Delft University of Technology
Faculty Mechanical, Maritime and Materials Engineering Transport Technology
J.A. Beekman Intelligent monitoring of large scale belt conveyor systems Literature survey, Report 2006.TL.7056, Transport Engineering and Logistics.
Because of the ever growing complexity and size of large scale belt conveyor systems, intelligent condition monitoring of these systems is increasingly interesting in order to keep the operational costs as low as possible and reduce system downtime. The existing techniques and possible techniques for the future for the monitoring of belt conveyor systems available in literature have been surveyed. The purpose of this survey is to investigate techniques for intelligent condition monitoring of a large scale belt conveyor system, therefore these questions are important:
Which techniques are mentioned in literature for the condition monitoring of the subsystems of a large scale belt conveyor system and how can these techniques be used for intelligent monitoring?
What is the problem with traditional monitoring?
Why should intelligent condition monitoring be implemented?
The last step is to describe how an intelligent condition monitoring system can be designed.
The steps that have to be taken to implement a condition monitoring system are; establish need, select maintenance strategy, economic justification of condition monitoring, investigate how equipment fails, select condition monitoring technique, install monitoring system, data collection and data analysis. All recent techniques for condition monitoring of large scale belt conveyor monitoring are surveyed as well as possible techniques for the future. For all subsystems of a large scale belt conveyor system several condition monitoring techniques are described.
Finally the implementation of an intelligent condition monitoring system is described. Because the traditional condition monitoring techniques can not be interpreted by a computer often new techniques need to be used or developed. The use of 'smart sensors' can provide the system with local signal conditioning and pre-processing before transmitting the data to a condition monitoring system. The possible intelligent decision making techniques: neural networks, case-based reasoning, expert systems and fuzzy logic are described to provide the system with learning and decision making abilities. Because of the complexity of the system the use of condition monitoring agents for the determination of the condition of a subsystem can be used to keep the amount of data to be processed acceptable.
Reports on Transport Engineering and Logistics (in Dutch)
