The paper aims at the higher reactive power management complexity caused by the access of distributed power, and the problem such as large data exchange capacity, low accuracy of reactive power distribution, a slow convergence rate, and so on, may appear when the controlled objects are large. This paper proposes a reactive power and voltage control management strategy based on virtual reactance cloud control. The coupling between active power and reactive power in the system is effectively eliminated through the virtual reactance. At the same time, huge amounts of data are treated to parallel processing by using the cloud computing model parallel distributed processing, realize the uncertainty transformation between qualitative concept and quantitative value. The power distribution matrix is formed according to graph theory, and the accurate allocation of reactive power is realized by applying the cloud control model. Finally, the validity and rationality of this method are verified by testing a practical node system through simulation.
A new soft-fault diagnosis approach for analog circuits with parameter tolerance is proposed in this paper. The approach uses the fuzzy nonlinear programming (FNLP) concept to diagnose an analog circuit under test quantitatively. Node-voltage incremental equations, as constraints of FNLP equation, are built based on the sensitivity analysis. Through evaluating the parameters deviations from the solution of the FNLP equation, it enables us to state whether the actual parameters are within tolerance ranges or some components are faulty. Examples illustrate the proposed approach and show its effectiveness.
While the Slope Fault Model method can solve the soft-fault diagnosis problem in linear analog circuit effectively, the challenging tolerance problem is still unsolved. In this paper, a proposed Normal Quotient Distribution approach was combined with the Slope Fault Model to handle the tolerances problem in soft-fault diagnosis for analog circuit. Firstly, the principle of the Slope Fault Model is presented, and the huge computation of traditional Slope Fault Characteristic set was reduced greatly by the elimination of superfluous features. Several typical tolerance handling methods on the ground of the Slope Fault Model were compared. Then, the approximating distribution function of the Slope Fault Characteristic was deduced and sufficient conditions were given to improve the approximation accuracy. The monotonous and continuous mapping between Normal Quotient Distribution and standard normal distribution was proved. Thus the estimation formulas about the ranges of the Slope Fault Characteristic were deduced. After that, a new test-nodes selection algorithm based on the reduced Slope Fault Characteristic ranges set was designed. Finally, two numerical experiments were done to illustrate the proposed approach and demonstrate its effectiveness.
To overcome the detrimental influence of α impulse noise in power line communication and the trap of scarce prior information in traditional noise suppression schemes , a power iteration based fast independent component analysis (PowerICA) based noise suppression scheme is designed in this paper. Firstly, the pseudo-observation signal is constructed by weighted processing so that single-channel blind separation model is transformed into the multi-channel observed model. Then the proposed blind separation algorithm is used to separate noise and source signals. Finally, the effectiveness of the proposed algorithm is verified by experiment simulation. Experiment results show that the proposed algorithm has better separation effect, more stable separation and less implementation time than that of FastICA algorithm, which also improves the real-time performance of communication signal processing.
Finding effective ways to efficiently drive roadways at depths over 1 km has become a hotspot research issue in the field of mining engineering. In this study, based on the local geological conditions in the Xinwen Mining Area (XMA) of China, in-situ stress measurements were conducted in 15 representative deep roadways, which revealed the overall tectonic stress field pattern, with the domination of the horizontal principal stresses. The latter values reached as high as 42.19 MPa, posing a significant challenge to the drivage work. Given this, a comprehensive set of innovative techniques for efficiently driving roadways at depths over 1 km was developed, including (i) controlled blasting with bidirectional energy focusing for directional fracturing, (ii) controlled blasting with multidirectional energy distribution for efficient rock fragmentation, (iii) wedge-cylinder duplex cuts centered on double empty holes, and (iv) high-strength supports for deep roadways. The proposed set of techniques was successfully implemented in the –1010 west rock roadway (WRR) drivage at the Huafeng Coal Mine (HCM). The improved drivage efficiency was characterized by the average and maximum monthly advances of 125 and 151 m, respectively. The roadway cross-sectional shape accuracy was also significantly improved, with the overbreak and underbreak zones being less than 50 mm. The deformation in the surrounding rock of roadway (SRR) was adequately controlled, thus avoiding repeated maintenance and repair. The relevant research results can provide technical guidance for efficient drivage of roadways at depths over 1 km in other mining areas in China and worldwide.