Sign Detection System and Sign Detection Method

Patent metadata

Field	Value
Publication number	US-2026072425-A1
Application number	US-202319101918-A
Country	US
Kind code	A1
Filing date	Aug 24, 2023
Priority date	Aug 31, 2022
Publication date	Mar 12, 2026
Grant date	—

Abstract

In order to achieve high accuracy of detecting a sign of cooling performance deterioration, a sign detection system includes: a pre-processing unit acquiring operation data of a time series about a cooling target apparatus and extracting features from the operation data, the cooling target apparatus including a temperature rise source and a cooling unit cooling the temperature rise source, and a sign detection unit diagnosing cooling performance of the cooling unit, based on an output obtained by inputting the features extracted from the operation data for diagnosis to a sign detection model, the sign detection model being constructed using training data generated based on the features extracted from the operation data for training and a label indicating a state of the cooling performance. The sign detection model is constructed using the training data generated based on the features extracted from the operation data including the operation statuses corresponding to the being operating and the being on standby. When diagnosing the cooling performance, the sign detection unit inputs the features extracted from the operation data including only the operation statuses corresponding to the being operating, to the sign detection model.

First claim

1 . A sign detection system comprising:
a pre-processing unit acquiring operation data of a time series about a cooling target apparatus and extracting features from the operation data, the cooling target apparatus comprising a temperature rise source and a cooling unit cooling the temperature rise source with a cooling medium; and a sign detection unit diagnosing cooling performance of the cooling unit, based on an output obtained by inputting the features extracted from the operation data for diagnosis by the pre-processing unit to a sign detection model, the sign detection model being constructed using training data generated based on the features extracted from the operation data for training by the pre-processing unit and a label indicating a state of the cooling performance; wherein the operation data includes operation statuses each of which indicates the cooling target apparatus being operating or being on standby; the sign detection model is constructed using the training data generated based on the features extracted from the operation data including the operation statuses corresponding to the being operating and the being on standby; and when diagnosing the cooling performance, the sign detection unit inputs the features extracted from the operation data including only the operation statuses corresponding to the being operating, to the sign detection model.

2 . The sign detection system according to claim 1 , wherein
the label indicating the state of the cooling performance of the cooling unit is a label indicating normality or abnormality.

3 . The sign detection system according to claim 1 , wherein
the label indicating the state of the cooling performance of the cooling unit is a label indicating normality or a corresponding abnormality factor among a plurality of abnormality factors.

4 . The sign detection system according to claim 1 , wherein
the features include statistical features that are statistics of the operation data at each hour included in a first statistical period before each hour of the time series.

5 . The sign detection system according to claim 1 , wherein
the sign detection model is constructed using the training data generated based on the features extracted from the operation data including the operation statuses corresponding to the being operating and the being on standby, after the operation statuses being excluded from the operation data; and when diagnosing the cooling performance, the sign detection unit inputs the features extracted from the operation data including only the operation statuses corresponding to the being operating, to the sign detection model after excluding the operation statuses from the operation data.

6 . The sign detection system according to claim 1 , wherein
the sign detection model is constructed using the training data generated based on the features extracted from the operation data including the operation statuses corresponding to the being operating and the being on standby, with the operation statuses being included; and when diagnosing the cooling performance, the sign detection unit inputs the features extracted from, instead of the operation data including only the operation statuses corresponding to the being operating, the operation data including the operation statuses corresponding to the being operating and the being on standby, to the sign detection model, with the operation statuses being included.

7 . The sign detection system according to claim 4 , wherein
the features include descriptive features that are statistics of the operation data at each hour included in each of a plurality of sections obtained by dividing a second statistical period before each hour of the time series, the statistics being calculated for each of the sections.

8 . The sign detection system according to claim 7 , wherein
the sign detection model is constructed using the training data generated based on the features extracted from the operation data including the operation statuses corresponding to the being operating and the being on standby, after the operation statuses being excluded from the operation data; and when diagnosing the cooling performance, the sign detection unit inputs the features extracted from, instead of the operation data including only the operation statuses corresponding to the being operating, the operation data including the operation statuses corresponding to the being operating and the being on standby, to the sign detection model after excluding the operation statuses from the operation data.

9 . The sign detection system according to claim 7 , wherein
the second statistical period is longer than the first statistical period.

10 . The sign detection system according to claim 7 , wherein
the plurality of sections are sections obtained by separating the second statistical period at equal intervals.

11 . The sign detection system according to claim 7 , wherein
the plurality of sections are sections obtained by separating the second statistical period such that intervals are determined according to time zones in which the cooling target apparatus is operating.

12 . The sign detection system according to claim 1 , comprising a construction unit, the construction unit constructing the sign detection model using the training data.

13 . A sign detection method executed by a sign detection system, the sign detection method comprising:
a pre-processing step of acquiring operation data of a time series about a cooling target apparatus and extracting features from the operation data, the cooling target apparatus comprising a temperature rise source and a cooling unit cooling the temperature rise source with a cooling medium; and a sign detection step of diagnosing cooling performance of the cooling unit, based on an output obtained by inputting the features extracted from the operation data for diagnosis by the pre-processing step to a sign detection model, the sign detection model being constructed using training data generated based on the features extracted from the operation data for training by the pre-processing step and a label indicating a state of the cooling performance; wherein the operation data includes operation statuses each of which indicates the cooling target apparatus being operating or being on standby; the sign detection model is constructed using the training data generated based on the features extracted from the operation data including the operation statuses corresponding to the being operating and the being on standby; and at the sign detection step, when the cooling performance is diagnosed, the features extracted from the operation data including only the operation statuses corresponding to the being operating are inputted to the sign detection model.

14 . The sign detection method according to claim 13 , wherein
the features include statistical features that are statistics of the operation data at each hour included in a first statistical period before each hour of the time series.

15 . The sign detection method according to claim 13 , wherein
the sign detection model is constructed using the training data generated based on the features extracted from the operation data including the operation statuses corresponding to the being operating and the being on standby, after the operation statuses being excluded from the operation data; and at the sign detection step, when the cooling performance is diagnosed, the features extracted from the operation data including only the operation status corresponding to the being operating are inputted to the sign detection model after t

Assignees

• Hitachi Industry Equipment Systems Co Ltd

Inventors

• Nojiri Tohru
• Takano Masahiko
• Nakagawa Yuusuke
• Ojima Masayoshi

Classifications

• G05B23/024

  Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks · CPC title

• G05B23/02 Primary

  Electric testing or monitoring · CPC title

• G06F11/3058

  Monitoring arrangements for monitoring environmental properties or parameters of the computing system or of the computing system component, e.g. monitoring of power, currents, temperature, humidity, position, vibrations (thermal management in cooling arrangements of a computing system G06F1/206) · CPC title