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This paper introduces the structural characteristics of a 6-D force sensor based on an E-type membrane, analyzes the calibration results of each bridge, and determines the coupling relationship between bridges of a sensor. In the case that a sensor has no fault in its bridges, a decoupling matrix is calculated by identifying a linear decoupling model. In the case that the fault happens, a linear neural network method is used to discard the faulty bridge to calculate the reduced-dimensional decoupling matrix, and the BP neural network nonlinear method is used to compensate the faulty bridge signal for fault-tolerant decoupling. Simulation results indicate that the reliability of the sensor under the fault condition has been significantly improved.

A method of global optimizing power generation is introduced in this paper. Under the condition of maintaining the same working hours of different units, electricity quantity generated between the different power suppliers is equal in one province, and it is also fulfilling the primary electricity schedule with a secure stable power system and low emission. This method is capable of minimizing resource consumption and emission while satisfying the power requirement by independently adjusting electricity generating units internally to optimum. Therefore, it is an important and effective way to promote energy saving in power generating and controlling.

With the rapid development of industry in China, the number of gas pipelines that are proposed or under construction is increasing year by year. Accidents such as fire, explosion, and toxic diffusion inevitably happen, which often cause a large number of casualties and property losses. It is increasingly important to analyze the risk along the gas pipelines realistically and to suitably plan, and utilize the surrounding land based on the risk analysis results, thereby reducing the hazards. A theoretical system for risk assessment along the gas pipelines is proposed in this paper. Risks of various major accidents are considered together, superposition effect is analyzed. After the individual risk distribution is obtained, risk zones are divided according to corresponding individual risk value of HSE, and land-use planning suggestions are proposed. Finally, a natural gas pipeline in China is used as an example to illustrate the risk assessment process and its application in urban land-use planning. The proposed method has a certain theoretical and practical significance in establishing and improving risk analysis along the gas pipeline and urban land-use planning.

An improved hybrid homotopy method is proposed to decouple the multi-input model of tactile sensors. The time-embedded homotopy algorithm is proved to be very suitable for solving the problem. Three tracking factors that control the efficiency of the algorithm are studied: tracking operator, stepsize, and accuracy. Trust region methods are applied to track the zero paths instead of the traditional differential algorithm, and a periodic sampling method is proposed to improve the efficiency of the algorithm. Numerical experiments show that both the robustness and accuracy have received a huge boost after the hybrid algorithm is applied.

The paper expresses two strategies for improving the sensitivity of capacitive pressure sensor. Microstructuring of dielectric elastomer surface can significantly increase capacitance response of the sensor due to raising permittivity and elasticity of dielectric. For the thin sensor, multi sensor units using stacked structure have multiplied effect in signal output.

In the present work, aiming at meeting the requirements of flexibility and three-dimensional force detection, a novel tactile sensor based on conductive and insulating rubbers was designed. Specifically, the microstructural unit consisting of three columns was orderly arranged in the cuboid made up of insulating rubbers. The microstructural units were prepared by conductive rubbers. According to the related theories of material mechanics, the relation between the resistance values of the columns and the applied three-dimensional forces was analyzed. Using COMSOL software, the multi-physical simulations were performed on the designed sensor, and the simulation results fit well with our conclusions on the variation tendency of resistance values. Finally, in order to eliminate the coupling effects among different dimensions, a decoupling algorithm based on BP neural network was proposed, and the results indicate that the designed sensor can accurately detect the three-dimensional force.

This paper presents a flexible tactile sensor, which uses a novel structure and effective decoupling method to detect multi-point three-dimensional touch force. Firstly, the structure characteristics of the sensor are introduced. According to the theories of force-sensitive conductive rubber, the relationship between the resistance and the force exerted on the sensor is analyzed. Furthermore the mathematical model of the sensor based on finite element method is conducted. The simulation result is consistent well with the theory result. Then a decoupling method based on the RBF neural network is proposed in order to obtain the force from the resistance. The research indicates that the flexible tactile sensor with the novel structure and the decoupling method can accurately detect the three-dimensional force.

In the Smart grid, network security is the important part. In this paper, we will introduce a new method detection based on Support Vector Machines to detect Masquerade attack, and test it and other methods on the dataset from keyboard commands on a UNIX platform. The presence of shared tuples would cause many attacks in this dataset to be difficultly detected, just as other researchers shown. In order to eliminate their negative influence on masquerade detection, we take some preprocessing for the dataset before detecting masquerade attacks. Our results show that after removing the shared tuples, the classifiers based on support vector machines outperforms the original approaches presented.