Deviation Detection Using Feature Extraction in Industrial Rotary Machinery Diagnostics

Proceedings of the XXth Conference of Open Innovations Association FRUCT

卷:29

Vladislav Ermakov¹  Dmitry Korzun¹  Kirill Rudkovskiy¹ 

[1] Petrozavodsk State University (PetrSU), Russia;

关键词: faults detection;    industrial internet;    digital profile;    deviation analysis;   

DOI  :  10.5281/zenodo.4770808

来源: DOAJ

【 摘 要 】

The data sensing and communication technologies of Industrial Internet of Things (IIoT) enables monitoring technical state and utilization conditions for industrial rotary machinery. The monitoring system is based on multiple sensors that embed or surround machinery unit under the observation. The sensed data are used for diagnostics of the machinery operation and utilization processes. In this paper, we construct a digital profile for a given machinery. Its digital profile is constructed from the sensed data as information model evolving in time. Hence, detection of deviations in the digital profile provides basic information on possible faults and other incorrectness in industrial rotary machinery. The NASA bearing dataset was used to evaluate the proposed model efficiency.

【 授权许可】

Unknown