Data Compression Algorithms And Energy Efficiency Analysis Of Vibration Signal In Wireless Monitoring

Vibration generally exists when the power machinery is working, to ensure the production safty, condition monitoring must be adopted, and the wireless sensor network that consist of many wireless sensor nodes usually be used in the process. The vibration signal of equipment can be acquired by the sensor nodes, with the aid of wireless network, mass of vibration signals will be transmitted to data processing and signal analysis center. Due to the dynamic characteristics of vibration signals, a large amount of energy will be consumed in the transmission process of vibration data, therefore, to reduce the data volume, some kinds of data compression algorithms usually be adopted. However, On the one hand, data compression can reduce the data volume, on the other hand, it also increases the energy consumption of sensor nodes. Therefore, energy balance between the two sides must be considered for the energy limited sensor nodes.According to the characteristics of vibration signal, this paper studies compression characteristics of the commonly used compression algorithms and a combined compression algorithm is proposed to improve the compression ratio, the energy efficiency evaluation method of the nodes is also studied in this paper and applies this method in evaluating two typical compression algorithms and the proposed combined compression algorithm. The study show that compression algorithm reduces the data volume, but energy consumption of data processing increases at the same time, so a appropriate algorithm must be adopted to balance the relationship of two sides. Due to the vibration data contains lots of noise, lossy compression algorithm can be used to retain the useful signal and filter out noise at the same time, then a better energy efficiency and compression ratio will be acquired.