Optimization selection of test points on complex equipment for discrete firefly algorithm

He-qi, 王鹤淇 Wang; Wei-guo, 王伟国 Wang; Li-hong, 郭立红 Guo; Ting-xia, 刘廷霞 Liu; Run-qiang, 姜润强 Jiang; Hong-jun, 于洪君 Yu

doi:10.3788/ope.20172505.1357

Cited by 3 publications

(1 citation statement)

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“…The sigmoid function shows a good balance between linearity and non-linearity, which is expressed as [22]:…”

Section: An Adaptive Non-uniform Crossover (Anc) Operatormentioning

confidence: 99%

A reliability evaluation framework for smart meters based on AGG-ARIMA and PFR

Ma¹,

Meng²,

Teng³

et al. 2022

Meas. Sci. Technol.

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The unavoidable outliers and the characteristics of the small sample dataset affect the performance of the Failure Rate (FR) prediction and reliability analysis model of Smart Meters (SMs). To solve these problems, we choose the Basic Error (BE) as the performance index of the equipment and propose a reliability evaluation framework for SMs by combining AGG-ARIMA and PFR for the first time. First, the Autoregressive Integrated Moving Average (ARIMA) model is used to predict the BEs to describe the performance of SMs. Then, an Adaptive Gauss Genetic-algorithm (AGG) is used to optimize the order of ARIMA and a Proportional FR (PFR) model is established to analyze the reliability of batch SMs through the BE predictions. Finally, actual datasets from four companies are used to verify the effectiveness of our evaluation framework. The experimental results show that our framework has better reliability assessment performance for SMs under small sample conditions, and has strong adaptability to the analysis of individual meters.

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“…The sigmoid function shows a good balance between linearity and non-linearity, which is expressed as [22]:…”

Section: An Adaptive Non-uniform Crossover (Anc) Operatormentioning

confidence: 99%

A reliability evaluation framework for smart meters based on AGG-ARIMA and PFR

Ma¹,

Meng²,

Teng³

et al. 2022

Meas. Sci. Technol.

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Test configuration method based on E-dominant NSGA2

Yun

2021

J. Phys.: Conf. Ser.

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In order to solve the problems of the same target importance and too large solution set in the existing solutions, an E-dominant NSGA2 algorithm is proposed to solve the problem. In this paper, the mathematical model of the problem is established with the optimization objectives of test cost, test quantity and false alarm rate. The testability model under unreliable test condition is established by using Bayesian network. Then the E-dominated NSGA2 algorithm is used to solve the problem. After verification, the algorithm has good performance and practical value.

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A review on dependency matrix and its application in fault diagnosis

Cui

et al. 2022

2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)

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Optimization selection of test points on complex equipment for discrete firefly algorithm

Cited by 3 publications

References 0 publications

A reliability evaluation framework for smart meters based on AGG-ARIMA and PFR

A reliability evaluation framework for smart meters based on AGG-ARIMA and PFR

Test configuration method based on E-dominant NSGA2

A review on dependency matrix and its application in fault diagnosis

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