PREDICTING THE SERVICE LIFE OF MECHANICAL SYSTEMS CONSIDERING THEIR BLOW-UP MODE OPERATION

This article presents a novel approach to predicting the service life of mechanical systems. Forecasting is based on the assumption that the product's behavior under operating conditions should be considered as the system's behavior operating in a blow-up mode. According to this, the information signal recorded when monitoring the technical condition of a product must contain a periodic component. The method is based on isolating this component and then approximating it with a model. The model of this component is described by a log-periodic function. The model parameters include the operating time of the product before repair and are determined in the periodic component approximation process by this model.

Authors

Publication Details

Journal
MM Science Journal
Published
2024-09-16
DOI
https://doi.org/10.17973/mmsj.2024_10_2024003
Citations
2
Primary Topic
Engineering Diagnostics and Reliability
Type
article
Field-Weighted Citation Impact
0.54
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article

PREDICTING THE SERVICE LIFE OF MECHANICAL SYSTEMS CONSIDERING THEIR BLOW-UP MODE OPERATION

Anton Panda, Volodymyr Nahornyi
2 citations
MM Science Journal
Engineering Diagnostics and Reliability
0.54
article

PREDICTING THE SERVICE LIFE OF MECHANICAL SYSTEMS CONSIDERING THEIR BLOW-UP MODE OPERATION

Anton Panda, Volodymyr Nahornyi
article en
2 citations

Abstract

This article presents a novel approach to predicting the service life of mechanical systems. Forecasting is based on the assumption that the product's behavior under operating conditions should be considered as the system's behavior operating in a blow-up mode. According to this, the information signal recorded when monitoring the technical condition of a product must contain a periodic component. The method is based on isolating this component and then approximating it with a model. The model of this component is described by a log-periodic function. The model parameters include the operating time of the product before repair and are determined in the periodic component approximation process by this model.

MM Science JournalVol. 2024(4)
Openalex Percentile: Top 40%
Engineering Diagnostics and Reliability
0.54
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