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Open Access

Edge Device Fault Probability Based Intelligent Calculations for Fault Probability of Smart Systems

School of Environmental and Chemical Engineering, Shenyang Ligong University, Shenyang 110159, China
Chulalongkorn Business School, Faculty of Commerce and Accountancy, Chulalongkorn University, Bangkok 10900, Thailand
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Abstract

In a smart system, the faults of edge devices directly impact the system’s overall fault. Further, complexity arises when different edge devices provide varying fault data. To study the Smart System Fault Evolution Process (SSFEP) under different fault data conditions, an intelligent method for determining the Smart System Fault Probability (SSFP) is proposed. The data types provided by edge devices include the following: (1) only known edge device fault probability; (2) known Edge Device Fault Probability Distribution (EDFPD); (3) known edge device fault number and EDFPD; (4) known factor state of the edge device fault and EDFPD. Moreover, decision methods are proposed for each data case. Transfer Probability (TP) is divided into Continuity Transfer Probability (CTP) and Filterability Transfer Probability (FTP). CTP asserts that a Cause Event (CE) must lead to a Result Event (RE), while FTP requires CF probability to exceed a threshold before RF occurs. These probabilities are used to calculate SSFP. This paper introduces a decision method using the information diffusion principle for low-data SSFP determination, along with an improved method. The method is based on space fault network theory, abstracting SSFEP into a System Fault Evolution Process (SFEP) for research purposes.

Keywords

smart systemsintelligent scienceedge devicefault probabilitydecision method

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Tsinghua Science and Technology
Volume 29 Issue 4,
August 2024
Pages 1023-1036
DOI: 10.26599/TST.2023.9010085
Cite this article:
Li S, Cui T, Viriyasitavat W. Edge Device Fault Probability Based Intelligent Calculations for Fault Probability of Smart Systems. Tsinghua Science and Technology, 2024, 29(4): 1023-1036. https://doi.org/10.26599/TST.2023.9010085

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Received: 21 June 2023
Revised: 29 July 2023
Accepted: 12 August 2023
Published: 09 February 2024
© The Author(s) 2024.

The articles published in this open access journal are distributed under the terms of theCreative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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