Applied Mechanics and Materials Vols. 602-605

Abstract: The paper introduces the key points of vibration diagnosis technology on-site operation, from the diagnosis, diagnostic object, working condition of equipment, equipment principle and correct data analysis etc., and giving analysis, to prevent the generation of error analysis, to prevent the acquisition signal distortion, improving the diagnosis efficiency and reliability.

Abstract: In pipeline leak detection, collected fault signal will inevitably influenced by all kinds of industrial noise, sometimes even the useful signals submerged by the noise, so it causes a huge problem for leak location. Regarding this problem, the Empirical Mode Decomposition was used to analyze the signal instead of the traditional method of Time-Frequency analysis method. Compared with the traditional method, this method can not only get tid of noise, but also analyze the fault signal more accurately, which would help to improve the accuracy of the pipeline leak detection further.

Abstract: A wireless control system for pointolite on the light pen based on TMS320DM642 and CC2530 is introduced in this paper, in order to solve the problem that only pointolite's switch values could be controlled on the light pen in light-pen CMMs, but not lightening time values and brightness values. Through wireless networks of Zigbee, not only pointolite could be switched on or off separately, but also lightening time values and brightness values could be changed by TMS320DM642. Protocols of wired and wireless communication, multipoint answer and error reporting are also given, to improve anti-jamming capability of the system. The experimental result demonstrates that the control success rate could reach 96%, as the wireless modules of TMS320DM642 and the light pen within 8m. So the developed system has high anti-interference capability and could meet expected requirements.

Abstract: This study focuses on physical activity recognition of elder people using a single triaxial accelerometer attached on waist. With accelerations data acquired continuously by a wearable wireless device, a motion pattern recognition method based on acceleration time series analysis of human activity states is proposed. We use Hidden Markov Model (HMM) to identify physical activity series. Experimental result shows that the activity recognition rate is 95.7% using this method, which can play an important role in the adjuvant therapy.

Abstract: According instantaneous frequency measurement theory, we propose a new PCM/FM telemetry signal demodulation method. This paper introduces the basic principles of this demodulation method and implementation process, the influence of instantaneous frequency measurement accuracy and the impact of factors on the Doppler frequency demodulation performance is proposed to improve the accuracy and instantaneous frequency measurement method demodulation performance. Simulation results show that this method is superior demodulation performance, strong anti-jamming capability, ease of software programming and DSP devices to achieve.

Abstract: Recently, the field of Prognostics and Health Management (PHM) for electronic products and systems has received increasing attention due to the potentialities to provide early warning of system failures, reduce life cycle costs, and forecast maintenance as needed. This paper introduces the sensors and their sensor technologies. The required attributes of sensors for the development for PHM of electronics are discussed. Finally, their trends in sensor systems are presented.

Abstract: K-means algorithm is common in text clustering algorithm. The traditional K-means algorithm has sensitivity to the initial centers. The result of clustering depends on the initial centers excessively. For different input, the output fluctuated considerably. The K-means algorithm combined features dictionary with density based on outlier detection to detect the outliers in text data. In the first stage, the density parameter is given to all of the data objects using the custom distance function. In the second stage, K-means is used to cluster base on the distribution of density. K data objects are chosen to be the initial clustering centers as they belong to high density area and have the farthest distance for each other. In the third stage, the exception text sets can be identified from the clustering by the outlier detection algorithm. Experimental results show that the proposed approach can efficiently detect outliers in data set.

Abstract: In this paper, we present a new visual saliency model, which based on Wavelet Transform and simple Priors. Firstly, we create multi-scale feature maps to represent different features from edge to texture in wavelet transform. Then we modulate local saliency at a location and its global saliency, combine the local saliency and global saliency to generate a new saliency .Finally, the final saliency is generated by combining the new saliency and two simple priors (color prior an location prior). Experimental evaluation shows the proposed model can achieve state-of-the-art results and better than the other models on a public available benchmark dataset.

Abstract: Representation model of composition event is a very important issue in the study of composition event. Aiming to solve the problem of no well reflecting the spatial-temporal characteristic of CPS (Cyber-Physical Systems) in current composition even models, a representation model of composition event based on multi-tuple is proposed for CPS in this paper. The contribution of the paper lies that we use five tuples: object, time, space, event and property, to represent a composition event of CPS, which not only can more comprehensively reflect the spatial-temporal characteristic of CPS event, but also can reflect the some dynamic change features of external environment. The simulation results show that our proposed scheme has several advantages in reducing event average error rate compared with some general event model methods.

Abstract: Based To solve the problem of incomplete monitoring information,single function and low extensibility of public bus monitoring system,a remote digital monitoring system of public bus based on embedded platform is designed. Bus stop announcer,CAN controller,satisfaction evaluator and other vehicle electronic equipment are integrated into vehicle terminal,which collect,transmit and feedback real time data such as the location of bus,bus station information,running state parameters,satisfaction and vehicle scheduling information. The remote monitoring center receives the data and generates the visualizations webpage at the same time. Bus remote monitoring system is established,and the operation efficiency and security of public bus is improved.After large amounts of running and tests,result of the test indicates the monitoring data received from this system is reliable and stabilized.