公开(公告)号：US20180075235A1

公开(公告)日：2018-03-15

申请号：US15495213

申请日：2017-04-24

Applicant: Hitachi, Ltd.

Inventor： Yoshiyuki TAJIMA ,  Susumu SERITA ,  Masami YAMASAKI

IPC: G06F21/55

CPC classification number: G06F21/554 ,  G06F2221/034

Abstract: An abnormality detection system is configured to (a) convert, based on a prescribed rule, a time-sequential event included in a log output by a monitoring target system into a symbolized event; (b) learn, based on a normal-time log symbolized in (a), a symbolized event sequence, which appears in a same pattern, as a frequently-appearing pattern; and (c) detect an occurrence or a nonoccurrence of an abnormality, based on whether not the frequently-appearing pattern is occurring in a monitoring-time log symbolized in (a).

公开(公告)号：US20230102000A1

公开(公告)日：2023-03-30

申请号：US17793803

申请日：2021-01-15

Applicant: Hitachi, Ltd.

Inventor： Shinichi TSUNO ,  Yoshiyuki TAJIMA

IPC: G06N5/022

Abstract: The time-series pattern explanatory information generating apparatus includes a prediction model learning unit configured to learn time-series data acquired from a monitored system in a neural network to construct a prediction model. A candidate sequence pattern generating unit is configured to use the prediction model to extract candidate sequence patterns included in time-series data and indicating a characteristic change. A sequence pattern generating unit calculates a dissimilarity among the candidate sequence patterns to classify the candidate sequence patterns, and output a representative candidate sequence pattern included in each classification as a sequence pattern of time-series data; and a time-series data analyzing unit calculates a feature from an arbitrary sequence pattern extracted from time-series data obtained from the monitored system, draws a comparison with a change detection model storing a feature, in advance, from a normal-time sequence pattern, and outputs an analysis result as to whether the monitored system is normal.

公开(公告)号：US20180246958A1

公开(公告)日：2018-08-30

申请号：US15756321

申请日：2016-03-28

Applicant: HITACHI, LTD.

Inventor： Susumu SERITA ,  Yoshiyuki TAJIMA ,  Tomoaki AKITOMI ,  Fumiya KUDO

IPC: G06F17/30

CPC classification number: G06F16/353 ,  G06F16/00

Abstract: Provided is a technique for extracting a factor (event pattern) that has an influence on an objective index (objective variable). A data analysis device according to the present disclosure performs: a process of generating, with respect to explanatory variable data included in data to be analyzed, a time-series pattern in a predetermined range; a process of calculating a correlation value between the time-series pattern and at least one item of objective variable data included in the data to be analyzed; and a process of outputting, together with the correlation value, the time-series pattern corresponding to the correlation value as an analysis result.

公开(公告)号：US20190312936A1

公开(公告)日：2019-10-10

申请号：US16302129

申请日：2016-06-03

Applicant: HITACHI, LTD.

Inventor： Tomoyuki YAMAGATA ,  Takahiro OHIRA ,  Yuichi IGARASHI ,  Yoshiyuki TAJIMA

IPC: H04L29/08 ,  G01D4/00

Abstract: An on-site system includes a disclosure-condition-table storage unit and a disclosure-condition-table creation unit. The disclosure-condition-table storage unit stores a disclosure condition table for management of a relationship between a purpose of a service and a data characteristic of on-site data, as a disclosure condition for disclosing the on-site data to a service device that provides the service. The disclosure-condition-table creation unit creates the disclosure condition table in which a purpose of a service included in descriptive information of the service is associated with a data characteristic included in descriptive information of the on-site data, and stores the disclosure condition table in the disclosure-condition-table storage unit.

公开(公告)号：US20180275642A1

公开(公告)日：2018-09-27

申请号：US15907844

申请日：2018-02-28

Applicant: HITACHI, LTD.

Inventor： Yoshiyuki TAJIMA ,  Yoshinori MOCHIZUKI

IPC: G05B23/02 ,  G06Q50/10 ,  G01D3/08

CPC classification number: G05B23/024 ,  G01D3/08 ,  G05B23/0254 ,  G06Q50/10

Abstract: An objective is to set an anomaly detection threshold easily and accurately. An anomaly detection system 1 includes an arithmetic device 1H101 that executes processing of learning a predictive model that predicts a behavior of a monitoring target device based on operational data on the device, processing of adjusting an anomaly score such that the anomaly score for operational data under normal operation falls within a predetermined range, the anomaly score being based on a deviation of the operational data acquired from the monitoring target device from a prediction result obtained by the predictive model, processing of detecting an anomaly or a sign of an anomaly based on the adjusted anomaly score, and processing of displaying information on at least one of the anomaly score and a result of the detection on an output device.

公开(公告)号：US20230144809A1

公开(公告)日：2023-05-11

申请号：US17919757

申请日：2021-05-21

Applicant: HITACHI, LTD.

Inventor： Yoshiyuki TAJIMA ,  Daisuke INABA ,  Yoshinori MOCHIZUKI

IPC: G06F18/22 ,  G06F18/21 ,  G06N20/00

CPC classification number: G06F18/22 ,  G06F18/217 ,  G06N20/00

Abstract: A system calculates an inter-distribution distance between target data and base data for each of one or more second periods in an entire period between an end time of a first period and a relearning timing of a learning model. For each second period, the target data is data for the second period in the entire data that is data for the entire period. The base data is data for the first period and is data related to creation of the learning model. The system specifies, as a variation point, a time in accordance with the second period during which the calculated inter-distribution distance is greater than or equal to a threshold. The system determines and outputs one or more training data candidates from a part or all of the entire data based on the one or more variation points for relearning of the learning model.

公开(公告)号：US20220058485A1

公开(公告)日：2022-02-24

申请号：US17414705

申请日：2019-12-13

Applicant: Hitachi, Ltd.

Inventor： Yoshiyuki TAJIMA ,  Yohei KONO

IPC: G06N3/08

Abstract: A data generation device generates a data set and includes: a perturbation generation unit that generates a perturbation set for deforming each element based on at least one of an input of each element of a training data set and information on the training data set; a pseudo data synthesis unit that generates a new pseudo data set different from the training data set from the training data set and the perturbation set; an evaluation unit that calculates a distributional distance of the training data set and the pseudo data set or an estimated amount of the distributional distance and a magnitude of perturbation of the pseudo data with respect to the training data obtained from the perturbation set; and a parameter update unit that updates a parameter used by the perturbation generation unit to generate the perturbation set so that the distributional distance of the training data set and the pseudo data set is close to each other and the magnitude or expected value of the perturbation becomes a predetermined target value.

公开(公告)号：US20210224599A1

公开(公告)日：2021-07-22

申请号：US17256070

申请日：2019-05-29

Applicant: Hitachi, Ltd.

Inventor： Yoshiyuki TAJIMA ,  Kazuya MONDEN

IPC: G06K9/62 ,  G05B23/02

Abstract: There are provided a device that collects operation data from equipment, and an information processing apparatus that detects an anomaly or an omen of an anomaly of the equipment on the basis of anomaly detection models constructed from the operation data, the information processing apparatus including means for collecting the operation data, means for learning anomaly detection models from the operation data, and means for calculating an anomaly score of respective operation data from the operation data and the anomaly detection models, the means for learning an anomaly detection model in which a dispersion of elements is small among the anomaly detection models. Thus, in an anomaly detection system, when the operation state of equipment is monitored, even if data for performing division of operation states cannot be obtained or even if division cannot be performed correctly, misdetection of an anomaly such as a malfunction or a failure or an omen of an anomaly can be decreased and the state of the system can be evaluated correctly.

公开(公告)号：US20200293018A1

公开(公告)日：2020-09-17

申请号：US16807707

申请日：2020-03-03

Applicant: HITACHI, LTD.

Inventor： Shinichi TSUNOO ,  Yoshiyuki TAJIMA ,  Daisuke YAMAZAKI

IPC: G05B19/406

Abstract: A time series data monitoring system includes: a series pattern candidate generating unit that generates series pattern candidates included in time series data obtained from a monitored system using the time series data and a prediction model of the time series data; and a series pattern generating unit that classifies the series pattern candidates generated by the series pattern candidate generating unit and outputs, as a series pattern of the time series data, a candidate satisfying a predetermined condition among the classified series pattern candidates.