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    科学领域:

    • 光学传感器网络的光学传感器网络
    • 光纤传感技术是光纤传感技术.
    • 网络的可靠性和故障容忍度.

    背景情况:

    • 纤维支格 (FBG) 传感器对于各种应用中的监控至关重要.
    • 传统的FBG网络面临着故障检测和网络弹性方面的挑战.
    • 在FBG传感器系统中需要强大的自我修复能力和准确的故障识别.

    研究的目的:

    • 为FBG传感器网络提出和评估一种新的三层环架构.
    • 增强网络的重新配置能力和自我修复特性.
    • 开发和验证用于软故障检测和可靠性估计的方法.

    主要方法:

    • 实现了三层环架构,增强了重新配置能力.
    • 开发一种自我修复机制,以应对多重光纤链路故障的弹性.
    • 应用多类支持矢量机 (多类SVM) 算法用于软故障检测.
    • 利用人工神经网络 (ANN) 模型进行可靠性估计.

    主要成果:

    • 拟议的网络展示了自我修复能力,成功地从三个光纤链路故障中恢复.
    • 多类SVM算法在检测FBG传感器中的软故障方面实现了99%的准确性.
    • 该ANN可靠性估计模型以合理的计算成本准确预测了网络的可靠性.

    结论:

    • 拟议的三层环架构显著提高了FBG传感器网络的弹性和故障耐受性.
    • 像多类SVM和ANN这样的先进算法为故障检测和可靠性评估提供了有效的解决方案.
    • 这项研究有助于开发更可靠,更强大的光学传感系统.