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    • 2. 发明授权
    • Diagnostic system with learning capabilities
    • 具有学习能力的诊断系统
    • US06442542B1
    • 2002-08-27
    • US09415408
    • 1999-10-08
    • Vipin Kewal RamaniRasiklal Punjalal ShahRamesh RamachandranPiero Patrone BonissoneYu-To ChenPhillip Edward SteenJohn Andrew Johnson
    • Vipin Kewal RamaniRasiklal Punjalal ShahRamesh RamachandranPiero Patrone BonissoneYu-To ChenPhillip Edward SteenJohn Andrew Johnson
    • G06F1730
    • G01R31/2846G06F11/2257Y10S707/915Y10S707/99933Y10S707/99945
    • A diagnostic system is provided for identifying faults in a machine (e.g., CT scanner, MRI system, x-ray apparatus) by analyzing a data file generated thereby. The diagnostic system includes a trained database containing a plurality of trained data, each trained data associated with one of plurality of known fault types. Each trained data is represented by a trained set of feature values and corresponding weight values. Once a data file is generated by the machine, a current set of feature values are extracted from the data file by performing various analyses (e.g., time domain analysis, frequency domain analysis, wavelet analysis). The current set of feature values extracted is analyzed by a fault detector which produces a candidate set of faults based on the trained set of feature values and corresponding weight values for each of the fault types. The candidate set of faults produced by the fault detector is presented to a user along with a recommend repair procedure. In cases where no fault is identified or in response to a misdiagnosis produced by the diagnostic system, the user may interactively input a faulty condition associated with the machine being diagnosed (e.g., based on his/her experience). The diagnostic system further includes a learning subsystem which automatically updates the plurality of trained data based on the faulty condition input by the user.
    • 提供诊断系统,用于通过分析由此产生的数据文件来识别机器中的故障(例如,CT扫描仪,MRI系统,x射线设备)。 诊断系统包括训练数据库,其包含多个训练数据,每个训练数据与多个已知故障类型之一相关联。 每个经过训练的数据由经过训练的特征值组和对应的权重值表示。 一旦数据文件由机器生成,通过执行各种分析(例如,时域分析,频域分析,小波分析)从数据文件中提取当前的一组特征值。 提取的当前特征值组由故障检测器分析,故障检测器基于经过训练的特征值集合和每个故障类型的对应权重值产生候选的故障集合。 由故障检测器产生的候选故障集与推荐的修复过程一起呈现给用户。 在没有发现故障或者响应诊断系统产生的误诊的情况下,用户可以交互地输入与被诊断的机器相关联的故障状况(例如,基于他/她的经验)。 诊断系统还包括学习子系统,该学习子系统基于用户输入的故障条件自动更新多个经过训练的数据。