An SNN Ontology Based Environment Monitoring Method for Intelligent Irrigation System

In order to realize high precision of environment parameters detection in irrigation applications, a sensor and sensor network (SSN) ontology based data fusion method is proposed. An SSN sub-ontology for soilstate monitoring is revised, which includes the sensing devices hierarchies and measurement properties selection according to the detection feature interests. As for sensor data processing, a tuning data method by data pool filtering and clustering is adopted, as well as a useful data fusion method for multi-sensor system. The testing results show that both the accuracy and efficiency of the proposed method are higher after related filtering and clustering process, which enables a thorough monitoring for intelligent irrigation systems and can be extended into environment monitoring and control applications.     

Discretization Algorithm Based on Particle Swarm Optimization and Its Application in Attributes Reduction for Fault Data

In order to increase the fault diagnosis efficiency and make the fault data mining be realized, the decision table containing numerical attributes must be discretized for further calculations. The discernibility matrix-based reduction method depends on whether the numerical attributes can be properly discretized or not. So a discretization algorithm based on particle swarm optimization (PSO) is proposed. Moreover, hybrid weights are adopted in the process of particles evolution. Comparative calculations for certain equipment are completed to demonstrate the effectiveness of the proposed algorithm. The results indicate that the proposed algorithm has better performance than other popular algorithms such as class-attribute interdependence maximization (CAIM) discretization method and entropy-based discretization method.     

Inspection-Based Policy Considering Human Errors for Three-Stage Delay Time Degradation Systems

A periodic inspection policy for a single component system based on a three-stage failure process is proposed, and two different kinds of failures covering “hard” and “human” are considered in the proposed policy. The system is periodically inspected and inspections are perfect so that they can identify the intended defect. If the severe defect is detected by an inspection, an immediate repair is needed. However, once the system is identified to be in the minor defective state, there are two options. The first is to do nothing till the arrival of identifying the severe defect or hard failure, and the second is to repair immediately. Repair for any defect can renew the system with a limited probability such that the system may fail after repair due to human errors, which is common in many industrial applications. Two models are constructed by minimizing the expected cost per unit time and compared. We provide a numerical example to demonstrate the proposed model.     

Reliability Analysis of Systems with Common Cause Failure Based on Stress-Strength Interference Model

Many mechanical systems have the characteristics of multiple failure modes and complex failure mechanisms. On the basis of stress-strength interference (SSI) model, this paper takes the mechanical system with common cause failure (CCF) as the research object. The relationship between the stress distribution and the strength distribution is studied, and the failures of components are independent of each other under the deterministic stress. Then, the concept of conditional reliability is introduced to build the system reliability models under the action of one-stress and multi-stress for both series and parallel systems. Finally, the corresponding properties of the proposed methods are discussed to show their advantages.     

A New Fusion Chemical Reaction Optimization Algorithm Based on Random Molecules for Multi-Rotor UAV Path Planning in Transmission Line Inspection

A fusion chemical reaction optimization algorithm based on random molecules (RMCRO) is proposed to meet the special demand of power transmission line inspection. This new algorithm improves the shortcomings of chemical reaction algorithm by merging the idea of repellent-attractant rule and accelerates convergence by using difference algorithm. The molecules in this algorithm avoid obstacles and search optimal path of transmission line inspection by using sensors on multi-rotor unmanned aerial vehicle (UAV). The option of optimal path is based on potential energy of molecules and cost function without repeated parameter adjustment and complicated computation. By compared with an improved particle swarm optimization (IMPSO) in different circumstances of simulation, it can be concluded that the new algorithm presented not only can obtain more optimal path and avoid to trap in local minimum, but also can keep related sensors in a more stable status.     

Economic Dispatch of Islanded Microgrid Considering a Cooperative Strategy Between Diesel Generator and Battery Energy Storage System

For the impact of intermittent resources’ high penetration on the economic dispatch of islanded microgrid, a new economic dispatch method is presented to minimize the overall generating cost for islanded microgrid, considering a cooperative strategy between diesel generator (hereinafter referred to as DE) and battery energy storage system (BESS). The optimum economic operation range of DE and the optimal set-point between DE and BESS are presented in the cooperative dispatch strategy, in which BESS is used fully to enable DE in a lower cost and higher efficient way. The results are analyzed under various operation conditions and also prove the validity of the proposed method.     

Reliability Analysis of Aero-Engine Main Fuel System Based on GO Methodology

To improve the reliability of an aero-engine main fuel system, the quantitative and qualitative reliability analysis of the system is conducted based on goal oriented (GO) methodology. The quantitative reliability analysis results and the minimum cut sets of the fuel system are obtained, respectively. These results are compared with the results of the FTA (Fault Tree Analysis) method, and the comparison result shows GO method is rational and applicable. Therefore, it is feasible to apply the GO method in the reliability analysis of an aero-engine main fuel system.     

Relative Attitude Dynamics and Control of Spacecraft Formation Flying Considering Flexible Panels

As a key technology for orbital applications, researches on spacecraft formation flying (SFF) attract more attention. However, most of existing researches about dynamics and control of SFF focus on rigid spacecrafts without considering the effect of flexible attachments (such as flexible panels). In this paper, relative attitude dynamics and active control of SFF for a flexible spacecraft (follower spacecraft) and a rigid spacecraft (target spacecraft) are investigated. Firstly, a dynamic model of the flexible spacecraft is established by the principle of angular momentum. Then, the equation of relative attitude dynamics between the flexible spacecraft and the rigid spacecraft is derived by the quaternion to represent the attitude relation of the two spacecrafts. Finally, an attitude feedback controller is designed for the SFF system, and its stability is proved by the Lyapunov stability theory. Simulation results indicate that the panel flexibility has an obvious influence on the dynamic behaviour of the system, the designed controller can effectively control the attitude of the two spacecrafts to achieve synchronization, and the elastic vibration of the panels may be suppressed simultaneously.     

Cyclostationary Modeling of Surface Electromyography Signal During Gait Cycles and Its Application for Cerebral Palsy Diagnosis

Cerebral palsy (CP) is a group of permanent movement disorders that appear in early childhood. The electromyography (EMG) signal analysis and the gait analysis are two most commonly used methods in the clinic. In this paper, a cyclostationary model of the EMG signal is proposed. The model can combine the aforementioned two methods. The EMG signal acquired during the gait cycles is assumed to be cyclostationary due to the physiological characteristics of the EMG signal production. Then, the spectral correlation density is used to analyze the cyclic frequency (corresponding to the gait cycles) and spectral frequency (the frequency of EMG signal) in a waterfall representation of the two kinds of frequencies. The experiments show that the asymptomatic (normal) subjects and symptomatic subjects (with CP) can be distinguished from the spectral correlation density in a range of cyclic frequencies.     

Effect of Needle Coke on Gas Permeability of Ceramic Casting Molds

The permeability of a new investment casting mold system prepared by adding needle cokes has been investigated in this work. The permeability tests of the molds were carried out at the temperature of 25–1200 °C. The results showed that the addition of needle cork could significally increase the permeability of the molds by a factor of about 4 because the burning of needle cokes increased the porosities of the molds. Meanwhile, the needle coke modified molds exhibited higher green strength and greater thickness both on flat section and at sharp edges compared with the full fused silica mold. Taking account of the mold thickness, the needle coke modified molds had increased adjusted fracture load (AFL) by a factor of about 2 at the test temperature of 25–1200 °C. The addition of needle coke significally improved the permeability of the molds during both autoclaving and casting, and optimized the correlation between the permeability and green strength of the molds.