Along with the massive applications of the non-linear loads and the impact loads, many non-stationary stochastic signals such as harmonics, inter-harmonics, impulse signals and so on are introduced into the electric n...
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Along with the massive applications of the non-linear loads and the impact loads, many non-stationary stochastic signals such as harmonics, inter-harmonics, impulse signals and so on are introduced into the electric network, and these non-stationary stochastic signals have had effects on the accuracy of the measurement of electric energy. The traditional method like Fourier Analysis can he applied efficiently on the stationary stochastic signals, hut it has little effect on non-stationary stochastic signals. In light of this, the form of the signals of the electric network in wavelet domain will he discussed in this paper. A measurement method of active power based on multi-resolution analysis in the stochastic process is presented. This method has a wider application scope compared with the traditional method Fourier analysis, and it is of good referential value and practical value in terms of raising the level of the existing electric energy measurement.
Taking the heat exchange tube in the condenser as the research object, the three-dimensional finite element model of the heat exchange tube and the Internal and external fluid of pipe is established, and the bidirecti...
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This paper develops a segmented real-time dispatch model for power-gas integrated systems(PGISs), where power-to-gas(P2G) devices and traditional automatic generation control units are cooperated to manage wind power ...
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This paper develops a segmented real-time dispatch model for power-gas integrated systems(PGISs), where power-to-gas(P2G) devices and traditional automatic generation control units are cooperated to manage wind power uncertainty. To improve the economics of the real-time dispatch in regard to the current high operation cost of P2Gs, the wind power uncertainty set is divided into several segments, and a segmented linear decision rule is developed, which assigns adjustment tasks differently when wind power uncertainty falls into different segments. Thus, the P2G operation with high costs can be reduced in real-time adjustment. Besides, a novel segmented stochastic robust optimization is proposed to improve the efficiency and robustness of PGIS dispatch under wind power uncertainty, which minimizes the expected cost under the empirical wind power distribution and builds up the security constraints based on the robust optimization. The expected cost is formulated using a Nataf conversion-based multi-point estimate method, and the optimal number of estimate points is determined through sensitivity analysis. Furthermore, a difference-ofconvex optimization with a partial relaxation rule is developed to solve the non-convex dispatch problem in a sequential optimization framework. Numerical simulations in two testing cases validate the effectiveness of the proposed model and solving method.
The performance of anti narrowband noise of direct sequence spread spectrum (DSSS) communication system is investigated in this paper. The new result given in the paper shows that performance of anti noise in DSSS sys...
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To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is *** algorithm can recognize known jamming classes,detect new(unknown)jamming classes,an...
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To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is *** algorithm can recognize known jamming classes,detect new(unknown)jamming classes,and unsupervised cluseter new *** network of SNN-OWR is trained supervised with paired input data consisting of two samples from a known *** the one hand,the network is required to have the ability to distinguish whether two samples are from the same *** the other hand,the latent distribution of known class is forced to approach their own unique Gaussian distribution,which is prepared for the subsequent open set *** the test,the unknown class detection process based on Gaussian probability density function threshold is designed,and an unsupervised clustering algorithm of the unknown jamming is realized by using the prior knowledge of known *** simulation results show that when the jamming-to-noise ratio is more than 0d B,the accuracy of SNN-OWR algorithm for known jamming classes recognition,unknown jamming detection and unsupervised clustering of unknown jamming is about 95%.This indicates that the SNN-OWR algorithm can make the effect of the recognition of unknown jamming be almost the same as that of known jamming.
Based on the analysis of the feature of cognitive radio networks, a relevant interference model was built. Cognitive users should consider especially the problem of interference with licensed users and satisfy the sig...
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Based on the analysis of the feature of cognitive radio networks, a relevant interference model was built. Cognitive users should consider especially the problem of interference with licensed users and satisfy the signal-to-interference noise ratio (SINR) requirement at the same time. According to different power thresholds, an approach was given to solve the problem of coexistence between licensed user and cognitive user in cognitive system. Then, an uplink distributed power control algorithm based on traditional iterative model was proposed. Convergence analysis of the algorithm in case of feasible systems was provided. Simulations show that this method can provide substantial power savings as compared with the power balancing algorithm while reducing the achieved SINR only slightly, since 6% S1NR loss can bring 23% power gain. Through further simulations, it can be concluded that the proposed solution has better effect as the noise power or system load increases.
Fault diagnosis technology plays an important role in the industries due to the emergency fault of a machine could bring the heavy lost for the people and the company. A fault diagnosis model based on multi-manifold l...
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Fault diagnosis technology plays an important role in the industries due to the emergency fault of a machine could bring the heavy lost for the people and the company. A fault diagnosis model based on multi-manifold learning and particle swarm optimization support vector machine(PSO-SVM) is studied. This fault diagnosis model is used for a rolling bearing experimental of three kinds faults. The results are verified that this model based on multi-manifold learning and PSO-SVM is good at the fault sensitive features acquisition with effective accuracy.
Due to the difficulty in synthesizing perhalogenated metallophthalocyanine, the method of ammonium molybdate solid phase catalysis was introduced, and by using tetrachlorophthalic anhydride and urea as the raw materia...
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Due to the difficulty in synthesizing perhalogenated metallophthalocyanine, the method of ammonium molybdate solid phase catalysis was introduced, and by using tetrachlorophthalic anhydride and urea as the raw materials, hexadecachloro zinc phthalocyanine (ZnPcCl16) was synthesized. Components of the composite were analyzed by energy spectrum, and its functional group structures and absorption peaks were characterized by IR and UV-vis spectroscopy. The thin films of gas sensors were prepared in a vacuum evaporation system and evaporated onto SiO2 substrates, where sensing electrodes were made by MEMS micromachining. The optimal conditions for the films are: substrate temperature of 150 ℃ evaporation current of 95 A and film thickness of 50 nm. The result showed that the sensors were ideally sensitive to Cl2 gas and could detect the minimum concentration of 0.3 ppm.
Three-dimensional (3D) face recognition, as an important tool of modern authentication, is being causing concerns interests by more and more researcher. In this paper, a 3D measuring device for Chine-se adult's fa...
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Fault prediction technology of running state of electromechanical systems is one of the key technologies that ensure safe and reliable operation of electromechanical equipment in health state. For multiple types of mo...
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Fault prediction technology of running state of electromechanical systems is one of the key technologies that ensure safe and reliable operation of electromechanical equipment in health state. For multiple types of modern, high-end and key electromechanical equipment, this paper will describe the early faults prediction method for multi-type electromechanical systems, which is favorable for predicting early faults of complex electromechanical systems in non-stationary, nonlinear, variable working conditions and long-time running state; the paper shall introduce the reconfigurable integration technology of series safety monitoring systems based on which the integrated development platform of series safety monitoring systems is built. This platform can adapt to integrated R&D of series safety monitoring systems characterized by high technology, multiple species and low volume. With the help of this platform, series safety monitoring systems were developed, and the Remote Network Security Monitoring Center for Facility Groups was built. Experimental research and engineering applications show that: this new fault prediction method has realized the development trend features extraction of typical electromechanical systems, multi-information fusion, intelligent information decision-making and so on, improving the processing accuracy, relevance and applicability of information; new reconfigurable integration technologies have improved the integration level and R&D efficiency of series safety monitoring systems as well as expanded the scope of application; the series safety monitoring systems developed based on reconfigurable integration platform has already played an important role in many aspects including ensuring safety operation of equipment, stabilizing product quality, optimizing running state, saving energy consumption, reducing environmental pollution, improving working conditions, carrying out scientific maintenance, advancing equipment utilization, saving mainten
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