Applied Mechanics and Materials Vols. 556-562

Abstract: Positioning errors were found through the analysis to AGPS positioning algorithm with mobile station (MS) clock error. These errors are engendered in the process of calculating the pseudo-range. Using fuzzy algorithm, the large positioning error of several hundred kilometers was eliminated. After this method, the objective function is quadratically related to the deviation of reference time. The objective function curve were fitted with three reference time values and determined the lowest point of curve to amend the reference time. This method removed residual positioning error.

Abstract: A multiple model cardinalized probability hypothesis density (CPHD) filter is proposed for tracking multiple maneuvering targets. The augmented state is established by combining the target motion mode with the kinematic state. Both the posterior cardinality distribution of the targets and the posterior probability hypothesis density (PHD) of the augmented state are jointly propagated by using CPHD recursion. Simulation results show that the proposed filter improves the estimation accuracy of target number and target states over the multiple model PHD filter and single model CPHD filter respectively.

Abstract: In the intelligent monitoring system of heavy machinery, the key technology is control algorithm because it is difficult to formulate exact mathematical model to the nonlinear and time-varying characteristic in heavy machinery. The monitoring system is firstly designed and developed for the universal system in heavy machinery. And then, RBF Neural Network is applied in the control strategy by OD2131 MCU(micro controller unit). The simulated curve is displayed by Matlab. Their dada communication between OD2131 MCU and Matlab is in CANopen protocol. Finally, the simulation is made for an electric motor. The simulation results show that adding artificial neural network compensation can enhance the accuracy in the intelligent control system.

Abstract: A trajectory tracking method based on feedback control in the virtual domain is proposed for the algorithm of online real-time trajectory planning. The method using the way that polynomials approximate states and differential equations convert into algebraic equations. Time domain is converted into virtual domain by introducing the virtual path. Moreover, using the feedback correction tracks fixed trajectory exactly by real-time information. In the background of intercepting of ballistic missiles, simulation verification is carried out on the condition of initial minor disturbances. The simulation results demonstrate that the miss distance, pitch angle error and yaw angle error can meet the requirements.

Abstract: Spindle wear of CNC machine affects the working efficiency of the machine. To solve this problem, the reasons for the generation of CNC machine tool equipment wear is analyzed, the system's hardware modules and software modules are designed and implemented in accordance with the system requirements. Parameters such as input and output power, spindle speed of CNC machine tool equipment are acquired by the sensor circuit. After a comprehensive analysis of the data, system software combined with neural network model displays the test results on the LCD screen, real-time output of CNC machine tool equipment operating status and the spindle wear. Thus the operation of CNC machine is ensured and equipment failure is avoided. Through the system test, indicating that the proposed system can real-time output the monitor results of spindle wear of CNC machine tool equipment, and has high measurement accuracy for the main parameters such as power and efficiency of the equipment.

Abstract: This paper researches a robust damage identification system considering the effects of the environmental and operational conditions based on distributed fiber Bragg grating system. Initially a well-verified method is used to identify damage, but the failure result is obtained. The environmental and operational variations causing the false-positive indication are analyzed, such as the temperature, the change of the excitation and the relaxation phenomenon of the sensors. The Hilbert-Huang Transform method is used to decompose the dynamic strain signal into several intrinsic mode function components, the physical meanings of which are discussed. Then the second level component is used as the damage-induced signal component. Lastly the damage index based on the autoregressive model and Mahalanobis distance is constructed to detect and locate damage.

Abstract: To effectively capture an unknown object, inertia parameters such as mass and inertia need to be confirmed. To measure the inertia parameter of unknown object, this paper proposes a measuring method applying to the collision process during capturing. This paper described the collision capturing model with the equivalent spring damping method, set up a collision dynamic mathematical model. Study the influence of the collision times and collision point location on precision of inertia parameter identification. The results show that, increasing the diversity of the collision point and the number of collisions, can reduce the condition number, and improve the identification accuracy. Based on the discernibility matrix made up by the 12 groups’ data in case 6, identification error can be dropped to less than 1%.

Abstract: Subjectivity education embodies the basic requirements of ideological and political education and has a profound meaning to improve ideological and political education effectiveness. Through practical experience in the field of ideological and political education, research experience with the actual investigation, and a combination of theory with practice, the author researches on coupling factor of subjectivity ideological and political education and the actual situation, with the use of factor principal component analysis to establish countermeasures model and makes in-depth study and optimization of the ideological and political education teaching science concepts and strategies.

Abstract: Objective: We do it to realize the wireless collection and transmission for heart sound signals, from the shape to simplify the equipment and to reduce the interference of the tested patients. Method: We use state-of-the-art 2.4G transmission technology to transport the heart sound signals collected by the front-end to the terminal of analysis. Results: We have successfully exploited the transmission equipment to transmit heart sound signals with good performance. Conclusion: By using the method can we realize the wireless collection and transmission for heart sound signals.

Abstract: This work presents a new method using Kalman filter (KF) and Least Squares Support Vector Machine (LS-SVM) for the inertial navigation systems (INS)/wireless sensors network (WSN) integrated navigation. In this mode, when the ultrasonic-based WSN is working well, LS-SVM is trained for the mapping between the position measured by INS and the corresponding error. Once the ultrasonic-based WSN is outage, the LS-SVM is used to predict the error of position, which is the unavailable measurement vector of the integrated filter when the ultrasonic-based WSN is outage. Thus, the filter in this mode is able to work where there is no data from the ultrasonic devices. The results show that the proposed method is able to provide continuous navigation information when the data of indoor positioning system is outage, and it is effective to reduce the probability of the estimating outliers.