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  4. VIBROCHANGE - A development system for condition monitoring based on advanced techniques of signal processing
 
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VIBROCHANGE - A development system for condition monitoring based on advanced techniques of signal processing

Journal
Int J of Advanced Manufacturing Technology
ISSN
0268-3768
Date Issued
2019
Author(s)
Aiordachioaie, Dorel
Popescu, Theodor Dan
DOI
10.1007/s00170-019-04255-3
Abstract
Condition monitoring, change detection, and diagnosis are important activities and research directions in the field of system engineering and maintenance of the equipment and industrial processes. Starting from a relative difficulty to implement new advanced algorithms in industry, the paper puts forward a development system for building and testing new methods and algorithms in the field of change detection and diagnosis. The proposed system has specialized sub-systems/modules: VIBROGEN to generate vibration signals, as effects of the faults, under controlled conditions, i.e., time, size, and working loads; VIBROSIG for signal pre-processing and acquisition tasks. The VIBROCHANGE is the main sub-system and it works on two levels. The upper one is VIBROTOOL, which runs on high-level programming languages with complex libraries and algorithms, suitable more for algorithm development. The lower one is VIBROMOD, and it works in real conditions of the monitored process, with restricted hardware and software, such as type and library. It implements and runs the converted algorithms from the high-level language, and accepted by to the industrial electronic equipment. The system provides robust results on both levels. The development stage of the algorithms is considered finished only when the results on both levels are close enough one to the other. As example of usage, some results of change detection algorithms, running on the highest-level, are presented and discussed. The processed signals are coming from vibrations generated by bearings with various type and size of faults. The obtained results recommend that the system should be used in the development and testing activities of models, methods, and algorithms for condition monitoring.

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