公开(公告)号：US07096159B2

公开(公告)日：2006-08-22

申请号：US10932578

申请日：2004-09-02

申请人： Zehra Cataltepe ,  Ming Fang ,  Claus Neubauer ,  Chao Yuan

发明人： Zehra Cataltepe ,  Ming Fang ,  Claus Neubauer ,  Chao Yuan

IPC分类号： G06F15/00 ,  G06F19/00

CPC分类号： G05B23/0221 ,  G05B17/02

摘要： A system for detecting one or more faulty sensors in a multi-sensor monitor includes a partitioning module for partitioning sensor values generated by the multi-sensor monitor into two distinct sets, a training set and a validation set. The system also includes a training module for training a model using the sensor values belonging to the training set and applying the model to each sensor value belonging to the validation set so as to determine a range of acceptable sensor values. The system further includes an estimating module for obtaining an estimated sensor value for each sensor using the model, and a fault-determining module for testing at least one sensor combination if a sensor value is not within its range of acceptable sensor values. A sensor combination includes at least one sensor whose estimated sensor value is not within the range of acceptable values.

摘要翻译： 用于检测多传感器监视器中的一个或多个故障传感器的系统包括分区模块，用于将由多传感器监视器生成的传感器值分成两个不同的集合，训练集和验证集合。 该系统还包括训练模块，用于使用属于训练集的传感器值训练模型，并将该模型应用于属于验证集的每个传感器值，以便确定可接受的传感器值的范围。 该系统还包括估计模块，用于使用该模型获得每个传感器的估计传感器值;以及故障确定模块，用于如果传感器值不在可接受传感器值的范围内，则测试至少一个传感器组合。 传感器组合包括至少一个其估计传感器值不在可接受值的范围内的传感器。

公开(公告)号：US20060074595A1

公开(公告)日：2006-04-06

申请号：US11202861

申请日：2005-08-12

申请人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

发明人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

IPC分类号： G06F11/30

CPC分类号： G05B23/0254 ,  G05B23/0297

摘要： A method and apparatus for detecting faults in power plant equipment is discloses using sensor confidence and an improved method of identifying the normal operating range of the power generation equipment as measured by those sensors. A confidence is assigned to a sensor in proportion to the residue associated with that sensor. If the sensor has high residue, a small confidence is assigned to the sensor. If a sensor has a low residue, a high confidence is assigned to that sensor, and appropriate weighting of that sensor with other sensors is provided. A feature space trajectory (FST) method is used to model the normal operating range curve distribution of power generation equipment characteristics. Such an FST method is illustratively used in conjunction with a minimum spanning tree (MST) method to identify a plurality of nodes and to then connect those with line segments that approximate a curve.

摘要翻译： 一种用于检测发电厂设备故障的方法和装置公开了使用传感器置信度和一种通过这些传感器测量的识别发电设备的正常工作范围的改进方法。 与传感器相关的残差成比例地分配给传感器的置信度。 如果传感器具有高残留量，那么传感器的信心就很小。 如果传感器具有较低的残留量，则会将高置信度分配给该传感器，并提供该传感器与其他传感器的适当加权。 使用特征空间轨迹（FST）方法对发电设备特性的正常工作范围曲线分布进行建模。 这种FST方法被说明性地与最小生成树（MST）方法一起使用以识别多个节点，然后将它们与近似于曲线的线段连接。

公开(公告)号：US20060048007A1

公开(公告)日：2006-03-02

申请号：US11197270

申请日：2005-08-04

申请人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

发明人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

IPC分类号： G06F11/00

CPC分类号： G05B23/024

摘要： A method and apparatus for detecting out-of-range conditions representing normal operations is disclosed. A support vector machine is used to generate an improved representation of historical training data from power generation equipment that facilitates a more accurate determination of the boundary between measurements that should be considered faults and those that represent normal operating conditions. The SVM receives data collected from a plurality of independent sensors associated with the power generating equipment in order to generate a boundary substantially separating a first class of data (e.g., a fault) from a second class of data (e.g., a normal operating condition) in a support vector machine feature space. Elements of operational data are collected and compared to the boundary generated from historical training data. A determination is then made whether the element of operational data is in a particular class, such as a class associated with out-of-range conditions.

摘要翻译： 公开了一种用于检测表示正常操作的超范围条件的方法和装置。 支持向量机用于生成来自发电设备的历史训练数据的改进表示，其有助于更准确地确定应被认为是故障的测量值与表示正常操作条件的测量之间的边界。 SVM接收从与发电设备相关联的多个独立传感器收集的数据，以便产生基本上将第一类数据（例如，故障）与第二类数据（例如，正常操作条件）分离的边界， 在支持向量机的特征空间。 收集操作数据的元素，并与历史训练数据生成的边界进行比较。 然后确定操作数据的元素是否在特定类中，例如与超范围条件相关联的类。

公开(公告)号：US07953577B2

公开(公告)日：2011-05-31

申请号：US11202861

申请日：2005-08-12

申请人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

发明人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

IPC分类号： G06F11/30 ,  G21C17/00

CPC分类号： G05B23/0254 ,  G05B23/0297

摘要： A method and apparatus for detecting faults in power plant equipment is discloses using sensor confidence and an improved method of identifying the normal operating range of the power generation equipment as measured by those sensors. A confidence is assigned to a sensor in proportion to the residue associated with that sensor. If the sensor has high residue, a small confidence is assigned to the sensor. If a sensor has a low residue, a high confidence is assigned to that sensor, and appropriate weighting of that sensor with other sensors is provided. A feature space trajectory (FST) method is used to model the normal operating range curve distribution of power generation equipment characteristics. Such an FST method is illustratively used in conjunction with a minimum spanning tree (MST) method to identify a plurality of nodes and to then connect those with line segments that approximate a curve.

摘要翻译： 一种用于检测发电厂设备故障的方法和装置公开了使用传感器置信度和一种通过这些传感器测量的识别发电设备的正常工作范围的改进方法。 与传感器相关的残差成比例地分配给传感器的置信度。 如果传感器具有高残留量，那么传感器的信心就很小。 如果传感器具有较低的残留量，则会将高置信度分配给该传感器，并提供该传感器与其他传感器的适当加权。 使用特征空间轨迹（FST）方法对发电设备特性的正常工作范围曲线分布进行建模。 这种FST方法被说明性地与最小生成树（MST）方法一起使用以识别多个节点，然后将它们与近似于曲线的线段连接。

公开(公告)号：US07552035B2

公开(公告)日：2009-06-23

申请号：US10977220

申请日：2004-10-28

申请人： Zehra Cataltepe ,  Claus Neubauer ,  Chao Yuan

发明人： Zehra Cataltepe ,  Claus Neubauer ,  Chao Yuan

IPC分类号： G06F17/10

CPC分类号： G05B23/0243

摘要： A method to use a receiver operator characteristics curve for model comparison in machine condition monitoring. The method and systems of using this method may be used to evaluate different monitoring models. These models may be used to monitor a variety of different systems such as power plant systems or magnetic resonance imaging systems. The methods use training data and designate one or more points in the data as a false negative, thereby permitting a receiver operator characteristics analysis to be performed. Multiple receiver operator characteristics analyses may be performed either on different models or on different points within a single model, thereby permitting the receiver operator characteristics analyses to be used to select a beneficial model for monitoring a particular system.

摘要翻译： 一种在机器状态监测中使用接收机操作员特征曲线进行模型比较的方法。 使用该方法的方法和系统可用于评估不同的监测模型。 这些模型可用于监测各种不同的系统，例如发电厂系统或磁共振成像系统。 该方法使用训练数据并将数据中的一个或多个点指定为假阴性，从而允许执行接收者操作员特征分析。 可以在单个模型中的不同模型或不同点执行多个接收者操作者特征分析，从而允许接收者操作员特征分析用于选择用于监视特定系统的有益模型。

公开(公告)号：US07035763B2

公开(公告)日：2006-04-25

申请号：US10932577

申请日：2004-09-02

申请人： Chao Yuan ,  Claus Neubauer ,  Hans-Gerd Brummel ,  Ming Fang ,  Zehra Cataltepe

发明人： Chao Yuan ,  Claus Neubauer ,  Hans-Gerd Brummel ,  Ming Fang ,  Zehra Cataltepe

IPC分类号： G06F15/00 ,  G06F19/00

CPC分类号： G05B9/02 ,  G05B23/0254

摘要： A system for generating a sensor model for use in sensor-based monitoring is provided. The system includes a segmenting module for segmenting a collection of sensor vectors into a plurality of bins comprising distinct sensor vectors. The system also includes a set-generating module for generating a set of statistically significant sensor vectors for each bin. The system further includes a consistency determination module for generating at least one consistent set of sensor vectors from the sets of statistically significant sensor vectors. Additionally, the system includes a model-generating module for generating a sensor model based upon the at least one consistent set.

摘要翻译： 提供了一种用于生成用于基于传感器的监测的传感器模型的系统。 该系统包括分段模块，用于将传感器向量的集合分成多个包含不同传感器向量的箱。 该系统还包括用于为每个仓生成一组统计上显着的传感器向量的集合生成模块。 所述系统还包括一致性确定模块，用于从所述统计学上有意义的传感器向量集合生成至少一个一致的传感器向量集合。 另外，该系统包括用于基于至少一个一致集合生成传感器模型的模型生成模块。

公开(公告)号：US20050062599A1

公开(公告)日：2005-03-24

申请号：US10932576

申请日：2004-09-02

申请人： Claus Neubauer ,  Zehra Cataltepe ,  Chao Yuan ,  Jie Cheng ,  Ming Fang ,  Wesley McCorkle

发明人： Claus Neubauer ,  Zehra Cataltepe ,  Chao Yuan ,  Jie Cheng ,  Ming Fang ,  Wesley McCorkle

IPC分类号： G05B23/02 ,  G08B29/00

CPC分类号： G05B23/0272 ,  Y04S10/522

摘要： A tool for sensor management and fault visualization in machine condition monitoring. The method and system are able to monitor a plurality of sensors at one time. The sensors may be used in a power plant system monitoring system. The method and system may display a fault status for each sensor in the plurality of sensors in a single display, wherein the fault status for each sensor is displayed over time. The method and system also provide a mechanism that permits a user to examine details of each sensor in the plurality of sensors at any given time. In addition, the method and system are capable of categorizing each fault in the fault status using one or more properties or categorizing criteria. The method and system also permit sensors to be tested such that different operating models may be examined by utilizing different sensors.

摘要翻译： 机器状态监测中的传感器管理和故障可视化工具。 该方法和系统能够一次监视多个传感器。 传感器可用于发电厂系统监控系统。 该方法和系统可以在单个显示器中的多个传感器中的每个传感器显示故障状态，其中每个传感器的故障状态随时间显示。 该方法和系统还提供了允许用户在任何给定时间检查多个传感器中的每个传感器的细节的机构。 此外，该方法和系统能够使用一个或多个属性或分类标准对故障状态中的每个故障进行分类。 该方法和系统还允许测试传感器，使得可以通过利用不同的传感器检查不同的操作模型。

公开(公告)号：US20050055609A1

公开(公告)日：2005-03-10

申请号：US10932573

申请日：2004-09-02

申请人： Chao Yuan ,  Zehra Cataltepe ,  Claus Neubauer ,  Ming Fang

发明人： Chao Yuan ,  Zehra Cataltepe ,  Claus Neubauer ,  Ming Fang

IPC分类号： G05B23/02 ,  G06F11/00

CPC分类号： G05B23/0254 ,  G05B23/0235

摘要： A joint approach of out-of-range detection and fault detection for power plant monitoring. The method initially determines whether a sensor is an independent sensor or a dependent sensor. If the sensor is an independent sensor, then an operating range is established for each independent sensor. A reading from each independent sensor is then compared with the operating range that has been established. If the reading is out-of-range, an alarm may be activated. If the reading is not out-of-range, then this reading is used to determine an expected operating range for each dependent sensor. A reading from each dependent sensor is then compared with the predicted operating range. Again, if the reading from the dependent sensor is out of the expected range, an alarm may be sounded.

摘要翻译： 电站监控的超范围检测和故障检测的联合方法。 该方法最初确定传感器是独立传感器还是依赖传感器。 如果传感器是独立的传感器，则为每个独立的传感器建立一个工作范围。 然后将每个独立传感器的读数与已建立的操作范围进行比较。 如果读数超出范围，则可能会激活报警。 如果读数不超出范围，则该读数用于确定每个相关传感器的预期工作范围。 然后将每个从属传感器的读数与预测的工作范围进行比较。 再次，如果来自从属传感器的读数超出预期范围，则可能会发出警报。

公开(公告)号：US07216061B2

公开(公告)日：2007-05-08

申请号：US11210486

申请日：2005-08-24

申请人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

发明人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

IPC分类号： G06F15/00

CPC分类号： G06F11/0751 ,  G05B23/0221 ,  G06F11/0736

摘要： An apparatus for detecting faults in a system monitored by a plurality of sensors is provided. The apparatus includes a hidden process driver unit that generates a hidden process driver based upon sensor values received from a group of correlated sensors selected from among the plurality of sensors. The apparatus also includes a sensor estimating unit that generates sensor estimates for each of the plurality of sensors based upon the hidden process driver and a known process driver provided by an uncorrelated sensor. The apparatus further includes a fault determining unit that indicates a fault when a residual based upon a difference between a sensor value supplied by one of the plurality of sensors and a corresponding one of the sensor estimates lies outside an acceptable range of residual values.

摘要翻译： 提供了一种用于检测由多个传感器监控的系统中的故障的装置。 该装置包括隐藏的处理驱动器单元，其基于从从多个传感器中选择的一组相关传感器接收的传感器值来生成隐藏的处理驱动器。 该装置还包括传感器估计单元，其基于隐藏的处理驱动器和由不相关的传感器提供的已知的处理驱动程序来生成多个传感器中的每一个的传感器估计。 该装置还包括故障确定单元，当基于由多个传感器中的一个传感器提供的传感器值与传感器估计值之一之间的差值在残差值的可接受范围之外的残差时，指示故障。

公开(公告)号：US07188050B2

公开(公告)日：2007-03-06

申请号：US11197270

申请日：2005-08-04

申请人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

发明人： Chao Yuan ,  Claus Neubauer ,  Zehra Cataltepe

IPC分类号： G06F11/00 ,  G06F15/00

CPC分类号： G05B23/024

摘要： A method and apparatus for detecting out-of-range conditions representing normal operations is disclosed. A support vector machine is used to generate an improved representation of historical training data from power generation equipment that facilitates a more accurate determination of the boundary between measurements that should be considered faults and those that represent normal operating conditions. The SVM receives data collected from a plurality of independent sensors associated with the power generating equipment in order to generate a boundary substantially separating a first class of data (e.g., a fault) from a second class of data (e.g., a normal operating condition) in a support vector machine feature space. Elements of operational data are collected and compared to the boundary generated from historical training data. A determination is then made whether the element of operational data is in a particular class, such as a class associated with out-of-range conditions.

摘要翻译： 公开了一种用于检测表示正常操作的超范围条件的方法和装置。 支持向量机用于生成来自发电设备的历史训练数据的改进表示，其有助于更准确地确定应被认为是故障的测量值与表示正常操作条件的测量之间的边界。 SVM接收从与发电设备相关联的多个独立传感器收集的数据，以便产生基本上将第一类数据（例如，故障）与第二类数据（例如，正常操作条件）分离的边界， 在支持向量机的特征空间。 收集操作数据的元素，并与历史训练数据生成的边界进行比较。 然后确定操作数据的元素是否在特定类中，例如与超范围条件相关联的类。