A behavior prediction method for complex system based on belief rule base with structural adaptive

Zhang, QingXi; Zhao, BoYing; He, Wei; Zhu, HaiLong; Zhou, GuoHui

doi:10.1016/j.asoc.2023.111118

Cited by 15 publications

(7 citation statements)

References 37 publications

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“…In this paper, the model is optimized using the P-CMA-ES algorithm. The core objective of the optimization process is to improve the accuracy of the IBRB-r model by exploring the most appropriate configuration of the model parameters and thus improving the accuracy of the IBRB-r model [3].…”

Section: The Interpretable Optimization Methods For the Irbr-rmentioning

confidence: 99%

“…However, it can be challenging for the BRB model initially built by experts to fully match the requirements of real spaceship flywheel systems because of the limitations of expert knowledge. For this reason, actual observation data must be introduced for model calibration and optimization to ensure that the model is closer to the real system operation status and health assessment needs [3]. However, the algorithms used in the optimization process often contain a certain stochastic component, which has the potential to weaken the interpretability of health assessment methods to some extent [20].…”

Section: Interpretability Of the Ibrb-r Modelmentioning

confidence: 99%

“…The research cost of the actual flywheel system is high and the failure rate of the bearing component, which is the key component of the flywheel system, is high. Therefore, based on existing research, the flywheel bearing component is selected as an example to verify the effectiveness of the IBRB-r model [3,51]. The two input attributes are ST rise and speed reduction (SL).…”

Section: Background Descriptionmentioning

confidence: 99%

“…Therefore, it is particularly important to establish a reliable and credible flywheel health status assessment method. The spacecraft flywheel system is a key component of satellite attitude control [3]. Numerous elements, including aging, temperature changes, and space radiation, can have an impact on the health of flywheel systems.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is especially necessary and important to construct a hybrid model that combines the advantages of both knowledge and data. Zhang et al proposed a structurally adaptive belief rule base (BRB) method for the behavioral prediction of complex systems, which achieves accurate prediction of the behavior of complex systems [3]. Lou and Xie proposed a multiview universum support vector machine with insensitive pinball loss (Pin-MvUSVM) to achieve accurate classification of multiview datasets [24].…”

Section: Introductionmentioning

confidence: 99%

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An interpretable spacecraft flywheel system health status assessment method under perturbation

Zhang,

He,

et al. 2024

Meas. Sci. Technol.

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Health status assessment is an important measure for maintaining the safety of spacecraft flywheel systems. The influence of noise, sensor quality, and other disturbance factors can lead to a decrease in the reliability of the collected information. This can affect the model accuracy. Moreover, a loss of belief in the model is frequently caused by the opaque nature of the procedure and the incomprehensibility of the outcomes, particularly in fields such as aerospace. It is urgent to maintain the interpretability of the model and successfully identify the unreliability of the observed data. Therefore, this paper proposes a spacecraft flywheel system health status assessment method under perturbation based on interpretable belief rule base with attribute reliability (IBRB-r). First, the attribute reliability is calculated based on the average distance method, and a new fusion method of attribute reliability is proposed to reduce the interference of unreliable information. Then, a new interpretable constraint strategy is proposed to improve the rationality and interpretability of the parameters. Finally, the proposed method is validated by a case study of the health status assessment of a spacecraft flywheel system. Experiments show that the IBRB-r maintains high accuracy and interpretability under unreliable observation data.

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Section: The Interpretable Optimization Methods For the Irbr-rmentioning

confidence: 99%

Section: Interpretability Of the Ibrb-r Modelmentioning

confidence: 99%

Section: Background Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An interpretable spacecraft flywheel system health status assessment method under perturbation

Zhang,

He,

et al. 2024

Meas. Sci. Technol.

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A New Interpretable State‐of‐Health Assessment Model for Lithium‐Ion Batteries With Multidimensional Adaptability Optimization

Zhang,

Qu,

Liu

et al. 2024

Energy Science & Engineering

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The state‐of‐health (SOH) assessment of lithium‐ion batteries is critical to the development and optimization of maintenance strategies. To ensure the accuracy of the assessment results, it must not only address a variety of uncertainties but also rationalize and transparently conduct the assessment process, as well as make the results interpretable and traceable. These requirements are necessary to ensure that the battery operates safely and steadily. As an interpretable modeling method, belief rule base (BRB) has been widely used in lithium‐ion battery SOH assessment. However, current BRB‐based models face two problems: (1) The initial reference values provided by experts often have limited accuracy due to complex internal chemistry. (2) The multidimensionality of the parameters in the interpretable optimization process and the differences in their properties should be fully considered. Therefore, this paper proposes a new SOH assessment model for lithium‐ion batteries based on an interpretable BRB with multidimensional adaptability optimization (IBRB‐mao). First, an interpretable knowledge and data dual‐driven reference value generation method is proposed to address the issue of imprecise reference values. Expert knowledge is maintained when generating reference values using this method. Second, two interpretable multidimensional constraint strategies are proposed to ensure interpretability in the optimization process. Finally, the NASA lithium‐ion battery data set is taken as a case study to validate the effectiveness of the proposed method.

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A new automated interval structure belief rule base-based fault diagnosis method for complex systems

Wan,

Zhang,

et al. 2024

Nonlinear Dyn

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A behavior prediction method for complex system based on belief rule base with structural adaptive

Cited by 15 publications

References 37 publications

An interpretable spacecraft flywheel system health status assessment method under perturbation

An interpretable spacecraft flywheel system health status assessment method under perturbation

A New Interpretable State‐of‐Health Assessment Model for Lithium‐Ion Batteries With Multidimensional Adaptability Optimization

A new automated interval structure belief rule base-based fault diagnosis method for complex systems

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