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    • 1. 发明申请
    • Monitoring Health of Dynamic System Using Speaker Recognition Techniques
    • 使用扬声器识别技术监测动态系统的健康状况
    • US20140365411A1
    • 2014-12-11
    • US14297595
    • 2014-06-05
    • Homayoon BeigiRaimondo BettiLuciana Balsamo
    • Homayoon BeigiRaimondo BettiLuciana Balsamo
    • G06F17/50G06N99/00
    • G06N99/005G01M13/028G10L17/26
    • Monitoring health of dynamic systems includes using speaker recognition techniques. Some embodiments include determining a system-independent statistical (first) model, and determining a healthy system (second) model based on data representing vibrations of multiple healthy systems and the first model and speaker recognition techniques. Vibration data are obtained from a particular system. It is determined whether the particular system is unhealthy based on the vibration data from the particular system and the first model and the second model and speaker recognition techniques. Some embodiments include obtaining training data that represents vibrations of multiple healthy systems. A damage-sensitive parameter is based on the training data. A threshold value that separates damaged systems from healthy systems is based on the training data and the parameter. It is determined whether a particular system is healthy based on the threshold value and a value for the parameter for vibration data from the particular system.
    • 监测动态系统的健康状况包括使用说话者识别技术。 一些实施例包括确定基于系统的统计(第一)模型,以及基于表示多个健康系统的振动的数据和第一模型和说话者识别技术来确定健康系统(第二)模型。 振动数据从特定系统获得。 基于来自特定系统的振动数据和第一模型以及第二模型和说话人识别技术确定特定系统是否不健康。 一些实施例包括获得表示多个健康系统的振动的训练数据。 伤害敏感参数基于训练数据。 将损坏的系统与健康系统分开的阈值是基于训练数据和参数。 基于阈值确定特定系统是否健康,以及来自特定系统的振动数据的参数值。
    • 2. 发明授权
    • Monitoring health of dynamic system using speaker recognition techniques
    • 使用说话人识别技术监测动态系统的健康状况
    • US09495646B2
    • 2016-11-15
    • US14297595
    • 2014-06-05
    • Homayoon BeigiRaimondo BettiLuciana Balsamo
    • Homayoon BeigiRaimondo BettiLuciana Balsamo
    • G06N99/00G01M13/02G10L17/26
    • G06N99/005G01M13/028G10L17/26
    • Monitoring health of dynamic systems includes using speaker recognition techniques. Some embodiments include determining a system-independent statistical (first) model, and determining a healthy system (second) model based on data representing vibrations of multiple healthy systems and the first model and speaker recognition techniques. Vibration data are obtained from a particular system. It is determined whether the particular system is unhealthy based on the vibration data from the particular system and the first model and the second model and speaker recognition techniques. Some embodiments include obtaining training data that represents vibrations of multiple healthy systems. A damage-sensitive parameter is based on the training data. A threshold value that separates damaged systems from healthy systems is based on the training data and the parameter. It is determined whether a particular system is healthy based on the threshold value and a value for the parameter for vibration data from the particular system.
    • 监测动态系统的健康状况包括使用说话者识别技术。 一些实施例包括确定基于系统的统计(第一)模型,以及基于表示多个健康系统的振动的数据和第一模型和说话者识别技术来确定健康系统(第二)模型。 振动数据从特定系统获得。 基于来自特定系统的振动数据和第一模型以及第二模型和说话人识别技术确定特定系统是否不健康。 一些实施例包括获得表示多个健康系统的振动的训练数据。 伤害敏感参数基于训练数据。 将损坏的系统与健康系统分开的阈值是基于训练数据和参数。 基于阈值确定特定系统是否健康,以及来自特定系统的振动数据的参数值。