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AbstractCurrent wind turbine (WT) studies focus on improving their reliability and reducing the cost of energy, particularly when they are operated offshore. WT Supervisory Control and Data Acquisition (SCADA) systems contain alarm signals providing significant important information. Pattern recognition embodies a set of promising techniques for intelligently processing WT SCADA alarms. This paper presents the feasibility study of SCADA alarm processing and diagnosis method using an artificial neural network (ANN). The back-propagation network (BPN) algorithm was used to supervise a three layers network to identify a WT pitch system fault, known to be of high importance, from pitch system alarm. The trained ANN was then applied on another 4 WTs to find similar pitch system faults. Based on this study, we have found the general mapping capability of the ANN help to identify those most likely WT faults from SCADA alarm signals, but a wide range of representative alarm patterns are necessary for supervisory training.
In view of application requirements, control axes, the development cycle and other factors of open CNC machine tools, we consider the modular as the guiding ideology and propose a design method of three-dimensional engraving and milling machine based on open CNC system. In this paper we make a detailed design for mechanism structure and control system. Experiments show that this machine has milling and engraving capabilities, can process metal and non-metallic parts, which is a high efficiency, multi-function numerical control equipment.
In this paper, a hybrid system to carry out the function of photovoltaic power generation and power quality control simultaneously was proposed. The configuration and principle of the hybrid system were discussed firstly, and then the mathematical model of the hybrid system was presented. To realize the compound function, a deadbeat compound control strategy was proposed. In the compound control strategy, the calculation method of the reference signal is proposed to achieve reactive power and harmonic detection, active signal for grid-connected electricity generating and DC-side voltage maintaining; to improve the dynamic response and decrease the steady-state error of the hybrid system, deadbeat compound control method was proposed. The new hybrid system is implemented in a 10kVA prototype in the laboratory. Simulation and experimental results show that the proposed hybrid system can effectively stabilize photovoltaic power generation, reactive power compensation, and harmonic elimination.
We study the natural filtrations of the finite-dimensional modular Lie superalgebras W (n, m) and H(n, m). In particular, the natural filtrations which are invariant relative to the automorphisms of the Lie superalgebras are employed in order to characterize the Lie superalgebras themselves.
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