Advanced Materials Research Vols. 765-767

Abstract: The EEDM(Ensemle Empirical Mode Decomposition) combined with correlation coefficient was proposed for identify the fault of rolling bearing. First, the fault of rolling bearing vibration signal will be decomposed into several IMF components, in view of the illusive component may appear in EEDM components, respectively calculate each IMF components and the correlation between the original signal, then carry out spectrum analysis to each IMF components and pick up fault feature. Through the experimental failure data analysis of rolling bearing inner ring, the EEMD method is good for fault identification of rolling bearing.

Abstract: This paper proposes a monitoring system for factory aquaculture, which collects data and sends them via wireless sensor network (WSN). This monitoring system consists of front-end equipment and upper computer. The front-end equipment is a wireless sensor network consisting of several sensor nodes with different functions and one coordinator node. The upper computer includes monitoring software to monitor the water quality parameters. We mainly focus on designing the solution of monitoring system, the connection circuit between RS232 and SP3232E, as well as the flow of sampling application. Experimental results show that our monitoring system can meet the basic requirements for monitoring the water quality parameters.

Abstract: In this paper, combining with research situation at home and abroad,the gear parameters extraction methods were compared,including point cloud extraction in reverse engineering, image measurement technology and traditional measurement technique, etc. Analyzes the various technical method,At last,gear parameter extraction of the prospects for development are put forward.

Abstract: Neural network and Fault dictionary are two kinds of very useful fault diagnosis method. But for large scale and complex circuits, the fault dictionary is huge, and the speed of fault searching affects the efficiency of real-time diagnosing. When the fault samples are few, it is difficulty to train the neural network, and the trained neural network can not diagnose the entire faults. In this paper, a new fault diagnosis method based on combination of neural network and fault dictionary is introduced. The fault dictionary with large scale is divided into several son fault dictionary with smaller scale, and the search index of the son dictionary is organized with the neural networks trained with the son fault dictionary. The complexity of training neural network is reduced, and this method using the neural networks ability that could accurately describe the relation between input data and corresponding goal organizes the index in a multilayer binary tree with many neural networks. Through this index, the seeking scope is reduced greatly, the searching speed is raised, and the efficiency of real-time diagnosing is improved. At last, the validity of the method is proved by the experimental results.

Abstract: For the purpose of screening drivers with higher than normal temperature, we developed a device based on Forward-looking Infrared Imagery (FLIR). Infrared curtain is used to detect the height of vehicle for the automatic positioning mechanism, face recognition technology is used to overcome sources of interferences, a dynamic equivalent temperature screening method is developed to distinguish the drivers with higher than normal temperature. This device was tested in Huang gang Port and had a good result, now it has become a standard facility in port of entry.

Abstract: Obtaining the fault information online may eliminate many potential fatal accidents, in order to inspect and resolve the online fault diagnosis problem in process industry, an online fault diagnosis model based on IoT(Internet of Things) is proposed in the paper. the model is composed as four layer of user layer, application layer, basic technology layer and resources layer, and it can use the resources effectively such as virtual organizations, entity organization, equipment, network resources and so on, the basic technologies such as Internet of things, multiple information collection, knowledge engineering and application technologies were analyzed in the paper too. Finally, an application system is developed, and it proved the model is validity and correctness.

Abstract: This paper presents service scenario, classification and service requirement of Electronic health monitoring (EHM), which are very important for standardization.

Abstract: A dual-mode receiver combination of GPS and Compass (BD) is introduced on the assumption when only one of the satellites had a failure, how to implement a weighting RAIM monitoring. And the GPS and BD in single mode and the GPS/BD dual-mode were simulated to produce the Fault Detection Rates and RAIM integrity availability. It is demonstrated that the dual-mode RAIM algorithm is superior to any kind of single-system RAIM algorithms.

Abstract: This paper introduces T/4 time-lapse elimination detection, a novel method of detecting three-phase magnitude based on double d-q synchronous reference frame, functioning in decoupling positive and negative sequences of fundamental wave. When the voltage (or current) fundamental positive and negative sequence components are separated, their magnitudes can be detected respectively, so it is effective to restrain the impact on detection precision from negative sequence component. To verify the performance of this novel method, simulation experiments like transient response under normal grid condition and dynamic response under three-phase unbalance with harmonic pollution condition is finished. The results indicate that the novel method obtains a high precision of measure and a better dynamic property and has advantages on preventing harmonic propagation compared with T/16 time-lapse elimination detection method. Thus it can be wildly applied in three-phase power electronic devices.

Abstract: In ECG signals accurate detection to the position of QRS complex is a key to automatic analysis and diagnosis system. And its premise is that effectively remove all kinds of noise interference in ECG signal. Here, a method of detecting QRS based on EMD and wavelet transform was presented which is aim to improve the anti-noise performance of the detection algorithm. It is combined EMD with the theory of singularity detecting based on wavelet transform modulus maxima method. It has the high detection accuracy and good precision that can give an effective way to the automatic analysis for ECG signal.