公开(公告)号：WO2022006301A1

公开(公告)日：2022-01-06

申请号：PCT/US2021/039937

申请日：2021-06-30

Applicant: KIM, Charles

Inventor： KIM, Charles

IPC: G01R31/08 ,  G01R31/14 ,  G01R31/52 ,  G01R31/50 ,  G01R31/083 ,  G01R31/088 ,  G01R31/58 ,  G06F17/17

Abstract: A method, computer program, and computer system is provided for fault detection in an electrical network. An inductance between a reference point and a fault is determined at a first time based on measuring a fault current. A resistance between the reference point and the fault may be determined at a second time based on measuring a differential of the fault current as zero. A location of the fault may be identified based on the inductance and the resistance.

公开(公告)号：WO2021179957A1

公开(公告)日：2021-09-16

申请号：PCT/CN2021/078674

申请日：2021-03-02

Applicant: 中国标准化研究院

Inventor： 张运红 ,  赵朝义

IPC: G06F17/17 ,  G06Q10/06 ,  G06Q30/02

Abstract: 本发明涉及产品使用质量或性能判定技术领域，特别涉及产品使用质量或性能的判定方法及设备。该判定方法包括：根据使用前、使用后测试数据计算体验因子效应量；对使用前、使用后测试数据方差分析或t检验，获得体验因子在规定置信水平的显著性水平p值；根据规定的置信水平和体验因子效应量，将体验因子显著性水平p值与显著性水平α值比较得出差异显著性结果。对使用前、后测试数据方差分析或t检验，求体验因子差异变化的显著性水平p值，结合体验因子效应量，在规定置信水平判定其是否显著，由此判断产品使用质量或性能的影响情况，将该影响效果与常规的标准判定结果相结合，准确判定产品是否合格，解决单一标准判定的局限性以及测试不准的问题。

公开(公告)号：WO2021144390A1

公开(公告)日：2021-07-22

申请号：PCT/EP2021/050741

申请日：2021-01-14

Applicant: ABB POWER GRIDS SWITZERLAND AG

Inventor： FENG, Xiaoming

IPC: H02J13/00 ,  G01R19/25 ,  G01R21/133 ,  G01R19/2513 ,  G06F17/17 ,  G06Q10/04 ,  H02J13/00002 ,  H02J13/00006 ,  H02J13/00034 ,  H02J2203/10 ,  H02J2203/20 ,  H02J2213/00 ,  H02J2310/58 ,  H02J3/003 ,  H02J3/004

Abstract: Systems, methods, techniques and apparatuses of state estimation are disclosed. One exemplary embodiment is a method comprising determining, with a state estimator, a state estimate based on power grid data corresponding to characteristics of a power grid; calculating, with the state estimator, a gradient based on the state estimate; calculating, with the state estimator, a first gain matrix based on a Gauss-Newton method and a second gain matrix based on Newton's method; selecting, with the state estimator, either the first gain matrix or the second gain matrix for calculating a correction of the state estimate; calculating, with the state estimator, the correction of the state estimate; updating, with the state estimator, the state estimate; and determining, with the state estimator, whether the updated state estimate has converged.

公开(公告)号：WO2021070317A1

公开(公告)日：2021-04-15

申请号：PCT/JP2019/039989

申请日：2019-10-10

Applicant: 日本電信電話株式会社

Inventor： 濱田　浩気

IPC: G06F17/17 ,  G09C1/00

Abstract: 近似関数計算装置は、関数gb(x)を求めるテイラー展開部と、区間[x0,b]における関数gb(x)による関数f(x)の近似の誤差の上界を求める第一誤差上界計算部と、区間[x0,b]における関数gb(x)による関数f(x)の近似の誤差の上界がε以下となる最大のbである展開位置b'を求める展開位置計算部と、区間[b',x2]における関数gb'(x)による関数f(x)の近似の誤差の上界を求める第二誤差上界計算部と、区間[b',x2]における関数gb'による関数f(x)の近似の誤差の上界がε以下となる最大のx2である右端位置x2'を求める右端位置計算部と、区間[x0,x2']と、関数gb'(x)についての情報とを出力する出力部と、区間[x2',x1]を区間Dとして各部の処理を繰り返す制御部と、を備えている。

公开(公告)号：WO2021059331A1

公开(公告)日：2021-04-01

申请号：PCT/JP2019/037289

申请日：2019-09-24

Applicant: 三菱電機株式会社

Inventor： 網嶋　武 ,  高橋　龍平

IPC: G06F17/17 ,  G01S13/66 ,  G06F17/18

Abstract: 平滑フィルタ装置（１）は、トラッキングインデックスを用いて、複数の観測方法にそれぞれ対応する平滑誤差標準偏差が同じ値となるように、各観測時刻における駆動雑音標準偏差を算出し、算出した駆動雑音標準偏差を用いて、観測値の時系列データの平滑処理を行う。

公开(公告)号：WO2021039545A1

公开(公告)日：2021-03-04

申请号：PCT/JP2020/031316

申请日：2020-08-19

Applicant: 日本電信電話株式会社

Inventor： 橋本　悠香 ,  松尾　洋一 ,  石川　勲 ,  池田　正弘 ,  河原　吉伸

IPC: G06N7/00 ,  G06N7/08 ,  G06F17/17

Abstract: 異常検知装置において、観測データに基づいて、当該観測データを生成する数学モデルを表現するＲＫＨＳ上のPerron-Frobenius作用素の近似を作成する近似部と、前記Perron-Frobenius作用素の近似と、時刻ｔの観測データを用いて、時刻ｔ＋１におけるデータを予測し、予測したデータと、時刻ｔ＋１の観測データとの乖離に基づいて、時刻ｔ＋１の観測データが異常か否かを判断する検知部とを備える。

公开(公告)号：WO2020169961A1

公开(公告)日：2020-08-27

申请号：PCT/GB2020/050384

申请日：2020-02-18

Applicant: IRUIZ CONTRACTING LIMITED

Inventor： RUIZ, Ignacio ,  ZERON, Mariano

IPC: G06N3/08 ,  G06N3/04 ,  G06F17/17 ,  G06Q30/02

Abstract: The invention provides a non-homogeneous machine learning architecture for approximating an overall function as a composition of at least a first approximation function and a second approximation function. The non-homogeneous machine learning architecture comprises a neural network architecture for providing the first approximation function, the neural network architecture being configured to receive a plurality of input values for the overall function as an input to the first approximation function, and to apply the first approximation function to the received input values to generate a plurality of neural network output values. The non-homogeneous machine learning architecture comprises an interpolation architecture for providing the second approximation function, the interpolation architecture being configured to receive the plurality of neural network output values as an input to the second approximation function, and to apply the second approximation function to generate at least one interpolation output value to be used in approximating at least one output value of the overall function.

公开(公告)号：WO2020096727A1

公开(公告)日：2020-05-14

申请号：PCT/US2019/055585

申请日：2019-10-10

Applicant: THERMWOOD CORPORATION

Inventor： SUSNJARA, Kenneth, J. ,  VAAL, Scott, G. ,  VOTE, Nicolas, C.

IPC: B29C64/10 ,  B33Y10/00 ,  B33Y50/02 ,  G06F7/50 ,  G06F17/17 ,  G06T17/00

Abstract: A method of forming a part using additive manufacturing may include receiving, at a computer numeric controlled (CNC) machine, a computer aided design (CAD) model of the part. The method may further include dividing the CAD model into plurality of sections. The method may further include slicing each of the plurality of sections into a plurality of layers. Each section may include a distinct set of print parameters. The method may further include depositing a flowable material onto a worktable according the set of print parameters for each section of the of the plurality of sections to manufacture the part.

公开(公告)号：WO2019135988A1

公开(公告)日：2019-07-11

申请号：PCT/US2018/067846

申请日：2018-12-28

Applicant: GLYSENS INCORPORATED

Inventor： GUPTA, Piyush ,  LUCISANO, Joseph

IPC: A61B5/145 ,  G06F17/10 ,  G06F17/15 ,  G06F17/17

Abstract: Apparatus and methods for response modeling and correction of signals associated with a parameter sensor. In one exemplary embodiment, the parameter sensor is configured to measure a physiologic analyte of a living being (e.g., blood glucose), and the apparatus and methods employ a mathematical transformation of two or more sensing elements (electrodes) of the sensor in order to compensate for temporal response differences or "mismatch." This compensation enables the calculated blood analyte level, which results from processing of the signals of the two or more sensing electrodes, to be more accurate than calculations made without such compensation. In one variant, the parameter signals are generated, and compensation processing conducted, autonomously via a common implanted sensor platform.

公开(公告)号：WO2018068654A1

公开(公告)日：2018-04-19

申请号：PCT/CN2017/103988

申请日：2017-09-28

Applicant: 深圳云天励飞技术有限公司

Inventor： 王冬陆 ,  田第鸿

IPC: G06F17/17

Abstract: 一种场景模型动态估计方法及装置，所述方法包括：(a)建立用于描述动态变化的场景的场景模型（S10）；(b)获取样本特征数据（S11）；(c)根据所述样本特征数据，对所述场景模型中初始时刻的模型参数初始估计，计算初始时刻的模型参数（S12）；(d)将所述初始时刻的模型参数确定为当前时刻的模型参数（S13）；(e)获取所述当前时刻的下一时刻的观测特征数据（S14）；(f)根据所述当前时刻的模型参数及所述下一时刻的观测特征数据，计算所述下一时刻的模型参数（S15）；(g)将所述下一时刻确定为当前时刻（S16）；(h)利用迭代方法执行(e)(f)(g)，直至计算完所述场景模型中每个时刻的模型参数（S17）。该方法能提高运算速度，使结果更稳定，平滑。