Applied Mechanics and Materials Vols. 34-35

Abstract: The acoustic emission extraction experiment of rotor crack fault has done on the rotor comprehensive fault simulation test-bed. Characteristics of acoustic emission signal of different crack rotors in various depth and conditions are analyzed. The noise-disturbing problems and the noise-eliminating methods of the acoustic emission signal were researched in the paper, and the comparison has been done with the vibration method of crack fault diagnosis by the experiment. The advantages of acoustic emission technique has been highlighted in the early period crack fault diagnosis. The wavelet packet technique was applied to obtain the characteristics of acoustic emission signal of the rotor crack propagation. the diagnosis results are shown to be quite clear, reliable and accurate.

Abstract: The faults of rotating machinery are monitored by fixing the sensors on rotor directly, which brings some problems such as difficulty in fixing the sensors, poor universality and so on, while brings some advantages such as rapidness, convenience and good universality and so on by fixing the sensors on the base. The arrangement of sensors on rotating machinery base was designed by taking advantage of the vibration transitivity of rotor-bearing-base, which will provide a new method for fault diagnosis of rotating machinery. The solid model of rotor test bench was built by combining with PROE and ANSYS. The transient analysis of rotor test bench was done, and the vibration response characteristics of base and the arrangement of sensors were obtained. Finally, the validity of the sensor arrangement was verified by experiments.

Abstract: This paper considers the analysis of the mechanical behaviour of a laminate constituted of 12 layers of glass fiber fabric/epoxy resin conditioned at different relative humidities of 0, 60 and 96% at 60 °C. The analysing of the experimental results obtained of hygrothermal ageing on the mechanical response has permited to show that the influence of the moisture concentration on the ultimate mechanical properties becomes significant and important for the composite conditioned at relative humidity of 96% to the periods I and II (state of saturation and ageing).

Abstract: Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. In this paper we propose an optimal algorithm with genetic algorithm taken into consideration, and compare it with three well known and widely used approaches, i.e., LEACH and LEACH-C, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, and data delivery at the base station than the other routing protocols. Key words: Wireless sensor networks, base station, heuristic optimized genetic algorithm, low energy adaptive clustering hierarchy

Abstract: In elliptic curve cryptography, reverse-mode operation is the impact on the efficiency of digital signature one of the most important factor. Analysis of the limited domain of elliptic curve digital signature process, to prove the correctness of the algorithm, a non-mode based on the inverse operation of the elliptic curve digital signature algorithm, the algorithm does not reduce the security on the basis of improved algorithms Efficiency.

Abstract: To achieve the highly reliable and highly accurate adjustment for electrohydraulic proportional pump A4VSO, an adjustment system is established, in which a servoproportional valve replaces a servo valve or a proportional valve. Then its mathematic model is obtained and simulated on Matlab/Simulink, and performance tests about pump displacement and output flow of the pump are carried out under different pressures. Both simulation and experimental results indicate that the adjustment system controlled by servoproportional valve is characterized by higher steady accuracy and more reliability, both the pump displacement and output flow of the pump A4VSO maintain proportional to the control signal, respectively.

Abstract: In press working, to prevent defects in sheet products and establish the traceability of the causes of defects, we have developed defect detection dies incorporating several types of sensor, including load sensors, fiber laser sensors, ultrasonic sensors and optional sensors. Typical defects such as the rising of pierced scraps, burrs, spring-back/spring-go and wrinkling can be detected using the defect detection dies, i.e., the intelligent forming dies. The real-time defect inspection of all products will be possible. This system can be used to identify defective products on the basis of sensor information compiled in a database. The causes of defects can be clarified from the situation in real time.

Abstract: Traditionally, tolerance and maintenance designs have been studied separately in manufacturing systems. An integration optimization model of tolerance and maintenance for multi-station sheet metal assembly was presented in this work. Based on the variation propagation state space model, a quality loss model of multi-station assembly processes was built. This model considered the effect of process loss. It built the function of fixture tolerance, replacement cycle and total cost. The nonlinear tolerance optimization of locating holes (slots) in multi-station sheet metal assembly was achieved. The optimization model was calculated with practical data in a vehicle body side assembly. Compared with the same type model, it’s verified correct and rational of the model in multi-station sheet metal assembly process quality control.

Abstract: Baysesian Neural Network approach for predicting the temper embrittlement of steam turbine rotor in service was proposed. The FATT50 (the fracture appearance transition temperature) of the rotors was predicted as a function of ratio of the two peak current densities (Ipr / Ip ) tested by electrochemical potentiodynamic reaction method, temperature of electrolyte, J-factor and grain size ( N ). A database was obtained from the test of electrochemical potentiodynamic reaction and Charpy impact. The Bayesian neural network technique was used for modeling of temper embrittlement. The neural network shows a more precise prediction of temper embrittlement of rotor steels than the prediction using multiple linear regression. The training error and verifying error is with the scatter of ±20°C. The results show that, for the temper embrittlement of rotor steels prediction, the prediction model based on Bayesian neural network is feasible and effective.

Abstract: The static and dynamic characteristics calculating of the whole machine structure by finite element method lead to dense grid nodes, which is not conducive to rapid quantitative analysis. Therefore, a simplified model and the corresponding static and dynamic characteristics are needed. This paper presents a simplified model using key nodes kept principle and a corresponding software which reads data from resulting data file, extracts information such as coordinates, static and dynamic displacement of relevant nodes from reading data and draws simplified models of the whole machine structure and static and dynamic deformation of it. Take XK173 Vertical Milling Machine as the case research object, establish a complete machine model, analyze the static and dynamic characteristics and reproduce that using simplified model by software. The result shows that the Vertical Milling Machine nodes are reduced from the original 153 238 nodes to156 nodes. It well preserves machine structure and static and dynamic characteristics, and lays foundations for simplifying follow-up quantitative analysis.