Advanced Materials Research Vols. 317-319

Abstract: Because of discontinuity at threshold, hard threshold de-noising leads to the additional oscillation at threshold when reconstructing the signal, so that the smoothness of the de-noised signal becomes weak; Soft threshold de-noising method can guarantee the good continuity of the signal. However, for the existence of the fixed bias between the estimated threshold and actual threshold, there are also deviations between the reconstructed signal and the actual signal existing deviations too. In this work, by using the high performance DSP as a signal processing tool, we reduced the noise of actual measured vibration signal collected from headstock of CA6140 lathe. By comparing, the result is the same as the noise reduction simulation calculated from MATLAB, which demonstrates the noise reduction effect of wavelet adjustment factor threshold de-noising apparently.

Abstract: The stress response of fracture trauma section has certain inertia and pure lag, conventional PID control can not obtain optimal stress control accuracy. In allusion to this problem, this paper proposes using fuzzy adaptive PID control, aims at the optimal physiological stimulation stress (Jorgensen curve) in the course of fracture healing, conducts real-time control to the fracture trauma section stress. According to the established fracture trauma system model, the fuzzy self-adaptive PID controller has been designed, and conducts simulation research on real-time stress control in the Matlab/Simulink simulation environment. The simulation results show that the stress control accuracy of fuzzy self-adaptive PID control is obviously better than that of the classical PID control and classical fuzzy control, which can effectively control the stress of trauma section in fracture healing, to promote bone repair and bone growth towards the optimal level, and then to ensure the speed and quality of fracture healing.

Abstract: In order to extract pathological features of heart sound signal accurately, an algorithm for extracting the sub-band energy is developed based on the wavelet packet. The db6 wavelet is taken as the mother function, and the best wavelet packet basis of heart sound signal is picked out. Then, various heart sound signals are decomposed into four levels and the wavelet packet coefficients of the best basis are obtained. According to the equal-value relation between wavelet packet coefficients and signal energy in time domain, the normalized sub-band energy of the best basis is extracted as the feature vector. Based on BP network, seven identification models for seven kinds of heart sound were trained separately. Then, these models were tested by using 70 heart sounds, and the mean of identification accuracy is 72.9%.

Abstract: The paper presents on power electronics controlled rectifier faults diagnose technology based on the combination wavelet packet transformation and neural network mainly. By using the character of wavelet packet multiresolution, fault signal is decomposed at multi-scale, orthogonalation and normalization, extract feature vector, which as training input of neural network, and design classifier of fault pattern. The validity and feasibility of the fault diagnosis method is demonstrated by simulation. this method can quite accurately diagnosis fault and define fault element for power electronics controlled rectifier, and the diagnosis precision is high, the method has very good practical value and apply future on solving power electronics controlled rectifier fault diagnosis.

Abstract: This article combines the virtual instrumentation with the droplet analysis technique. According to the characters of the signal collected by the fiber capacity drop analyzer, the system employs dual channel acquisition. The design of the interface program is completed by invoking the Dynamic Library files of the data acquisition card, taking the advantages of the dynamic linking technology of LABVIEW. Friendly interface is designed. And the functions, such as data acquisition, display and save, are realized. The information acquisition system for the fiber capacitive drop analyzer is finally achieved by LABVIEW.

Abstract: The incremental optical encoder is widely used in PMSM servo system for speed detection. However, this method is detected the average speed, which will cause delay time, and make the speed control system unstable at low speed range. A speed observer was designed in this paper, which is combining state observer and Kalman filter to estimate instantaneous speed. Simulation results show that this method can improve the speed detection accuracy of the PMSM servo system.

Abstract: The brushless direct current motor(DC) simulation model based on neural network control strategy is developed, according to the physical structure of the motor, after the analysis of in-wheel motor mathematical model. The simulation has pulse width modulation (PWM) generation module,which can adjust the PWM duty cycle to regulate the motor speed. Simulation results show that there is good agreement between the output ofsimulation model and the theoretical analysis.The application of neural networkcontrol in brushless DC motor offers the advantages of rapid response, without overshoot ,and higher steady-state accuracy.

Abstract: By taking full advantage of the technologies of data acquisition, signal analysis and processing and fault diagnosis, this thesis carries out a research on the realization method of mine hoist bearing condition monitoring and fault diagnosis. Firstly, this thesis takes a technical analysis for rolling bearing. Secondly, based on determining the overall framework and using a virtual instrument software (Labview), it carries out a program development of the system. The developed system not only integrates the functions of traditional instruments, but also describes the bearing states and the types of bearing failure accurately according to the running status of the monitored bearings. It provides technical support for the mine hoist repair and maintenance and scientific protection for its safe running.

Abstract: The identification of the fuel types plays an important role in ensuring the safety and economics of the power plants. In order to obtain the flame signal in the process of combustion, a flame detection system is designed and a laboratorial platform is constructed. This paper extracts the signal parameters—the mean, the peak-peak value, the flicker frequency, and the flicker intensity —and takes them as the characteristic quantities of the flame signal. Based on the least squares support vector machines (LSSVM), an efficient method of identifying the flame types is developed. The result of the identification is more ideal, with the correct identification rate up to 100%. This shows that the method combined the four characteristic quantities with the LSSVM can obtain a good result in the identification of the fuel types.

Abstract: This document mainly analyses the sources of harmonic and harmonic hazards in power system. The article mainly from a few key links of power system which are electric power capacitor, power transformer, electric motors, relay protection to illustrate harmonic hazards and described harmonic treatment methods.