公开(公告)号：US09886478B2

公开(公告)日：2018-02-06

申请号：US13115006

申请日：2011-05-24

Applicant: Joydeb Mukherjee

Inventor： Joydeb Mukherjee

IPC: G06F7/00 ,  G06F17/30 ,  B64F5/60 ,  B64F5/40 ,  G07C5/08 ,  G10L15/26 ,  G06F17/27 ,  G06F17/28

CPC classification number: G06F17/3043 ,  B64F5/40 ,  B64F5/60 ,  G06F17/277 ,  G06F17/2785 ,  G06F17/2881 ,  G06F17/30401 ,  G07C5/0808 ,  G10L15/26

Abstract: An aircraft service information handling system comprises an input module operable to collect field service narrative data. A natural language data extraction module extracts problem data and related solution data from the narrative data, and a database module populates an aircraft service information database with the extracted problem data and the related extracted solution data. The database module further searches the database for populated problem data, and retrieves the related populated solution data.

公开(公告)号：US20110257839A1

公开(公告)日：2011-10-20

申请号：US13115006

申请日：2011-05-24

Applicant: Joydeb Mukherjee

Inventor： Joydeb Mukherjee

IPC: G06F17/00

CPC classification number: G06F17/3043 ,  B64F5/40 ,  B64F5/60 ,  G06F17/277 ,  G06F17/2785 ,  G06F17/2881 ,  G06F17/30401 ,  G07C5/0808 ,  G10L15/26

Abstract: An aircraft service information handling system comprises an input module operable to collect field service narrative data. A natural language data extraction module extracts problem data and related solution data from the narrative data, and a database module populates an aircraft service information database with the extracted problem data and the related extracted solution data. The database module further searches the database for populated problem data, and retrieves the related populated solution data.

Abstract translation: 飞机服务信息处理系统包括可操作以收集现场服务叙述数据的输入模块。 自然语言数据提取模块从叙述数据中提取问题数据和相关解决方案数据，数据库模块利用提取的问题数据和相关提取的解决方案数据填充飞机服务信息数据库。 数据库模块还在数据库中搜索填充的问题数据，并检索相关的填充解决方案数据。

公开(公告)号：US08620519B2

公开(公告)日：2013-12-31

申请号：US11201694

申请日：2005-08-10

Applicant: Joydeb Mukherjee ,  Venkataramana B. Kini ,  Sunil K. Menon

Inventor： Joydeb Mukherjee ,  Venkataramana B. Kini ,  Sunil K. Menon

IPC: G01M15/14 ,  G06F17/16 ,  G06F17/17

CPC classification number: G01M15/14 ,  G05B23/0254 ,  G06F17/16 ,  G06F17/175

Abstract: An improved fault detection system and method is provided. The fault detection system and method combines the use of discrimination and representation based feature extraction to reliably detect symptoms of faults in turbine engines. Specifically, the fault detection system and method uses a kernel-based Maximum Representation Discrimination Features (MRDF) technique to detect symptoms of fault in turbine engines. The kernel-based MRDF system and method combines the use of discriminatory features and representation features in historical sensor data to facilitate feature extraction and classification of new sensor data as indicative fault in the turbine engine. Furthermore, the kernel-based MRDF technique facilitates the uncovering of nonlinear features in the sensor data, thus improving the reliability of the fault detection.

Abstract translation: 提供了一种改进的故障检测系统和方法。 故障检测系统和方法结合了使用歧视和基于表示的特征提取，可靠地检测涡轮发动机故障的症状。 具体来说，故障检测系统和方法使用基于内核的最大表征识别特征（MRDF）技术来检测涡轮发动机故障的症状。 基于内核的MRDF系统和方法结合了历史传感器数据中的区别特征和表示特征的使用，以便于将特征提取和新传感器数据分类为涡轮发动机中的指示故障。 此外，基于内核的MRDF技术有助于揭示传感器数据中的非线性特征，从而提高故障检测的可靠性。

公开(公告)号：US07660774B2

公开(公告)日：2010-02-09

申请号：US11165985

申请日：2005-06-24

Applicant: Joydeb Mukherjee ,  Sunil Menon ,  Venkataramana B. Kini ,  Dinkar Mylaraswamy

Inventor： Joydeb Mukherjee ,  Sunil Menon ,  Venkataramana B. Kini ,  Dinkar Mylaraswamy

IPC: G06E1/00

CPC classification number: G06N3/0454

Abstract: A system and method for fault detection is provided. The fault detection system provides the ability to detect symptoms of fault in turbine engines and other mechanical systems that have nonlinear relationships. The fault detection system uses a neural network to perform a data representation and feature extraction where the extracted features are analogous to principal components derived in a principal component analysis. This neural network data representation analysis can then be used to determine the likelihood of a fault in the system.

Abstract translation: 提供了一种用于故障检测的系统和方法。 故障检测系统提供检测涡轮发动机和其他具有非线性关系的机械系统的故障症状的能力。 故障检测系统使用神经网络来执行数据表示和特征提取，其中提取的特征类似于主成分分析中导出的主成分。 然后可以使用该神经网络数据表示分析来确定系统中故障的可能性。

公开(公告)号：US08963733B2

公开(公告)日：2015-02-24

申请号：US13371576

申请日：2012-02-13

Applicant: Chinmaya Kar ,  Rajat Sadana ,  Joydeb Mukherjee

Inventor： Chinmaya Kar ,  Rajat Sadana ,  Joydeb Mukherjee

IPC: F16C17/24

CPC classification number: G01M13/02 ,  G01M13/021 ,  G01M13/028 ,  G01M13/045

Abstract: A system includes more sensors configured to measure one or more characteristics of rotating equipment and a blind fault detection device. The blind fault detection device includes an input interface configured to receive at least one input signal from the one or more sensors. The blind fault detection device also includes a processing unit configured to identify a fault in the rotating equipment using the at least one input signal. The blind fault detection device further includes an output interface configured to provide an indicator identifying the fault. The processing unit is configured to identify the fault by determining at least one family of frequencies related to at least one sensor point, determining an average energy for the at least one sensor point based on the at least one family of frequencies, and comparing the average energy to a baseline value.

Abstract translation: 系统包括配置成测量旋转设备和盲故障检测设备的一个或多个特性的更多传感器。 盲目故障检测装置包括被配置为从一个或多个传感器接收至少一个输入信号的输入接口。 盲故障检测装置还包括处理单元，其被配置为使用至少一个输入信号来识别旋转设备中的故障。 盲目故障检测装置还包括被配置为提供识别故障的指示符的输出接口。 处理单元被配置为通过确定与至少一个传感器点相关的至少一个频率族来确定故障，基于至少一个频率族确定至少一个传感器点的平均能量，并且比较平均值 能量达到基准值。

公开(公告)号：US20130207810A1

公开(公告)日：2013-08-15

申请号：US13371576

申请日：2012-02-13

Applicant: Chinmaya Kar ,  Rajat Sadana ,  Joydeb Mukherjee

Inventor： Chinmaya Kar ,  Rajat Sadana ,  Joydeb Mukherjee

IPC: G08B21/00

CPC classification number: G01M13/02 ,  G01M13/021 ,  G01M13/028 ,  G01M13/045

Abstract: A system includes more sensors configured to measure one or more characteristics of rotating equipment and a blind fault detection device. The blind fault detection device includes an input interface configured to receive at least one input signal from the one or more sensors. The blind fault detection device also includes a processing unit configured to identify a fault in the rotating equipment using the at least one input signal. The blind fault detection device further includes an output interface configured to provide an indicator identifying the fault. The processing unit is configured to identify the fault by determining at least one family of frequencies related to at least one sensor point, determining an average energy for the at least one sensor point based on the at least one family of frequencies, and comparing the average energy to a baseline value.

Abstract translation: 系统包括配置成测量旋转设备和盲故障检测设备的一个或多个特性的更多传感器。 盲目故障检测装置包括被配置为从一个或多个传感器接收至少一个输入信号的输入接口。 盲故障检测装置还包括处理单元，其被配置为使用至少一个输入信号来识别旋转设备中的故障。 盲目故障检测装置还包括被配置为提供识别故障的指示符的输出接口。 处理单元被配置为通过确定与至少一个传感器点相关的至少一个频率族来确定故障，基于至少一个频率族确定至少一个传感器点的平均能量，并且比较平均值 能量达到基准值。

公开(公告)号：US07991580B2

公开(公告)日：2011-08-02

申请号：US12104039

申请日：2008-04-16

Applicant: Lokesh Sambasivan ,  Joydeb Mukherjee ,  Dinkar Mylaraswamy

Inventor： Lokesh Sambasivan ,  Joydeb Mukherjee ,  Dinkar Mylaraswamy

IPC: G06F17/18

CPC classification number: G05B23/0297

Abstract: A method for benchmarking diagnostic algorithms for a particular application is provided. The diagnostic algorithms are rank ordered based on a specified criterion so as to weed out weak algorithms, selecting more robust algorithms, defined in some sense, for deployment. This is realized by evaluating various parameters subsequently mentioned. A normalized product entropy ratio parameter is obtained. A performance parameter vector is fixed to define a plurality of sensitivity parameters including a plurality of threshold parameters and a plurality of data parameters. The plurality of threshold parameters and the plurality of data parameters are perturbed to obtain a threshold sensitivity parameter and a data sensitivity parameter.

Abstract translation: 提供了一种用于针对特定应用的基准诊断算法的方法。 诊断算法基于指定的标准进行排序，从而消除弱算法，选择更有力的算法，在某种意义上定义用于部署。 这是通过评估随后提到的各种参数来实现的。 得到归一化的产品熵比参数。 固定性能参数向量以定义多个灵敏度参数，包括多个阈值参数和多个数据参数。 扰动多个阈值参数和多个数据参数以获得阈值灵敏度参数和数据灵敏度参数。

公开(公告)号：US07949444B2

公开(公告)日：2011-05-24

申请号：US11245659

申请日：2005-10-07

Applicant: Joydeb Mukherjee

Inventor： Joydeb Mukherjee

IPC: G06F7/00 ,  G06F17/00

CPC classification number: G06F17/3043 ,  G06F17/30401 ,  G10L15/26

Abstract: An aircraft service information handling system comprises an input module operable to collect field service narrative data. A natural language data extraction module extracts problem data and related solution data from the narrative data, and a database module populates an aircraft service information database with the extracted problem data and the related extracted solution data. The database module further searches the database for populated problem data, and retrieves the related populated solution data.

Abstract translation: 飞机服务信息处理系统包括可操作以收集现场服务叙述数据的输入模块。 自然语言数据提取模块从叙述数据中提取问题数据和相关解决方案数据，数据库模块利用提取的问题数据和相关提取的解决方案数据填充飞机服务信息数据库。 数据库模块还在数据库中搜索填充的问题数据，并检索相关的填充解决方案数据。

公开(公告)号：US20100030492A1

公开(公告)日：2010-02-04

申请号：US12503783

申请日：2009-07-15

Applicant: Chinmaya Kar ,  Rajat Sadana ,  Venkataramana B. Kini ,  Meenakshi Suderam ,  Joydeb Mukherjee ,  Vedika Agrawal

Inventor： Chinmaya Kar ,  Rajat Sadana ,  Venkataramana B. Kini ,  Meenakshi Suderam ,  Joydeb Mukherjee ,  Vedika Agrawal

IPC: G01B5/28

CPC classification number: F16C19/52 ,  F16C41/00 ,  F16C2233/00 ,  G01H1/00 ,  G01M13/045

Abstract: A method includes receiving an input signal containing information associated with a rolling element bearing and/or a piece of equipment containing the rolling element bearing. The method also includes decomposing the input signal into a frequency-domain signal and determining at least one family of frequencies corresponding to at least one failure mode of the rolling element bearing. The method further includes generating a reconstructed input signal using the at least one family of frequencies and the frequency-domain signal. In addition, the method includes determining, using the reconstructed input signal, an indicator identifying an overall health of the rolling element bearing. The indicator could be determined using a baseline signal associated with either (i) normal operation of the rolling element bearing and/or the piece of equipment or (ii) defective operation of the rolling element bearing and/or the piece of equipment (where a severity of the defective operation will increase over time).

Abstract translation: 一种方法包括接收包含与滚动元件轴承相关联的信息的输入信号和/或包含滚动元件轴承的一件设备。 该方法还包括将输入信号分解成频域信号并且确定与滚动元件轴承的至少一个故障模式相对应的至少一个频率族。 该方法还包括使用至少一个频率族和频域信号来产生重建的输入信号。 另外，该方法包括使用重建的输入信号来确定识别滚动元件轴承的总体健康状态的指示器。 可以使用与（i）滚动体轴承和/或设备件的正常操作相关联的基线信号来确定指示器，或（ii）滚动元件轴承和/或设备件的不良操作（其中a 缺陷操作的严重程度随时间而增加）。

公开(公告)号：US20090265134A1

公开(公告)日：2009-10-22

申请号：US12104039

申请日：2008-04-16

Applicant: Lokesh Sambasivan ,  Joydeb Mukherjee ,  Dinkar Mylaraswamy

Inventor： Lokesh Sambasivan ,  Joydeb Mukherjee ,  Dinkar Mylaraswamy

IPC: G06F17/18

CPC classification number: G05B23/0297

Abstract: A method for benchmarking diagnostic algorithms for a particular application is provided. The diagnostic algorithms are rank ordered based on a specified criterion so as to weed out weak algorithms, selecting more robust algorithms, defined in some sense, for deployment. This is realized by evaluating various parameters subsequently mentioned. A normalized product entropy ratio parameter is obtained. A performance parameter vector is fixed to define a plurality of sensitivity parameters including a plurality of threshold parameters and a plurality of data parameters. The plurality of threshold parameters and the plurality of data parameters are perturbed to obtain a threshold sensitivity parameter and a data sensitivity parameter.

Abstract translation: 提供了一种用于针对特定应用的基准诊断算法的方法。 诊断算法基于指定的标准进行排序，从而消除弱算法，选择更有力的算法，在某种意义上定义用于部署。 这是通过评估随后提到的各种参数来实现的。 得到归一化的产品熵比参数。 固定性能参数向量以定义多个灵敏度参数，包括多个阈值参数和多个数据参数。 扰动多个阈值参数和多个数据参数以获得阈值灵敏度参数和数据灵敏度参数。