Advanced Materials Research Vols. 605-607

Abstract: With the use of Visual C++ 6.0 programming development tools as the secondary development of Unigraphics NX (UG), dynamic link library DLL plug-ins were created. This paper takes fixed pedestal which is a standard part with assembly level of mold as an example, describing the parametric assembly modeling technology and implementation method of automatic virtual assembly process. The method can improve the design efficiency greatly by changing the related parameters of the parts to regenerate model fast and complete the design as well as assemble of fixed pedestal. It is proved that this method can meet the mould design requirements, and can be expanded and used for parameterized modeling and assembling of other standard parts with assembly level of mold in the practice.

Abstract: Rear frame is an important component of underground transport vehicle, used to carry different functional devices. This paper took rear frame as a research object. First of all, software Proe was used to set up geometrical model; secondly, software ANSYS was used to establish a FEM model to grid and set boundary conditions, and then analyzed rear frame stress and strain in working speed. The results showed that the deformation of rear frame is very small, meets the design requirements; the maximum stress of rear frame is far less than the allowable stress, which meets the strength requirements. It provides important theoretical basis for rear frame’s design.

Abstract: Common Mode Failure (CMF) analysis is an important method for evaluating the reliability, safety and risk of complex systems. As the increasing in the system complexity, the common-mode question has become an important factor for conditioning the reliability and security of the control system. Based the discussion on the concepts of CMF, this paper provided a CMF analysis method using Markov model, including the modeling and analysis process. A case study was also presented to verify the feasibility of the analysis method.

Abstract: Gear profile deviation means deviation of actual gear profile compared with normal gear profile which is calculated in the gear end plane erected with gear involutes. And it is a main project for assessing moving tranquility. But tradition measuring machines couldn’t own universality well, and they were prone to being impacted by human beings. The paper shows a new method that DMIS programs for inspecting gear profile deviation can be generated automatically in Pro/CMM software according to CAD model of gear and then coordinate measuring machine will be driven by them to inspect gear profile deviation. The measurement method can achieve high-precision measurement collection points, high efficient measurement process, less manual intervention and low-level error.

Abstract: The general idea of the reliability qualification test is described firstly, with the analysis of the test principle, reliability indicators and pilot programs is developed, according to characteristics of mechanical and electric equipments onboard and its specific circumstances in the real production applications, a series of parameters in the program have been discussed and limited, the possible problems in the implementation of the program have been taken into account, in order to maximize the promotion of effective reliability test of mechanical and electric equipments onboard, to make sure that it will be carried out smoothly.

Abstract: For the use of CNC machine tools is more and more extensive, its fault diagnosis research is becoming more and more important. Failure forms are diversified, and fault reasons are very complicated. Once bearing that is an important transmission part is in fault, the machining efficiency will decrease and affect process accuracy, even make the machine work abnormally. This paper presents a deep analysis of bearing failure mechanism using the wavelet analysis method identify its failure, specially the motor and transmission machine bearing, which provides reliable basis for fault diagnosis and forecast.

Abstract: A new drop hammer was designed and used for multiple reference impact testing of two bridges. The drop hammer utilizes a multiple-rebound control system for successfully applying a single impact with repeatable high-level force for bridge testing. Signal analysis results indicate that the drop hammer provides a higher signal-noise ratio and a better coherence even when the response signals are subject to pollution due to traffic on the bridge. Modal flexibility was computed by using the impact data from the drop hammer, and meaningful deflected shapes could be generated demonstrating the potential of the envisioned structural assessment system.

Abstract: Organic Light Emitting Displays (OLED) is a new type of display device which has become increasingly attractive and popular. Due to the complex manufacturing process, various defects may exist on the OLED panel. These defects have the characteristics of fuzzy boundaries, irregular in shape, low contrast with background and they are mixed with the texture background increasing the difficulty of a rapid identification. In this paper, we proposed an approach to detect these defects based on the model of independent component analysis (ICA). The ICA model is applied to a perfect OLED image to determine the de-mixing matrix and its corresponding independent components (ICs). Through the choice of a proper ICi row vector, the new de-mixing matrix is generated which contains only uniform information and is used to reconstruct the OLED background image. The defect result can be obtained by the subtracting operation between the reconstructed background and the source images. The detection system is implemented in the Labview and the testing results show that the ICA based OLED defect detection method is feasible and effective.

Abstract: The theory of artificial neural network and support vector machine has been introduced. According to the characteristics of vibration signal for the valve mechanism, fault diagnosis has been proposed for abnormal valve clearance based on artificial neural network (ANN) and support vector machine (SVM). Two kinds of intelligent technology have been compared in fault identification by changing the number of training samples. The diagnosis has indicated that at small number of training samples SVM has high generalization ability, and at large number of training samples, ANN has exact recognition when it comes to diagnosing valve train.

Abstract: Through the plentiful authentic early failure data collected by field tracing test of 30 CNC machining tools with ATC (Automatic Tool Changer), we searched for the rules and distribution of early failure of the CNC machining tools. Main fault mode and facts which usually make a great possible impact on the reliability of these products are identified based on an analysis of these early failure data. The distribution model of early failure is found by analyzing and processing these data with the method of regression analysis and hypothesis testing as well as Bayesian forecasting of early fault phenomena. Suggestions how to enhance reliability level of these products are proposed.