New high speed electric locomotives put into operation which use AC-DC-AC type of drive system has cause the influence of the electric railway load to the electrical network present the new features. In this paper, with the actual tests data in substation, researched the impact of 350km/h high-speed passenger line to grid power quality separately from harmonics, negative sequence and unbalance, voltage fluctuation and so on in the base of analyzing of CRH2C electric locomotive model and the work principle. Different with traditional AC-DC electric locomotive, high-speed passenger line which widely used CRH AC electric locomotive has the characteristics such as the high harmonic current frequency spectrum is rich and the negative sequence influence is remarkable. In addition, in view of high-speed passenger line load characteristic and its impact on the grid, this paper analyzed present several commonly used power quality control measures and given the corresponding government recommendations.
In this paper, for improving the control system of some bio-chemistry analysis instrument, an approach of microstepping control for the step motors based on Field Programmable Gate Array (FPGA) is presented after the microstepping driving theory of the step motor with a constant torque was discussed deeply. And then the relative control system is schematically designed, mainly includes the internal logic design of the FPGA, the Communication interface design of the Microcomputer, the design of the power driving circuit, and the design of the interface circuit between the electrical sources. At last, it is verified by some experimental investigations that the control theory and approach presented in the paper are corrective, and the control system designed is very good to get a high precision of position control and high control repeatability. So the technology questions from the producing reality are resolved and the product quality is promoted.
Since the electro-hydraulic servo shaking table exists many nonlinear elements, such as, dead zone, friction and blacklash, its acceleration response has higher harmonics which result in acceleration harmonic distortion, when the electro-hydraulic system is excited by sinusoidal signal. For suppressing the harmonic distortion and precisely identify harmonics, a combination of the adaptive linear neural network and least mean M-estimate (ADALINE-LMM), is proposed to identify the amplitude and phase of each harmonic component. Namely, the Hampel's three-part M-estimator is applied to provide thresholds for detecting and suppressing the error signal. Harmonic generators are used by this harmonic identification scheme to create input vectors and the value of the identified acceleration signal is subtracted from the true value of the system acceleration response to construct the criterion function. The weight vector of the ADALINE is updated iteratively by the LMM algorithm, and the amplitude and phase of each harmonic, even the results of harmonic components, can be computed directly online. The simulation and experiment are performed to validate the performance of the proposed algorithm. According to the experiment result, the above method of harmonic identification possesses great real-time performance and it has not only good convergence performance but also high identification precision.
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