In order to solve overfitting of modeling in noisy circumstance, a normal function with corresponding training algorithm is proposed for wavelet networks based on wavelet sampling theory. Since such an algorithm can use sample distributions and errors respectively to train input and output weights, learning efficiencies of wavelet networks are improved greatly. In addition, the related theorems have also been given to demonstrate that the novel cost function can ensure minimization of the approximation error, the theories and experiments show that this novel cost function can ensure generalizations of wavelet networks. Data management module is responsible for data communication in the test process. It can obtain data from external or instrument drive module and transmit data to signal processing module for processing. When completion of the test, the test results are edited and printed through the affiliated function modules.

The Electromagnetic railgun is a new kinetic weapon with high initial velocity, long range and controllable energy release. It has broad application prospects in future national defense construction. Electromagnetic railgun works under extreme conditions such as high voltage, large current and strong load, its working state is extremely complex and there is a great risk, so numerical simulation and performance optimization of electromagnetic railgun are the key to the development of electromagnetic railgun. Based on the analysis of the working characteristics of the railgun, we establish a complete mathematical model of electromagnetic railgun system according to the interaction among power supply, rail, armature-projectile, etc., which provides a basis for subsequent simulation analysis and optimization.

Abstract In recent years, with the rapid development of integrated circuits and the widespread application of smart chips, the internal structure of complex electronic systems have become increasingly complex, which greatly increases the difficulty of board-level circuit testing and fault diagnosis of complex electronic systems. At present, traditional manual testing methods are no longer able to meet the maintenance requirements of modern complex electronic system board-level circuit. Therefore, the development of intelligent and universal automatic testing systems has become an important issue in fault detection of complex electronic systems. Based on the testing requirements of the automatic test system(ATS), this paper designs the corresponding overall scheme, software scheme and hardware circuit, and studies the fault diagnosis and test of board-level circuit of complex electronic system, and proposes to apply the traditional Bode diagram to the engineering practice of ATS. Fault detection is realized by utilizing the frequency domain characteristics of the object under test.

Abstract Tracking performance of naval gun servo system is very important to the whole combat function of naval gun weapon system. Therefore, it is very important to construct accurate mathematical model to improve the performance of servo system. This paper analyzed the structure of naval gun servo system in detail and established the transfer function of each component according to its working principle. Finally, the complete mathematical model of naval gun servo system is established through the organic combination of all parts. Then the stability of the mathematical model of naval gun servo system is judged by Rouse criterion. When the original servo system is unstable, it is necessary to modify the model of servo system by designing lead-lag correction to achieve stable control of the servo system, which lays a foundation for further research on control performance optimization based on mathematical model of naval gun servo system.

An electromagnetic railgun is a new type of weapon with ultrahigh speed based on electromagnetic thrust. It is used in important military domains, such as long-range strikes, strategic air defense, and ballistic interception. It is also used in aerospace fields, such as space debris cleanup, microsatellite launch, and space station relay launch, so its future prospects are excellent. We analyzed 1324 publications on electromagnetic railgun using CiteSpace and identified information including authors, institutions, journals, and popular research topics and trends. Our analysis found that the University of Texas is the research institution that has published the most documents on electromagnetic railgun, and French researcher Markus Schneider has published the most documents. The journals of IEEE Transactions on Magnetics and IEEE Transactions on Plasma Science have played an important role in promoting the development of electromagnetic railgun. The research direction of electromagnetic railgun has a distinct multidisciplinary characteristic because it touches on physics, engineering science, mathematics, materials science, energy and fuel, communication technology, instrumentation, and computer science. The development process of electromagnetic railgun can be grouped into three stages: basic theoretical research, engineering research, and system optimization research. The major research topics include electromagnetic force, armature design, rail materials, pulsed power supply, armature–rail contact surface characteristics, and coupling analysis of multiple physical fields. Future electromagnetic railgun will be scalable in terms of armature–rail contact characteristics and life span, energy storage density of power supply, current-carrying capability and thermal management of launcher materials, optimization design of armature structure, and complex data processing of control systems.

Abstract Traditional manual testing methods are no longer able to meet the maintenance needs of modern shipboard fire control system board-level circuits. Therefore, the development of intelligent and universal automatic test systems has become an important issue for shipboard fire control system fault detection. This article analyzes the performance and functional requirements of the automatic test system, develops the automatic test system based on PXI bus instruments, and designs an overall solution with signal time-frequency analysis capabilities that can carry out intelligent fault diagnosis for a variety of board-level circuits. On this basis, the design of hardware circuit and software solution is completed. The automatic test system was analyzed on hardware indicators and software functions. On the hardware side, the hardware resource selection was completed based on the hardware indicator requirements. On the software side, the overall software architecture design and the design of each functional module were completed based on the system software functional requirements. Finally, the composition and functions of each module of the system software and the overall operation process are introduced.

PMSM is a strong coupling system, which is very susceptible to disturbances and parameters variation. Thus, we propose a speed control based on wavelet neural network to optimize its performance. In order to verify the proposed method, we designed an experimental platform which has been used to demonstrate our design, and the experimental results show that there are jitter errors of the response speed with traditional PID control. However, by using the wavelet neural network PID control method, the jitter errors have been weakened and the response speed has been significantly accelerated. As a result, the control accuracy and the influence of jitters have both been dealt with well, therefore, the intelligent method can successfully improve the quality of the permanent magnet synchronous motor.

In order to solve the problem of finding out the frequency of signal through adaptive filter as soon as possible, the adaptive frequency search of adaptive filter has been focused in this paper. According to the change of the signal frequency, the proposed adaptive filter based on the technology of dichotomy decides the frequency of the input signal, realizes the narrowband filtering and the large dynamic variation of specific frequency signal. And the single frequency sinusoidal signal has been theoretically analyzed by the way of DTFT and discrete Fourier transform. Finally, the estimated value of the signal frequency has been preliminary measured by the method of DFT, then based on the characteristic of DFT, the dichotomy search for the real signal frequency has been designed so that the accuracy of frequency measurement would be guaranteed within 2Hz.

In order to solve the contradiction between the accuracy of weak signal acquisition and the limited frequency band, a weak signal acquisition system based on adaptive filter is designed in this paper. According to the change of the signal frequency, the proposed adaptive filter based on the technology of hardware adjustable narrowband filtering decides the frequency of the input signal, realizes the narrowband filtering and the large dynamic variation of specific frequency signal. And the high precision acquisition of weak signal can be obtained through the processing of filtering technologies under complex noise conditions, which includes adaptive frequency search, digital low-pass filtering, adaptive adjustment, etc. Finally, the test experiment of the designed filter has been implemented, and the experimental results show that the adaptive filter of the weak signal acquisition system can meet the design requirements and show high performance of data acquisition for weak signal.

In order to solve the problem of high precision acquisition of weak signals, a high accurately weak signal acquisition system has been designed in this paper. According to the proposed design requirements of the data acquisition system, the hardware acquisition circuit and the drive circuit as well as the processing of the upper computer are divided into modules. As the central work of this paper, the hardware and software of the drive modules are designed with specific flowcharts are given. And the designs of the system were debugged, analyzed and tested through experiment tests, and the high precision data acquisition of 0.5V DC signal has been obtained with specific datum are provided. The effectiveness of the proposed design to data acquisition of weak signal has been validated by the experimental results, and this design could be used in engineering projects.

To improve the Signal to Noise Ratio and the precision of data acquisition systems in the condition of broad bandwidth, an adaptive narrow-band filter circuit has been designed for obtaining weak signals in low-frequency domain. And the problems of classic filter circuits, such as wave form distortion and suffering from non-linearity of varactors, can be solved by the novel design in replacing varactor with voltage control capacitor. Simultaneously, by improving LRC filter circuit, our designs also can increase quality factor in traditional RC filter circuit. Therefore, this design has great advantages over classic filter circuits for its narrow frequency band, high quality factor and low signal deformation. The above properties of this circuit can make it used widely in removing noise for modulation and acquisition circuits with high precision, and can be used to obtain accurate band-pass filtering in low frequency bands, which has been verified by experiments showing superior advantages of improving the SNR and filtering effects.

Because sing traditional static neural network coping with continuous-time dynamic time may produce unsatisfactory control effect, a dynamic neural network (D-FNN) was adopted to design the speed controller to control PMSM vector control system. The D-FNN input and output are sliding mode switch function, sliding mode control function, respectively. The single input and single output neural network sliding mode control was achieved using D-FNN learning capability, which is not only can fully exert the characteristics of sliding mode control (SMC) which are insensitive to parameters change and disturbance, but also has the ability of fuzzy neural self-adjusting. The simulation results show that the proposed control scheme has stronger robustness.