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61. 发明授权

US08925791B2 Binary classification of items of interest in a repeatable process 有权
标题翻译：在可重复的过程中感兴趣的项目的二进制分类
公开(公告)号：US08925791B2
公开(公告)日：2015-01-06
申请号：US14264113
申请日：2014-04-29
申请人： GM Global Technology Operations LLC
发明人： Jeffrey A Abell , John Patrick Spicer , Michael Anthony Wincek , Hui Wang , Debejyo Chakraborty
IPC分类号： B23K1/06 , B23K5/20 , B23K20/00 , B23K20/10 , G05B11/00 , G05B11/06 , G06N99/00 , G05B23/02 , B23K20/12 , G05B1/00 , G05B1/01 , G05B1/04 , G05B11/01 , G05B19/00 , G05B19/02 , G05B19/04 , G05B19/18
CPC分类号： G06N99/005 , B23K20/10 , B23K20/106 , B23K20/12 , G05B1/00 , G05B1/01 , G05B1/04 , G05B11/00 , G05B11/01 , G05B11/011 , G05B19/00 , G05B19/02 , G05B19/04 , G05B19/18 , G05B23/0221
摘要： A system includes host and learning machines. Each machine has a processor in electrical communication with at least one sensor. Instructions for predicting a binary quality status of an item of interest during a repeatable process are recorded in memory. The binary quality status includes passing and failing binary classes. The learning machine receives signals from the at least one sensor and identifies candidate features. Features are extracted from the candidate features, each more predictive of the binary quality status. The extracted features are mapped to a dimensional space having a number of dimensions proportional to the number of extracted features. The dimensional space includes most of the passing class and excludes at least 90 percent of the failing class. Received signals are compared to the boundaries of the recorded dimensional space to predict, in real time, the binary quality status of a subsequent item of interest.
摘要翻译：系统包括主机和学习机。每个机器具有与至少一个传感器电通信的处理器。用于在可重复处理期间预测感兴趣的项目的二进制质量状态的指令被记录在存储器中。二进制质量状态包括传递和失败的二进制类。学习机器接收来自至少一个传感器的信号并识别候选特征。从候选特征中提取特征，每个特征更加预测二进制质量状态。提取的特征被映射到具有与提取的特征的数量成比例的数量的维数的维空间。维空间包含大部分传递类，并排除失败类的至少90％。将接收的信号与记录的维度空间的边界进行比较，以实时地预测随后的感兴趣的物品的二进制质量状态。

62. 发明申请

US20140372078A1 METHOD AND DEVICE FOR DETECTING A FAILURE ON AN AIRCRAFT 审中-公开
标题翻译：用于检测飞机失效的方法和装置
公开(公告)号：US20140372078A1
公开(公告)日：2014-12-18
申请号：US14306655
申请日：2014-06-17
申请人： AIRBUS OPERATIONS (SAS) , INSTITUT POLYTECHNIQUE DE BORDEAUX , CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) , UNIVERSITE DE BORDEAUX
发明人： Anca GHEORGHE , Philippe GOUPIL , Rémy DAYRE , Ali ZOLGHADRI , Jérôme CIESLAK , Denis EFIMOV
IPC分类号： G01M17/00
CPC分类号： G01M17/00 , B64C13/50 , G05B23/0221
摘要： The detecting means (1) comprise measuring means (2) adapted to measure and provide at least one raw data corresponding to an aircraft parameter, computing means (3) adapted to estimate at least one derivative of said raw data, and detecting means (4) adapted to detect a failure with the aid of said derivative, said computing means (3) being adapted to estimate said derivative by differentiation.
摘要翻译：检测装置（1）包括测量装置（2），其适于测量和提供对应于飞机参数的至少一个原始数据，适于估计所述原始数据的至少一个导数的计算装置（3）和检测装置）适于通过所述导数来检测故障，所述计算装置（3）适于通过微分来估计所述导数。

63. 发明申请

US20140368340A1 Self-Configuring System for Real-Time Health Monitoring of Manufacturing Equipment 有权
标题翻译：用于制造设备实时健康监测的自配置系统
公开(公告)号：US20140368340A1
公开(公告)日：2014-12-18
申请号：US13915787
申请日：2013-06-12
申请人： Zbigniew Jerzak , Yuanzhen Ji
发明人： Zbigniew Jerzak , Yuanzhen Ji
IPC分类号： G08B21/18
CPC分类号： G08B21/182 , G05B19/048 , G05B23/0221 , G05B2219/21062
摘要： Data is received that comprises at least one data stream derived from each of a plurality of sensors that each characterize one or more attributes of equipment components. Thereafter, using the received data and a density-based clustering algorithm that produces micro-clusters for each pair of sensors, correlated sensors having component correlations above a pre-defined threshold are identified. It can then be determined that data from two or more correlated sensors triggers at least one alert event. Subsequently, data is provided that characterizes the at least one alert event. Related apparatus, systems, techniques and articles are also described.
摘要翻译：收到的数据包括从多个传感器中的每一个导出的每个表征设备部件的一个或多个属性的至少一个数据流。此后，使用接收的数据和基于密度的聚类算法，为每对传感器产生微簇，识别具有高于预定义阈值的分量相关性的相关传感器。然后可以确定来自两个或更多个相关传感器的数据触发至少一个警报事件。随后，提供表征至少一个警报事件的数据。还描述了相关设备，系统，技术和物品。

64. 发明申请

US20140358465A1 YIELD ANALYSIS SYSTEM AND METHOD USING SENSOR DATA OF FABRICATION EQUIPMENT 审中-公开
标题翻译： YIELD分析系统和使用制造设备传感器数据的方法
公开(公告)号：US20140358465A1
公开(公告)日：2014-12-04
申请号：US14011873
申请日：2013-08-28
申请人： SAMSUNG SDS CO., LTD.
发明人： Kae Young SHIN , Jong Seung LIM , Dae Jung AHN , Seung Jai MIN , Jong Ho LEE
IPC分类号： H01L21/66
CPC分类号： H01L22/20 , G05B19/41875 , G05B23/0221 , G05B2223/02 , Y02P90/22
摘要： A system and method for analyzing a product fabrication process are disclosed. A product yield analysis system according to an exemplary embodiment of the present disclosure includes a data extraction unit that extracts sensor data from a plurality of sensors arranged in equipment for fabricating a product, a reference signal generation unit that generates a reference signal for each of the plurality of sensors from the sensor data, and a sensor detection unit that detects one or more sensors having a correlation with a yield of the product using the sensor data and the reference signal.
摘要翻译：公开了一种用于分析产品制造过程的系统和方法。根据本公开的示例性实施例的产品收益率分析系统包括：数据提取单元，其从布置在用于制造产品的设备中的多个传感器中提取传感器数据;参考信号生成单元，来自传感器数据的多个传感器，以及传感器检测单元，其使用传感器数据和参考信号来检测与产品的产量相关的一个或多个传感器。

65. 发明申请

US20140325292A1 VIRTUAL DATA POINT CREATION MECHANISM FOR A BUILDING MANAGEMENT FAULT DETECTION SYSTEM 审中-公开
标题翻译：建筑物管理故障检测系统的虚拟数据点创建机制
公开(公告)号：US20140325292A1
公开(公告)日：2014-10-30
申请号：US14162832
申请日：2014-01-24
申请人： ENERNOC, INC.
发明人： Edward C. Spivey , Lindsay K. Spivey
IPC分类号： G06F11/07
CPC分类号： G06F11/0751 , G01M99/00 , G05B15/02 , G05B23/0213 , G05B23/0218 , G05B23/0221 , G05B23/0254 , G05B2219/24033 , G05B2219/2642 , G05B2219/37537
摘要： An apparatus for detecting faults of components monitored by a building management system (BMS), including an automatic fault detection (AFD) element that monitors, in real time, data samples generated by the BMS indicating operative states of the components, and that employs the data samples to determine if one or more of the components are faulty. The AFD element includes a run time modeling element and a virtual datapoint creating element. The run time modeling element employs the data samples as inputs to execute one or more fault algorithms retrieved from a system configuration model, and generates outputs to the one or more fault algorithms that indicate if the one or more of the components are faulty. The virtual datapoint creating element estimates one or more synthesized datapoints that may be required by the one or more fault algorithms during execution by the run time modeling element.
摘要翻译：一种用于检测由建筑物管理系统（BMS）监控的构件的故障的装置，包括自动故障检测（AFD）元件，其实时监视由指示组件的操作状态的BMS产生的数据样本，并且采用数据样本以确定一个或多个组件是否有故障。 AFD元素包括运行时建模元素和虚拟数据点创建元素。运行时建模元件使用数据样本作为输入来执行从系统配置模型检索的一个或多个故障算法，并且生成指示所述一个或多个组件是否有故障的一个或多个故障算法的输出。虚拟数据点创建元素估计运行时间建模元件执行期间一个或多个故障算法可能需要的一个或多个合成数据点。

66. 发明申请

US20140325291A1 APPARATUS AND METHOD FOR SELECTION OF FAULT DETECTION ALGORITHMS FOR A BUILDING MANAGEMENT SYSTEM 审中-公开
标题翻译：选择用于建筑管理系统的故障检测算法的装置和方法
公开(公告)号：US20140325291A1
公开(公告)日：2014-10-30
申请号：US14162820
申请日：2014-01-24
申请人： ENERNOC, INC.
发明人： Edward C. Spivey , Lindsay K. Spivey
IPC分类号： G06F11/07
CPC分类号： G06F11/0751 , G01M99/00 , G05B15/02 , G05B23/0213 , G05B23/0218 , G05B23/0221 , G05B23/0254 , G05B2219/24033 , G05B2219/2642 , G05B2219/37537
摘要： An apparatus for detecting component faults monitored by a building management system (BMS), including an automatic fault detection (AFD) element, coupled to the BMS, that monitors samples generated by the BMS indicating operative states of the components, and that employs the data samples to determine if one or more of the components are faulty. The AFD element includes a run time modeling element and a fault detection algorithm element. The modeling element employs the samples as inputs to execute one or more fault algorithms retrieved from a system model, and generates outputs that indicate if the one or more of the components are faulty. The algorithm element is coupled to the system model, and employs normalized/standardized datapoints representing the samples to select the one or more fault algorithms for storage in the system model, where the one or more fault algorithms are selected from a standard fault algorithm data base.
摘要翻译：一种用于检测由楼宇管理系统（BMS）监控的组件故障的装置，包括耦合到BMS的自动故障检测（AFD）元件，其监视由BMS产生的指示组件的操作状态的采样，并且采用该数据样本以确定一个或多个组件是否有故障。 AFD元件包括运行时间建模元件和故障检测算法元件。建模元件使用样本作为输入来执行从系统模型检索的一个或多个故障算法，并且生成指示所述一个或多个组件是否有故障的输出。算法元件耦合到系统模型，并且采用表示采样的归一化/标准化数据点来选择用于在系统模型中存储的一个或多个故障算法，其中从标准故障算法数据库中选择一个或多个故障算法。

67. 发明申请

US20140324386A1 BUILDING MANAGEMENT SYSTEM FALSE-POSITIVE FAULT INDICATIONS REDUCTION MECHANISM 审中-公开
标题翻译：建筑管理系统虚拟正确的故障指示减少机制
公开(公告)号：US20140324386A1
公开(公告)日：2014-10-30
申请号：US14162838
申请日：2014-01-24
申请人： ENERNOC, INC.
发明人： Edward C. Spivey , Lindsay K. Spivey
IPC分类号： G01M99/00
CPC分类号： G06F11/0751 , G01M99/00 , G05B15/02 , G05B23/0213 , G05B23/0218 , G05B23/0221 , G05B23/0254 , G05B2219/24033 , G05B2219/2642 , G05B2219/37537
摘要： An apparatus for detecting faults of components monitored by a building management system (BMS), including an automatic fault detection (AFD) element that monitors data samples generated by the BMS indicating operative states of the components, and that determines if components are faulty. The AFD element includes a run time modeling element and a fault detection algorithm element. The run time modeling element employs the data samples and synthesized datapoints as inputs to execute fault algorithms retrieved from a system model, and generates outputs that indicate if the components are faulty, where employment of the synthesized datapoints increases fault coverage, resulting in a reduction of false alarms. The fault detection algorithm element employs normalized and standardized datapoints representing the data samples and the synthesized datapoints to automatically select the fault algorithms for storage in the system model, where the fault algorithms are selected from a standard fault algorithm data base.
摘要翻译：一种用于检测由建筑物管理系统（BMS）监控的部件的故障的装置，包括自动故障检测（AFD）元件，该自动故障检测（AFD）元件监视由BMS生成的指示组件的操作状态的数据样本，并且确定组件是否有故障。 AFD元件包括运行时间建模元件和故障检测算法元件。运行时建模元素采用数据样本和合成数据点作为输入，用于执行从系统模型检索的故障算法，并生成指示组件是否有故障的输出，其中合成数据点的使用增加了故障覆盖，从而导致虚假警报。故障检测算法元素采用标准化和标准化的数据点，代表数据样本和合成数据点，自动选择故障算法存储在系统模型中，故障算法从标准故障算法数据库中选择。

68. 发明申请

US20140280851A1 COMPLEX SYSTEM FUNCTION STATUS DIAGNOSIS AND PRESENTATION 审中-公开
标题翻译：复杂系统功能状态诊断和呈现
公开(公告)号：US20140280851A1
公开(公告)日：2014-09-18
申请号：US14262746
申请日：2014-04-26
申请人： The Boeing Company
发明人： Garry Gean Herzberg , Timothy Edward Jackson , Tracy Andrew Small , Charles Daniel Cowles , Erin Elizabeth Warr , Allen R. Link , Mark D. McCleary
IPC分类号： H04L12/24
CPC分类号： H04L41/00 , G05B23/0221 , G05B23/0229 , G06F11/3013 , G06F11/3055 , G06F11/3072 , H04L43/028 , H04L43/04 , H04L43/0817 , H04L43/18 , H04L43/50 , H04L67/12 , Y04S40/168 , Y04S40/18
摘要： Status of complex system functions is diagnosed and reported by analyzing traffic on a data network of the complex system. The network traffic may be placed on the data network by systems that perform functions for the complex system. A user may make a view selection via a remote user interface. The view selection identifies rules for determining a status of a selected subset of the functions or a status of selected ones of the functions for a selected state of operation, such as during initial power-up. The status of the functions may be determined from the network traffic using the rules and presented to the user via the user interface. The user may interact with the presentation to make different view selections. Multiple different view selections made via multiple different user interfaces may be supported simultaneously.
摘要翻译：通过分析复杂系统的数据网络上的流量来诊断和报告复杂系统功能的状态。可以通过为复杂系统执行功能的系统将网络流量放置在数据网络上。用户可以通过远程用户界面进行视图选择。视图选择识别用于确定所选择的功能子集的状态或用于所选择的操作状态的所选功能的状态的规则，诸如在初始加电期间。功能的状态可以使用规则从网络流量确定，并通过用户界面呈现给用户。用户可以与演示文稿进行交互以进行不同的视图选择。可以同时支持通过多个不同的用户界面进行的多个不同的视图选择。

69. 发明申请

US20140277921A1 SYSTEM AND METHOD FOR DATA ENTITY IDENTIFICATION AND ANALYSIS OF MAINTENANCE DATA 审中-公开
标题翻译：用于数据实体识别的系统和方法以及维护数据分析
公开(公告)号：US20140277921A1
公开(公告)日：2014-09-18
申请号：US13829619
申请日：2013-03-14
申请人： GENERAL ELECTRIC COMPANY
发明人： Vineel Chandrakanth Gujjar , Debasis Bal , Gopi Subramanian , Brian David Larder , Andrew James Smith , Mark Thomas Harrington
IPC分类号： B64F5/00
CPC分类号： G06Q10/20 , G05B23/0221 , G05B23/0283 , G06F16/3344
摘要： A method for identifying and analyzing data entities from (maintenance, repair, and overhaul (MRO)) data is provided. The method includes obtaining MRO data comprising unstructured text information. The method also includes performing named entity recognition on the MRO data to extract entities from the unstructured text information and label the entities with a tag. The method further includes analyzing the labeled entities via a heuristic to estimate an effectiveness of a fix for a specific issue or to estimate a reliability of a component.
摘要翻译：提供了一种从（维护，修理和大修（MRO））数据中识别和分析数据实体的方法。该方法包括获得包含非结构化文本信息的MRO数据。该方法还包括在MRO数据上执行命名实体识别，以从非结构化文本信息中提取实体并用标签来标记实体。该方法还包括通过启发式分析标记实体以估计针对特定问题的修复的有效性或估计组件的可靠性。

70. 发明申请

US20140236874A1 BINARY CLASSIFICATION OF ITEMS OF INTEREST IN A REPEATABLE PROCESS 审中-公开
标题翻译：可重复进程中的兴趣项目的二进制分类
公开(公告)号：US20140236874A1
公开(公告)日：2014-08-21
申请号：US14264113
申请日：2014-04-29
申请人： GM GLOBAL TECHNOLOGY OPERATIONS LLC
发明人： Jeffrey A. Abell , John Patrick Spicer , Michael Anthony Wincek , Hui Wang , Debejyo Chakraborty
IPC分类号： G06N99/00
CPC分类号： G06N99/005 , B23K20/10 , B23K20/106 , B23K20/12 , G05B1/00 , G05B1/01 , G05B1/04 , G05B11/00 , G05B11/01 , G05B11/011 , G05B19/00 , G05B19/02 , G05B19/04 , G05B19/18 , G05B23/0221
摘要： A system includes host and learning machines. Each machine has a processor in electrical communication with at least one sensor. Instructions for predicting a binary quality status of an item of interest during a repeatable process are recorded in memory. The binary quality status includes passing and failing binary classes. The learning machine receives signals from the at least one sensor and identifies candidate features. Features are extracted from the candidate features, each more predictive of the binary quality status. The extracted features are mapped to a dimensional space having a number of dimensions proportional to the number of extracted features. The dimensional space includes most of the passing class and excludes at least 90 percent of the failing class. Received signals are compared to the boundaries of the recorded dimensional space to predict, in real time, the binary quality status of a subsequent item of interest.
摘要翻译：系统包括主机和学习机。每个机器具有与至少一个传感器电通信的处理器。用于在可重复处理期间预测感兴趣的项目的二进制质量状态的指令被记录在存储器中。二进制质量状态包括传递和失败的二进制类。学习机器接收来自至少一个传感器的信号并识别候选特征。从候选特征中提取特征，每个特征更加预测二进制质量状态。提取的特征被映射到具有与提取的特征的数量成比例的数量的维数的维空间。维空间包含大部分传递类，并排除失败类的至少90％。将接收的信号与记录的维度空间的边界进行比较，以实时地预测随后的感兴趣的物品的二进制质量状态。

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