Title :
The Self-Diagnose Algorithm for Liquid Level Sensor on WSN Node
Author :
Zhao Jun ; Chen Xiangguang ; Liu Chuntao
Author_Institution :
Beijing Inst. of Technol., Beijing, China
Abstract :
In order to diagnose the state of the liquid level sensor on the tank truck and make sure the wireless sensor networks (WSN) work properly, this paper studies an on-line self fault diagnosing method for liquid level sensors installed on oil tank trucks. First, a flexible fault sensing circuit is designed as a state detection module on sensor node. Second, a self-diagnosing algorithm is proposed, the Mean-Variance model is used to analysis the measuring values and the liquid density is taken as the relationship of sensors. At last, the state detection module compares the statistics characteristic quantities with threshold values to get the condition attributes and detects the failure of the liquid level sensor. Field experiments and simulations at the detection accuracy and the misdiagnosis probability show that this self-diagnosing algorithm is suit to the liquid level sensor on the oil tank trucks.
Keywords :
fuel storage; level meters; wireless sensor networks; WSN node; liquid level sensor; mean-variance model; oil tank trucks; self-diagnose algorithm; self-diagnosing algorithm; tank truck; wireless sensor networks; Accuracy; Algorithm design and analysis; Fault detection; Fault diagnosis; Fuel storage; Pollution measurement; Wireless sensor networks; Liquid density; Liquid level sensor; Mean-Variance model; Self-diagnose algorithm; oil tank truck;
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-1-4577-2120-5
DOI :
10.1109/ISdea.2012.519