A Grid Cumulative Probability Localization-Based Industrial Risk Monitoring System

摘要

With the rapid development of modern industries, more and more risk factors exist in industrial operations, leading to a gradual increase in the frequency of industrial failures. The industrial enterprises have taken a variety of measures to analyze the risk factors in industrial operations, but establishing an effective monitoring and evaluation system remains a technical challenge. To overcome this challenge, a practical industrial risk monitoring system, based on the wireless sensor network (WSN), is established in this paper to improve resilience of the respective industrial operations. In the proposed system, the existing sensor nodes in the industrial environment are organized into WSN to transmit real-time data. A special inspection robot is used to monitor comprehensively the environmental and safety risk factors in the industrial environment. To obtain the location of the robot, the partial nodes of the WSN are organized dynamically as the anchor nodes of the localization system, and two grid cumulative probability localization (GCPL) algorithms are proposed based on the GCPL-circle intersection and GCPL-path loss methods, respectively. The GCPL algorithm determines the grid cumulative probability using prior location information of the target node and the received signal strength information between the anchor nodes and target node to locate the target node. Experimental results show that the two GCPL algorithms significantly improve the localization accuracy and stability, and hence can be implemented as a risk monitoring system for realworld applications.