Abstract-In order to solve the problem of mechanical vibration monitoring, a mechanical vibration monitoring system based on wireless sensor network was designed. First, the requirements of the hardware of the wireless rotating mechanical vibration monitoring system were analyzed. The monitoring node and base station node were designed. Then, based on the VisualBasic6.0 development tool, a software for monitoring the vibration of rotating machinery was designed. It had the functions of command control, data waveform display, and network topology display. In the mode of wireless mechanical vibration monitoring, the organization mode of the network, the transmission mode of data and the corresponding packet transmission format were improved. Finally, the reliable transmission of the data was verified. Compared with the traditional cable vibration sensor, the performance of the monitoring system was verified. The results showed that the wireless vibration monitoring system designed in this paper met the requirements for the monitoring of the vibration state of the rotating machinery. Keywords-wireless sensor networks, mechanical vibration monitoring, rotating machinery vibration IntroductionWith the development of science and technology, modern industrial equipment has been upgraded, serialized, refined and automated. This has made outstanding contributions to reducing product cost, protecting environmental energy and improving economic efficiency. At the same time, it puts forward higher requirements for the maintainability of rotating machinery. If a large equipment fails, it will have an impact on the whole production line or even the whole factory, and the economic loss is immeasurable. In order to reduce the impact caused by mechanical faults, more and more members of staff began to study the wired monitoring technology for the vibration of rotating machinery. At present, many wire monitoring equipment for rotating machinery vibration has been successfully developed and adopted by modern industries. With years of experiments and improvements, it can basically meet the monitoring needs of the operating conditions of rotating machinery and equipment in a simple environment. Wired connections have the advantage of simultaneous real-time trans- 126

This paper proposes a PCA and ANN based approach to identify significant influential quality factors and modeling customer satisfaction for complex service processes. Firstly, the performance evaluation index system includes initial factors and customer satisfaction degree is proposed, and then the measurement data are collected by questionnaires. Secondly, by using PCA, several preceding principal components (PCs) are extracted, which present about 90% contributions of the whole variations of initial factors. Thirdly, the extracted PCs are converted to new significant factors according to the corresponding coefficients of initial factors in each PC. Finally, BP network is applied to modeling the nonlinear relationship between the significant factors and customer satisfaction degree. The case study of the maintenance service process of an automobile 4S store shows that, the proposed approach can extracted the significant factors from lots of initial factors, and can exactly modeling the complex nonlinear relationship between influential factors and customer satisfaction as well. 1 Keywords -customer satisfaction modeling; complex service process; artificial neural networks; principal component analysis Along with market developing, the auto 4S shops, as a representative of modern service industry are able to birth and development. 4S mode is actually the inevitable product under the fierce competition in the car market. Therefore, it becomes very important to the development of service sector of how to improve the customer satisfaction and trust under the new features. How to make model in the study of customer satisfaction for the characteristics of strong nonlinear, and how to identify the key service quality factors becomes an important topic worthy of further study.The existing research of customer satisfaction modeling is multi-purpose structure equation model (SEM) [1] [2], for example: Peters and Enders [3] use SEM to study the impact of the biggest drivers of customer satisfaction; Sheng Lin, Jinlan Liu, Wenxiu Han [4] analysis PLS path modeling algorithm with multiple latent variables, using the method to discuss the correlation between each latent variable relations in customer satisfaction in a commercial real estate in Tianjin. But relation between the customer satisfaction and each Fund projects: 1. The national social science fund projects: Rapid rescue management system construction of the major emergency disasters in coal mine in China: 10GBL087; 2. The natural science research project of Henan province department of education: The key technology development of coal logistics network modeling and optimization under work well production conditions. Project numbers: 2011A410003 structure variables has strong nonlinear. Due to structural equation has certain inadaptability for processing nonlinear problem, It would affect the precision of the research on customer satisfaction by using the structural equation model. Thus the conclusion can't be convincingly. In order to solve this strong nonlinear pro...

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