Monitoring and Analysis of Heavy Machinery using non-intrusive measurement techniques.
The overall goal of the project is to develop and validate a set of methods for non-intrusive monitoring and performance measurement of heavy machinery, such as rig equipment, cranes, heavy-duty vehicles, cut-off and grinding machines. The expected output of the project is a software toolbox with a streamlined user interface for monitoring, analysing and measuring the performance of heavy machinery systems based on a framework of non-intrusive methods (e.g. audio or video sensors). With the help of the outlined software, defined Key Performance Indicators of the machines will be tracked and monitored, thus allowing Operators to be informed on the status of their machines and production processes in general.
Data acquisition will be done through contact-free measurements. New audio and video sensor technologies such as optical sensors, movement detectors, advanced audio detectors or noise detectors will be used for data acquisition. Locating those sensors near the machines and measuring the changes in conditions of the machine in its environment are the basic factors of the planned non-intrusive approach. The algorithms recognize the different operational states of the machines. For example, monitoring the process steps of a heavy machine using an optical sensor can support the tracking of its performance. Based on that information Time to Failure (TTF) - one of the Key Performance Indicators- can be estimated and monitored.