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    • 1. 发明申请
    • DIGITIZATION OF WORK PROCESSES USING WEARABLE WIRELESS DEVICES CAPABLE OF VOCAL COMMAND RECOGNITION IN NOISY ENVIRONMENTS
    • 使用可靠的无线设备进行工作流程的数字化,可以在噪声环境中进行声卡命令识别
    • US20050080620A1
    • 2005-04-14
    • US10605582
    • 2003-10-09
    • Kotesh RaoMichael HouseRobert RoneyAndrew Travaly
    • Kotesh RaoMichael HouseRobert RoneyAndrew Travaly
    • G10L21/00G10L21/02
    • G10L21/0208
    • In an information processing system having an equipment controller for enabling the digitization of complex work processes conducted during testing and/or operation of machinery and equipment, a local wireless communications network is implemented using at least one fixed point wireless communications access station and one or more voice-responsive wireless mobile computing/communications devices that are capable of accurate vocal command recognition in noisy industrial environments. The computing/communications device determines spectral characteristics of ambient non-speech background noises and provides active noise cancellation through the use of a directional microphone and an adaptive noise tracking and subtraction process. The device is carried by a user and is responsive to one or more vocal utterances of the user for communicating data to the information processing system and/or generating operational control commands to provide to the equipment controller for controlling the machinery or equipment.
    • 在具有用于使机器和设备的测试和/或操作期间进行的复杂工作处理的数字化的设备控制器的信息处理系统中,使用至少一个固定点无线通信接入站和一个或多个 语音响应无线移动计算/通信设备,能够在嘈杂的工业环境中进行精确的声带命令识别。 计算/通信设备确定环境非语音背景噪声的频谱特性,并通过使用定向麦克风和自适应噪声跟踪和减法处理来提供主动噪声消除。 该设备由用户携带并且响应于用户的一个或多个声音来传送数据到信息处理系统和/或产生操作控制命令以提供给设备控制器来控制机器或设备。
    • 2. 发明申请
    • METHOD AND SYSTEM FOR PREDICTING REMAINING LIFE FOR MOTORS FEATURING ON-LINE INSULATION CONDITION MONITOR
    • 用于预测在线绝缘条件监测器的电机的剩余寿命的方法和系统
    • US20060259271A1
    • 2006-11-16
    • US10908455
    • 2005-05-12
    • Michael HouseGreg FlickingerGary Chmiel
    • Michael HouseGreg FlickingerGary Chmiel
    • G06F19/00
    • G05B23/0248G01R31/343G05B23/0283
    • A method for determining reliability and a remaining time before failure with statistical confidence for a motor system includes acquiring historical motor data in a computer system, obtaining operational parameter data, uploading the operational parameter data to the computer system, performing failure analysis, developing a causal network, and performing an integrated causal network and reliability analysis of the motor system. The historical motor data corresponds to the motor system. The operational parameter data is obtained from sensors at the motor system. The sensors include a tan delta sensor. The failure analysis is performed based on a composite of reliability probability distributions corresponding to predetermined sub-populations of historical motor system failure causes. The causal network is developed for modeling reliability of one or more motor system components and assessing motor system component condition based on the causal network. Results from the performing failure analysis are integrated with results from the assessing motor system component condition based on the causal network to compute a quantitative value for a time remaining before failure with an ascertained statistical confidence.
    • 一种用于确定电动机系统的可靠性和剩余时间的统计置信度的方法包括获取计算机系统中的历史电动机数据,获得操作参数数据,将操作参数数据上传到计算机系统,执行故障分析,开发因果 网络,并对电机系统进行综合因果网络和可靠性分析。 历史电机数据对应于电机系统。 运行参数数据由电机系统的传感器获得。 传感器包括一个tanδ传感器。 基于对应于历史运动系统故障原因的预定子群体的可靠性概率分布的复合来执行故障分析。 因果网络是针对一个或多个电机系统组件的可靠性进行建模,并根据因果网络评估电机系统组件状况。 执行故障分析的结果与基于因果网络的评估电机系统组件条件的结果相结合,以在确定的统计置信度之前计算故障之前剩余时间的定量值。