Performance evaluation of aerospace relay based on evidential reasoning rule with distributed referential points

Wang, Jie; Zhou, Zhijie; Hu, Changhua; Tang, Shuaiwen; Ning, Pengyun

doi:10.1016/j.measurement.2021.109667

Cited by 12 publications

(4 citation statements)

References 25 publications

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“…The level reference values of indicators play a critical role in determining the aggregate outcome of ER rules [21]. However, the level reference values of indicators are often given by experts, which leads to unreasonable assessment results.…”

Section: Optimization Of the Er-drv Model Parametersmentioning

confidence: 99%

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A Health Assessment Method for Lithium-Ion Batteries Based on Evidence Reasoning Rules with Dynamic Reference Values

Yang,

Zhao,

Zhang

2024

Batteries

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The health assessment of lithium-ion batteries holds great research significance in various areas such as battery management systems, battery usage and maintenance, and battery economic evaluation. However, because environmental perturbations are not taken into account during the assessment, the accuracy and reliability of the assessment are limited. Thus, a health assessment model for lithium-ion batteries based on evidence reasoning rules with dynamic reference value (ER-DRV) is proposed in this paper. Firstly, considering that the data are subject to changes, dynamic reference values, real-time weights, and real-time reliability were utilized in the model to ensure the effectiveness and accuracy of the assessment. Moreover, an enhanced optimization method based on the whale optimization algorithm (WOA) was developed to improve the accuracy of the assessment model. In addition, the robustness of the ER-DRV model was studied with perturbation analysis methods. Finally, the proposed method was validated on two open lithium-ion battery datasets. The experimental results show that the health assessment method proposed in this article not only has higher accuracy and transparent reasoning process but also has strong robustness and good generalization ability.

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Section: Optimization Of the Er-drv Model Parametersmentioning

confidence: 99%

“…Zhao et al developed an online security evaluation model that incorporates the ER method [20]. Wang et al introduced an enhanced ER rule-based performance assessment model for an aerospace relay, which incorporates distributed referential points [21]. The above literature supports the efficacy of ER rules in health assessment.…”

Section: Introductionmentioning

confidence: 99%

A Health Assessment Method for Lithium-Ion Batteries Based on Evidence Reasoning Rules with Dynamic Reference Values

Yang,

Zhao,

Zhang

2024

Batteries

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“…An ER rule model based on a continuous probability distribution reference points is proposed to address the problem. Since the Gaussian distribution has been widely used in various fields, the dependence on expert knowledge in the qualitative approach can be made up, the distribution form of the reference points is specified as a Gaussian distribution [31]. In addition, the initial Gaussian distribution parameters are given based on expert knowledge, which may not be optimal.…”

Section: Introductionmentioning

confidence: 99%

A New Method for Oil-Immersed Transformers Fault Diagnosis Based on Evidential Reasoning Rule With Optimized Probabilistic Distributed

E.,

Zhang,

et al. 2024

IEEE Access

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Power transformers are important equipment in power systems. Most medium and large transformers are oil-immersed transformers, with the exception of some small-and medium-capacity transformers and gas transformers with special purpose. It is extremely critical to detect malfunction timely and accurately, because the reliability and safety of oil-immersed transformers can cause significant implications for power systems. Therefore, the fault diagnosis model based on the evidential reasoning (ER) rule with reference points in the Gaussian distribution form optimized by a constrained genetic optimization algorithm (GA), named GER-G model, is proposed in this paper. The GER-G fault diagnosis model can monitor and identify the degree of transformer faults in real time. First, the concentration of dissolved gases in the oil of oil-immersed transformers varies at different fault degrees, so the gases with high weight are selected using the maximum correlation-minimum redundancy (mRMR) to constitute the indicator system. Second, to solve the uncertainty existing in the fault information of transformers, the reference points of the ER rule are continuous probability distribution reference points described by Gaussian distribution form. Third, the constrained GA is proposed to adapt the Gaussian distribution. And the accuracy of fault diagnosis results can be enhanced by optimizing the grade parameters using constrained GA. Finally, the internal and external influences in the environment are quantified using perturbation analysis, the GER-G fault diagnosis model is applied to the dataset of dissolved gases in the oil, and the robustness and validity of the GER-G fault diagnosis model are validated. Meanwhile, the validation results also show that the GER-G fault diagnosis model possesses higher accuracy compared with other fault diagnosis methods.

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“…Based on this, this paper puts forward an evaluation model of the welding robot's health status based on the ER rule, and its results are interpretable, which also solves the difficulties of poor evaluation results caused by relying solely on qualitative knowledge and quantitative data. Additionally, the ER rule assessment model has been widely used in laser gyro [17], aerospace systems [18], and aerospace relay [19].…”

Section: Introductionmentioning

confidence: 99%

Health Status Evaluation of Welding Robots Based on the Evidential Reasoning Rule

et al. 2023

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It is extremely important to monitor the health status of welding robots for the safe and stable operation of a body-in-white (BIW) welding production line. In the actual production process, the robot degradation rate is slow and the effective data are poor, which can reflect a degradation state in the large amount of obtained monitoring data, which causes difficulties in health status evaluation. In order to realize the accurate evaluation of the health status of welding robots, this paper proposes a health status evaluation method based on the evidential reasoning (ER) rule, which reflects the health status of welding robots by using the running state data monitored in actual engineering and through the qualitative knowledge of experts, which makes up for the lack of effective data. In the ER rule evaluation model, the covariance matrix adaptive evolutionary strategy (CMA-ES) algorithm is used to optimize the initial parameters of the evaluation model, which improved the accuracy of health status evaluations. Finally, a BIW welding robot was taken as an example for verification. The results show that the proposed model is able to accurately estimate the health status of the welding robot by using the monitored degradation data.

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Performance evaluation of aerospace relay based on evidential reasoning rule with distributed referential points

Cited by 12 publications

References 25 publications

A Health Assessment Method for Lithium-Ion Batteries Based on Evidence Reasoning Rules with Dynamic Reference Values

A Health Assessment Method for Lithium-Ion Batteries Based on Evidence Reasoning Rules with Dynamic Reference Values

A New Method for Oil-Immersed Transformers Fault Diagnosis Based on Evidential Reasoning Rule With Optimized Probabilistic Distributed

Health Status Evaluation of Welding Robots Based on the Evidential Reasoning Rule

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