Vibration Data Processing Based on Petri Network in Wireless Sensor Networks

There are many auxiliaries with high rotating speed in a power plant, such as pumps, fans, motors and so on. To warrant their safe and reliable operation, their state of vibration has to be monitored. But because of their scattered location, the traditional way of online monitoring with shielded cable connections is costly and work expensive and the precision, reliability and safety of itinerant measurements are unable to meet the requirements of customers. In this paper, a novel method of vibration monitoring for auxiliaries in power plants based on wireless sensor networks has therefore been proposed to realize vibration data acquisition, on-line-detection and data analyzing in this paper, which meets the requirements of auxiliaries with less expenditure and warrants safe operation in the long run. Due to the restrictions of energy and bandwidth on wireless sensor networks, how to utilize the limited resources to acquire available and reliable data from the sensor nodes becomes a hot topic. After modeling and analyzing on mass data by time-sequence technique, a reliable data collection method based on AR(P) model with Petri Net technique are designed in order to improve the whole performance of the system, prolong the lifetime of the network and decrease the energy consumption of the sensor nodes.