates was developed in ANSYS 8.0, the calculated results show that the substrate temperature is influenced by the filament temperature, filaments diameter, the quantity of the filaments and the distance between the filaments and the substrates. The 3D finite element model of filaments and substrates also provides a basis for selecting the parameters to obtain uniform diamond films in miniature EACVD system.

Abstract: The remote monitoring and intelligent maintenance is one of the most important criteria for evaluating a product or a service. This paper focuses on the large asphalt mixing plant, an internet/intranet technology-based Browser/Server structure model of remote intelligent maintenance system for asphalt mixing plant is designed. The critical technologies of realizing the system which include the fieldbus-based data collection technology, the database technology, the intelligent fault diagnosis technology as well as the ASP technology are deeply studied respectively. The remote monitoring and intelligent maintenance system will well provide an effective and efficient activity that meets the customers’ requirements and satisfaction.

Abstract: Effects of running state and spindle speeds on the sound signals produced from a drill press are investigated. And the obtained sound signals by using of a sound level meter are analyzed in both time domain and frequency domain. It is evident that there is more high frequency energy for drilling sound signals with load than without load. And spindle speeds still affect their energy distribution of drilling sound signals. Using wavelet decomposition and wavelet packet decomposition, drilling sound signals are decomposed into a number of frequency bands. And energy percentages of the divided frequency bands are extracted to be the effective characteristics to recognize spindle speeds. Meanwhile, training error of different BP networks is compared to obtain the effective network for recognition spindle speeds. By using of the obtained network structure named 16-30-5, the study rate for training samples and the recognize rate for testing samples are all above 95%.

Abstract: The thermal error model of the ucp710 5-axis machine tool was acquired by the homogeneous coordinate transformation, and includes 17 thermal error components. The thermal behavior of the ucp710 machine tool has been tested and the temperature fields were recorded by the compensation control and temperature sensing systems. The developed compensation system has been applied to the ucp710 5-axis machine tool, and the accuracy has been improved about 1 times after compensation, demonstrating a very high potential for the error compensation of CNC machine tools.