Applied Mechanics and Materials Vols. 687-691

Abstract: In view of the fixed testing point and complex wiring in conventional piggery environment control, a new system based on wireless sensor network was designed. This system consisted of the control center with ARM-Linux, executing mechanism nodes and wireless sensor network containing the flexible sensor nodes which could be arbitrarily placed in piggery. In order to make reasonable use of the energy of Zigbee network and prolong the survival time, a improved zigbee tree routing algorithm was proposed. First of all, by analyzing the advantages and disadvantages of the Cluster-tree and AODVjr algorithm in the Zigbee protocol, the neighbor table was introduced into the improved algorithm. Secondly, the scope of the destination node was confirmed to control the radio range of the RREQ and prevented invalid RREQ flooding. Simulation results show that the improved algorithm optimized the overall energy consumption effectively, prolonged the time of the critical nodes, reduced the number of death nodes, balanced the network load and improved the overall performance of the network.

Abstract: According to the characteristics of piggery, such as complex environment, numerous control objects, complex wiring, a piggery environment control system based on wireless sensor networks was designed. This system consisted of the wireless network composed of various devices and sensors in piggery, the control center with ARM-LINUX and the remote control center. The energy of sensor nodes was offered by batteries in wireless sensor networks so that the power source was limited. In order to strengthen the node energy management, the LEACH algorithm was combined with AODV routing protocol, and a new optimization algorithm called LEACH-A was proposed in this paper. The wireless sensor networks execution process was divided into two phases, including cluster building and data transmission. In the two phases, the node residual energy was calculated by a weighted function and the cluster head role was changed by the size of remaining energy. NS-2 simulation results show that the proposed algorithm prolonged the lifetime of the nodes and the networks, and realized the energy optimization management.

Abstract: Systematic approach for the transmission line positive sequence parameters, temperature, and sag based on wavelet analysis to detect error is developed in this work. Unbiased (random/Gaussian) error such as, transient meter failures, transient meter malfunction, and measurements captured during system transients, are inherently in the form of large abrupt change of short duration in a measurement-sequence. These should be detected before the data is used because their presence will lead to insecure and unstable of power grid. The test results of the proposed method based on data of Sichuan power grid are presented.

Abstract: In order to confirm the reliability and accuracy of the excess heat triggered by current in the previous work [1-3], a new designed and built heat-flow calorimeter [4] was introduced in the same D/Pd gas-loading system as mentioned previously. The calorimeter was calibrated in nitrogen atmosphere and the results between the input power (P) and the exothermal electromotive force (V) could be simulated by a quadratic equation: P = (15.356 ± 0.068) V – (0.014 ± 0.039) V². The maximum excess power (6.398 ± 0.191 W) were found at the condition of an optimum current (8.47 A) and a deuterium pressure (3 × 10⁴ Pa). The reproducibility was 3/3 and the total excess energy released in these experiments was about 0.70 ± 0.02 MJ within 40 hours, which means (1.6 ± 0.1) ×10³ eV for each palladium atom. The excess heat power and excess heat energy were far more than that in a chemical reaction.

Abstract: In the paper, ultrasonic testing of austenitic stainless steel pipeline welding cladding is stimulated based on ultrasonic testing software CIVA. The result shows that the frequency is higher; the sensitivity on small defect testing is higher. When cylindrical defect with length of 6mm and diameter of 2mm is detected, the frequency is higher, the tested length-section result is more accurate, and the width-section (i.e., diameter) is not affected. The optimum frequency scope for testing the defect should be between 5MHz and 10MHz.

Abstract: For engine fault diagnosis problem, an engine fault diagnosis method based on particle swarm optimization algorithm is proposed. The velocity and spatial position of all the particles in the particle swarm are updated, in order to provide accurate data basis for the engine fault diagnosis. Particle swarm optimization method is utilized to process iteration for all particles, so as to determine whether failure exists in components of engine. Experimental results show that with the proposed algorithm to diagnose engine fault can effectively improve the accuracy of fault diagnosis, and achieved the desired results.

Abstract: Thermoelectric couple was employed in traditional airplane engine temperature measurement system with the disadvantages of large size,heavy weight,big error and slow response.This paper presents a new kind of real—time temperature measurement system using laser diode InGaAs/I as light source,and using pyroelectric detector LiTa03 as optical receiving unit and using a microprocessor as signal processing center.This instrument consists of three parts:optical emitting and receiving system,signal amplifying and controlling system,and display system。The principle and structure of the system are introduced.Experimental results of airplane engine real—time temperature measurement show that temperature measurement accuracy and response time conform to our requirement in the range of 300°C一800°Cand agree with prediction of theory.All these prove that the design is correct.

Abstract: In order to realize functions of automatic monitoring, alarming and extinguishment on fire in crude oil storage tank, the paper came up with a fire detection model with multisensor, including selective module with fire feature combination, supervised training module and fire detection module. By regarding PNN as a classifier to carry out tests on effectiveness of the model, the conclusions that the model can reduce the influence of fire parameters’ fluctuation on detection results was drew. Moreover, an excellent fault-tolerant ability was possessed at the same time. Through some confirmatory experiments, The phenomenon was reached that two kinds of parameters in adoptive four parameters have no normal fire signal, but the model still can greatly distinguish from correct fire state.

Abstract: The study of existing deficiencies, on the basis of overhead transmission line fault detection based on radial basis function (RBF) neural network theory, the fundamental frequency power spectrum as characteristic vector of fault signal, this paper proposes a new method of transmission line fault type identification. The system with complex structure of 10 KV overhead transmission lines as the research object, on the basis of the transmission line model is established by using Simulink software, for different types of short circuit fault simulation sampling, extract fault features, combined with the zero sequence current, as the input vector, establish the RBF neural network for fault type. Results show that: the fundamental frequency in fault signal power spectrum as the feature vector is easy to extract, information is more concise, the RBF neural network in the feasibility in training high, identify accurately and quickly.

Abstract: This document explains a system of open pit slope deformation monitoring. After calculating data by software of GPS Solution and the system which bases on the signal of GPS receiver obtain information of every GPS receiver. So it can get GIS information of whole coal mine. If there is any abnormal data, it will report to the police timely, and directly control the running of coal miningmachines through PLC. Compared with the technology before, the system has higher automation integration, higher positioning accuracy, gets more responsive and provides more reliable data. It’s the best choice for long-term spatial structure monitoring and condition assessment.