公开(公告)号：WO2014107303A1

公开(公告)日：2014-07-10

申请号：PCT/US2013/075905

申请日：2013-12-18

Applicant: SIEMENS CORPORATION ,  SIEMENS ENERGY, INC. ,  SIEMENS AKTIENGESELLSCHAFT ,  GUAN, Xuefei ,  ZHANG, Jingdan ,  ZHOU, Shaohua Kevin ,  KADAU, Kai ,  GUO, Yan ,  RASSELKORDE, El Mahjoub ,  ABBASI, Waheed A. ,  LEE, Chin-Sheng ,  LEWIS, Ashley L. ,  RADKE, Steve H.

Inventor： GUAN, Xuefei ,  ZHANG, Jingdan ,  ZHOU, Shaohua Kevin ,  KADAU, Kai ,  GUO, Yan ,  RASSELKORDE, El Mahjoub ,  ABBASI, Waheed A. ,  LEE, Chin-Sheng ,  LEWIS, Ashley L. ,  RADKE, Steve H.

IPC: G01N29/44 ,  G01N3/32 ,  G06F17/18

CPC classification number: G06N7/005 ,  G01N29/4472 ,  G01N2203/0066 ,  G01N2203/0073 ,  G01N2203/0214 ,  G01N2291/0258 ,  G06F17/5009

Abstract: A method for probabilistic fatigue life prediction using nondestructive testing data considering uncertainties from nondestructive examination (NDE) data and fatigue model parameters. The method utilizes uncertainty quantification models for detection, sizing, fatigue model parameters and inputs. A probability of detection model is developed based on a log-linear model coupling an actual flaw size with a nondestructive examination (NDE) reported size. A distribution of the actual flaw size is derived for both NDE data without flaw indications and NDE data with flaw indications by using probabilistic modeling and Bayes theorem. A turbine rotor example with real world NDE inspection data is presented to demonstrate the overall methodology.

Abstract translation: 考虑非破坏性检查（NDE）数据和疲劳模型参数的不确定性，使用非破坏性测试数据的概率疲劳寿命预测方法。 该方法利用不确定性量化模型进行检测，大小，疲劳模型参数和输入。 基于将实际缺陷大小与非破坏性检查（NDE）报告的大小相联系的对数线性模型开发了检测概率。 通过使用概率建模和贝叶斯定理，可以为无缺陷指示的NDE数据和缺陷指示的NDE数据导出实际缺陷大小的分布。 提出了具有真实世界NDE检测数据的涡轮转子实例，以演示整体方法。

公开(公告)号：WO2014055822A1

公开(公告)日：2014-04-10

申请号：PCT/US2013/063377

申请日：2013-10-04

Applicant: SIEMENS CORPORATION ,  SIEMENS ENERGY, INC. ,  GUAN, Xuefei ,  ZHANG, Jingdan ,  ZHOU, Shaohua Kevin ,  ULERICH, Nancy H. ,  KIM, Nam Eung ,  TEVS, Nikolai R.

Inventor： GUAN, Xuefei ,  ZHANG, Jingdan ,  ZHOU, Shaohua Kevin ,  ULERICH, Nancy H. ,  KIM, Nam Eung ,  TEVS, Nikolai R.

IPC: G01M5/00 ,  G01M15/14

CPC classification number: G01L5/00 ,  G01D21/00 ,  G01H17/00 ,  G01M5/0016 ,  G01M5/0041 ,  G01M15/14 ,  G01N3/56 ,  G06F17/40 ,  G06F19/00

Abstract: A method dynamically reconstructing a stress and strain field of a turbine blade includes providing a set of response measurements from at least one location on a turbine blade, band-pass filtering (32) the set of response measurements based on an upper frequency limit and a lower frequency limit, determining (33) an upper envelope and a lower envelope of the set of response measurements from local minima and local maxima of the set of response measurements, calculating (34) a candidate intrinsic mode function (IMF) from the upper envelope and the lower envelope of the set of response measurements, providing (37) an N x N mode shape matrix for the turbine blade, where N is the number of degrees of freedom of the turbine blade, when the candidate IMF is an actual IMF, and calculating (38) a response for another location on the turbine blade from the actual IMF and mode shapes in the mode shape matrix.

Abstract translation: 动态地重建涡轮叶片的应力和应变场的方法包括从涡轮叶片上的至少一个位置提供一组响应测量值，基于上限频率带通滤波（32）响应测量集合，以及 较低的频率限制，从所述一组响应测量的局部最小值和局部最大值确定（33）所述一组响应测量的上包络和下包络，从所述上包络线计算（34）候选固有模函数（IMF） 和所述一组响应测量的下部包络，提供（37）用于所述涡轮叶片的N×N模式形状矩阵，其中当所述候选IMF是实际IMF时，其中N是所述涡轮叶片的自由度的数量， 并且从模式形状矩阵中的实际IMF和模式形状计算（38）对涡轮叶片上的另一位置的响应。

公开(公告)号：WO2012040410A2

公开(公告)日：2012-03-29

申请号：PCT/US2011052675

申请日：2011-09-22

Applicant: SIEMENS CORP ,  SIEMENS AG ,  LIU DAVID ,  WU DIJIA ,  ZHOU SHAOHUA KEVIN ,  COSTA MARIA JIMENA ,  SUEHLING MICHAEL ,  TIETJEN CHRISTIAN

Inventor： LIU DAVID ,  WU DIJIA ,  ZHOU SHAOHUA KEVIN ,  COSTA MARIA JIMENA ,  SUEHLING MICHAEL ,  TIETJEN CHRISTIAN

IPC: G06T7/00

CPC classification number: G06T7/0016 ,  G06T7/41 ,  G06T2207/10072 ,  G06T2207/20012 ,  G06T2207/20041 ,  G06T2207/20081 ,  G06T2207/20104 ,  G06T2207/30056

Abstract: A method and system for automatically detecting liver lesions in medical image data, such as 3D CT images, is disclosed. A liver region is segmented in a 3D image. Liver lesion center candidates are detected in the segmented liver region. Lesion candidates are segmented corresponding to the liver lesion center candidates, and lesions are detected from the segmented lesion candidates using learning based verification.

Abstract translation: 公开了一种用于自动检测医学图像数据（例如3D CT图像）中的肝脏病变的方法和系统。 肝脏区域在3D图像中被分割。 在分段的肝脏区域中检测到肝脏病变中心候选者。 根据肝脏病变中心候选者对病变候选者进行分段，并且使用基于学习的验证从分段病变候选者中检测病变。

公开(公告)号：WO2014058638A1

公开(公告)日：2014-04-17

申请号：PCT/US2013/062559

申请日：2013-09-30

Applicant: SIEMENS CORPORATION ,  GUAN, Xuefei ,  ZHANG, Jingdan ,  ZHOU, Shaohua Kevin

Inventor： GUAN, Xuefei ,  ZHANG, Jingdan ,  ZHOU, Shaohua Kevin

IPC: G06F17/50 ,  G01N3/32

CPC classification number: G06F17/5009 ,  G06F2217/10 ,  G06F2217/76

Abstract: A method for predicting fatigue crack growth in materials includes providing a prior distribution obtained using response measures from one or more target components using a fatigue crack growth model as a constraint function, receiving new crack length measurements, providing a posterior distribution obtained using the new crack length measurements, and sampling the posterior distribution to obtain crack length measurement predictions.

Abstract translation: 用于预测材料中的疲劳裂纹扩展的方法包括使用疲劳裂纹扩展模型作为约束函数提供使用来自一个或多个目标部件的响应措施获得的先验分布，接收新的裂纹长度测量值，提供使用新裂纹获得的后验分布 长度测量，并对后验分布进行采样，以获得裂纹长度测量预测。

公开(公告)号：WO2012040410A3

公开(公告)日：2012-04-19

申请号：PCT/US2011052675

申请日：2011-09-22

Applicant: SIEMENS CORP ,  SIEMENS AG ,  LIU DAVID ,  WU DIJIA ,  ZHOU SHAOHUA KEVIN ,  COSTA MARIA JIMENA ,  SUEHLING MICHAEL ,  TIETJEN CHRISTIAN

Inventor： LIU DAVID ,  WU DIJIA ,  ZHOU SHAOHUA KEVIN ,  COSTA MARIA JIMENA ,  SUEHLING MICHAEL ,  TIETJEN CHRISTIAN

IPC: G06T7/00

CPC classification number: G06T7/0016 ,  G06T7/41 ,  G06T2207/10072 ,  G06T2207/20012 ,  G06T2207/20041 ,  G06T2207/20081 ,  G06T2207/20104 ,  G06T2207/30056

Abstract: A method and system for automatically detecting liver lesions in medical image data, such as 3D CT images, is disclosed. A liver region is segmented in a 3D image. Liver lesion center candidates are detected in the segmented liver region. Lesion candidates are segmented corresponding to the liver lesion center candidates, and lesions are detected from the segmented lesion candidates using learning based verification.

Abstract translation: 公开了一种用于自动检测医学图像数据中肝脏病变的方法和系统，如3D CT图像。 肝脏区域被分割成3D图像。 肝脏病变中心候选人在分段肝脏区域检测到。 病变候选者对应于肝脏病变中心候选物，并且使用基于学习的验证从分割的病变候选物检测病变。

公开(公告)号：WO2012040410A9

公开(公告)日：2012-03-29

申请号：PCT/US2011/052675

申请日：2011-09-22

Applicant: SIEMENS CORPORATION ,  SIEMENS AKTIENGESELLSCHAFT ,  LIU, David ,  WU, Dijia ,  ZHOU, Shaohua Kevin ,  COSTA, Maria Jimena ,  SUEHLING, Michael ,  TIETJEN, Christian

Inventor： LIU, David ,  WU, Dijia ,  ZHOU, Shaohua Kevin ,  COSTA, Maria Jimena ,  SUEHLING, Michael ,  TIETJEN, Christian

IPC: G06T7/00

Abstract: A method and system for automatically detecting liver lesions in medical image data, such as 3D CT images, is disclosed. A liver region is segmented in a 3D image. Liver lesion center candidates are detected in the segmented liver region. Lesion candidates are segmented corresponding to the liver lesion center candidates, and lesions are detected from the segmented lesion candidates using learning based verification.

公开(公告)号：WO2014052687A1

公开(公告)日：2014-04-03

申请号：PCT/US2013/062069

申请日：2013-09-27

Applicant: SIEMENS PRODUCT LIFECYCLE MANAGEMENT SOFTWARE INC. ,  WU, Dijia ,  BIRKBECK, Neil ,  SOFKA, Michal ,  LIU, Meizhu ,  ZHOU, Shaohua Kevin

Inventor： WU, Dijia ,  BIRKBECK, Neil ,  SOFKA, Michal ,  LIU, Meizhu ,  ZHOU, Shaohua Kevin

IPC: G06T7/00

CPC classification number: G06T7/0079 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/143 ,  G06T2207/10072 ,  G06T2207/20041 ,  G06T2207/20076

Abstract: A method for multiple bone segmentation for three-dimensional computed tomography comprises the acts: - receiving (20) computed tomography (CT) data representing first and second bones of a patient; - separately segmenting (22) the first and second bones; - refining (30) the segmenting of the first bone as a function of a first confidence map of the segmenting; - refining (30) the segmenting of the second bone as a function of a second confidence map of the segmenting; - adjusting (34) results of the segmenting of the first and second bones jointly as a function the first and second confidence maps; and - outputting (30) an image showing the first and second bones with the adjusted results of the segmenting.

Abstract translation: 用于三维计算机断层摄影的多骨分割方法包括以下动作： - 代表患者的第一和第二骨骼的接收（20）计算机断层摄影（CT）数据; - 分开（22）第一和第二骨骼; - 根据所述分割的第一置信度图来精炼（30）所述第一骨的分割; - 根据所述分割的第二置信图来精炼（30）所述第二骨的分割; - 调整（34）第一和第二骨骼的分割结果，作为第一和第二置信图的函数; 以及 - 输出（30）具有所述分割的调整结果的示出所述第一和第二骨骼的图像。

公开(公告)号：WO2013152085A1

公开(公告)日：2013-10-10

申请号：PCT/US2013/035090

申请日：2013-04-03

Applicant: SIEMENS CORPORATION ,  SIEMENS AKTIENGESELLSCHAFT ,  GUAN, Xuefei ,  ZHANG, Jingdan ,  KADAU, Kai ,  ZHOU, Shaohua, Kevin

Inventor： GUAN, Xuefei ,  ZHANG, Jingdan ,  KADAU, Kai ,  ZHOU, Shaohua, Kevin

IPC: G01N29/44 ,  G01N17/00

CPC classification number: G01N29/4418 ,  G01N17/00 ,  G01N29/4472 ,  G01N2203/0218 ,  G01N2291/0258

Abstract: A method for probabilistically predicting fatigue life in materials includes sampling (41) a random variable for an actual equivalent initial flaw size (EIFS), generating (42) random variables for parameters (InC, m) of a fatigue crack growth equation [Formula should be inserted here] from a multivariate distribution, and solving (43) the fatigue crack growth equation using these random variables. The reported EIFS data is obtained by ultrasonically scanning a target object, recording echo signals from the target object, and converting echo signal amplitudes to equivalent reflector sizes using previously recorded values from a scanned calibration block. The equivalent reflector sizes comprise the reported EIFS data.

Abstract translation: 一种用于概率预测材料疲劳寿命的方法包括对实际等效初始缺陷尺寸（EIFS）采样（41）随机变量，生成（42）疲劳裂纹扩展方程的参数随机变量（InC，m）[公式应该 并从多变量分布中求解（43）使用这些随机变量的疲劳裂纹扩展方程。 报告的EIFS数据是通过超声扫描目标物体，记录来自目标物体的回波信号，并使用先前记录的来自扫描校准块的值将回波信号幅度转换为等效反射镜尺寸而获得的。 等效的反射器尺寸包括报告的EIFS数据。

公开(公告)号：WO2013112522A1

公开(公告)日：2013-08-01

申请号：PCT/US2013/022652

申请日：2013-01-23

Applicant: SIEMENS CORPORATION ,  SIEMENS ENERGY, INC. ,  GUAN, Xuefei ,  ZHEN, Hui ,  ZHANG, Jingdan ,  ZHOU, Shaohua, Kevin ,  LEWIS, Ashley, L. ,  RADKE, Steve, H. ,  LEE, Chin-Sheng

Inventor： GUAN, Xuefei ,  ZHEN, Hui ,  ZHANG, Jingdan ,  ZHOU, Shaohua, Kevin ,  LEWIS, Ashley, L. ,  RADKE, Steve, H. ,  LEE, Chin-Sheng

IPC: G01N17/00

CPC classification number: G01N29/34 ,  G01N17/00 ,  G06F17/00

Abstract: A method of fatigue life prediction including: calculating a critical crack size of an object of interest; identifying a first flaw in ultrasound data of the object of interest; determining that the first flaw interacts with a second flaw, the first flaw is to be merged with the second flaw, or the first flaw is isolated; calculating an initial crack size based on the determination; and calculating an increase in the initial crack size due to fatigue and creep to determine a number of load cycles until the initial crack size reaches the critical crack size.

Abstract translation: 一种疲劳寿命预测方法，包括：计算感兴趣对象的临界裂纹尺寸; 识别感兴趣对象的超声数据中的第一缺陷; 确定第一缺陷与第二缺陷相互作用，第一缺陷将与第二缺陷合并，或者第一缺陷被隔离; 基于确定计算初始裂纹尺寸; 并计算由于疲劳和蠕变引起的初始裂纹尺寸的增加，以确定直到初始裂纹尺寸达到临界裂纹尺寸为止的负载循环次数。

公开(公告)号：WO2013112403A1

公开(公告)日：2013-08-01

申请号：PCT/US2013/022389

申请日：2013-01-21

Applicant: SIEMENS CORPORATION ,  SIEMENS ENERGY, INC. ,  XUEFEI, Guan ,  ZHANG, Jingdan ,  ZHOU, Shaohua Kevin ,  FISCHER, Mark W. ,  ABBASI, Waheed A. ,  KARSTETTER, Scott A. ,  ADAMS, Christopher John William

Inventor： XUEFEI, Guan ,  ZHANG, Jingdan ,  ZHOU, Shaohua Kevin ,  FISCHER, Mark W. ,  ABBASI, Waheed A. ,  KARSTETTER, Scott A. ,  ADAMS, Christopher John William

IPC: G01R31/34

CPC classification number: G01N27/904 ,  G01N27/20 ,  G01N27/82 ,  G01R31/1227 ,  G01R31/34 ,  G06F17/11

Abstract: In a general methodology for insulation defect identification in a generator core, a Chattock coil is used to measure magnetic potential difference between teeth. Physical knowledge and empirical knowledge is combined in a model to predict insulation damage location and severity. Measurements are taken at multiple excitation frequencies to solve for multiple characteristics of the defect.

Abstract translation: 在发电机铁心中用于绝缘缺陷识别的一般方法中，使用Chattock线圈来测量齿之间的磁势差。 物理知识和经验知识结合在一个模型中，以预测绝缘损伤位置和严重程度。 在多个激发频率下进行测量以解决缺陷的多个特征。