Development and evaluation of a brine mining equipment monitoring and control system using Wireless Sensor Network and fuzzy logic

Abstract

The brine mining equipment failure can seriously affect the productivity of the salt lake chemical industry. Traditional monitoring and controlling method mainly depends on manned patrol that is offline and ineffective. With the rapid advancement of information and communication technologies, it is possible to develop more efficient online systems that can automatically monitor and control the mining equipment and to prevent equipment damage from mechanical failure and unexpected interruptions with severe consequences. This paper describes a Wireless Monitoring and feedback fuzzy logic-based Control System (WMCS) for monitoring and controlling the brine well mining equipment. Based on the field investigations and requirement analysis, the WMCS is designed as a Wireless Sensors Network module, a feedback fuzzy logic controller, and a remote communication module together with database platform. The system was deployed in existing brine wells at demonstration area without any physical modification. The system test and evaluation results show that WMCS enables to track equipment performance and collect real-time data from the spot, provides decision support to help workers overhaul the equipment and follows the deployment of fuzzy control in conjunction with remote data logging. It proved that WMCS acts as a tool to improve management efficiency for mining equipment and underground brine resources.

A novel mobile agent-based distributed evidential expectation maximization algorithm for uncertain sensor networks

“…Referring to the broad applicability of the sensor networks, data mining in sensor networks has become an interesting field of research in recent years. Sensor networks specifically have been utilized in different fields such as mission application (Oracevic et al, 2014), traffic control (Du et al, 2015; Nellore and Hancke, 2016), industrial networks (Gomes et al, 2019; Zuhra et al, 2017), environmental monitoring (He et al, 2018; Srbinovska et al, 2015) and automatic transportation systems (Dimitrakopoulos et al, 2013). For example, a sensor network can be utilized as a part of hazardous and difficult to reach positions for individuals, such as special industrial and clinical fields for monitoring or tracking purposes (Akyildiz et al, 2002).…”