IP Library › Granted Patent US 12,560,486
Granted Patent B2
US 12,560,486 · App. 18/176,436 · Granted Feb 24, 2026

Devices and methods for temperature measurement

Inventors: Xiaonan Wang (HangZhou, CN); Lingrui Kong (Hangzhou, CN); Fei Xue (Hangzhou, CN)
Assignee: ZHEJIANG PIXFRA TECHNOLOGY CO., LTD.
G01J5/80G01J5/0859G06N3/09G06V40/165G01J2005/0077
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Quick Facts
Patent No.
US 12,560,486
App. No.
18/176,436
Granted
Feb 24, 2026
Kind
B2
Abstract

A device for temperature measurement, includes a blackbody configured to radiate a specified temperature, an infrared thermal imaging camera configured to measure a temperature of a target surface of the blackbody and a temperature of an object and at least one processor configured to calibrate the temperature of the object based on the specified temperature and the temperature of the target surface.

Claims (61)

1 . A device for temperature measurement, comprising:

a blackbody configured to provide a specified temperature;

an infrared thermal imaging camera configured to measure a temperature of a target surface of the blackbody and a temperature of an object; and

at least one processor configured to calibrate the temperature of the object based on the specified temperature and the temperature of the target surface according to operations including:

obtaining a relationship between a reference temperature and a gray value difference;

determining a temperature difference between the specified temperature and the temperature of the target surface;

determining a calibration value based on the gray value difference and the temperature difference; and

calibrating the temperature of the object based on the calibration value.

2 . The device of claim 1 , wherein the at least one processor is further configured to:

determine the gray value difference corresponding to a standard blackbody at the reference temperature.

3 . The device of claim 2 , wherein the at least one processor is further configured to:

obtain the relationship using a calibration model, wherein the calibration model includes a trained machine learning model.

4 . The device of claim 3 , wherein the calibration model is obtained according to operations including:

obtaining a plurality of training samples, wherein each of at least a portion of the training samples includes a sample temperature and a corresponding label, wherein the label represents a gray value corresponding to the standard blackbody at the sample temperature;

training a calibration model based on the plurality of the training samples.

5 . The device of claim 1 , wherein the at least one processor is further configured to:

calibrate the temperature of the object in real-time.

6 . The device of claim 1 , wherein the at least one processor is further configured to:

calibrate the temperature of the object based on a distance between the blackbody and the infrared thermal imaging camera that does not satisfy a condition.

7 . The device of claim 1 , wherein the at least one processor is further configured to:

calibrate the temperature of the object in response to determining that the temperature of the object is within a temperature range.

8 . The device of claim 1 , wherein the at least one processor is further configured to:

obtain images of at least one object;

perform image recognition by processing the images and obtaining an image recognition result, wherein the image recognition result represents a distance between the object and the device for temperature measurement;

calibrate the temperature of the object closest to the device for temperature measurement based on the image recognition result.

9 . The device of claim 1 , wherein the blackbody is movable, and the blackbody is moved according to a position of the object.

10 . A method for temperature measurement, implemented on a computing device having at least one processor and at least one storage device, the method comprising:

obtaining a specified temperature provided by a blackbody;

obtaining a temperature of a target surface of the blackbody and a temperature of an object detected by a device for temperature measurement; and

calibrating the temperature of the object based on the specified temperature and the temperature of the target surface according to operations including:

obtaining a relationship between a reference temperature and a gray value difference;

determining a temperature difference between the specified temperature and the temperature of the target surface;

determining a calibration value based on the gray value difference and the temperature difference; and

calibrating the temperature of the object based on the calibration value.

11 . The method of claim 10 , further comprising:

determining the gray value difference corresponding to a standard blackbody at the reference temperature.

12 . The method of claim 11 , further comprising:

obtaining the relationship using a calibration model, wherein the calibration model includes a trained machine learning model.

13 . The method of claim 12 , wherein the calibration model is obtained according to operations including:

obtaining a plurality of training samples, wherein each of at least a portion of the training samples includes a sample temperature and a corresponding label, wherein the label represents a gray value corresponding to the standard blackbody at the sample temperature;

training a calibration model based on the plurality of the training samples.

14 . The method of claim 10 , further comprising:

calibrating the temperature of the object in real-time.

15 . The method of claim 10 , further comprising:

calibrating the temperature of the object based on a distance between the blackbody and the infrared thermal imaging camera that does not-satisfies satisfy a condition.

16 . The method of claim 10 , further comprising:

calibrating the temperature of the object in response to determining that the temperature of the object is within a temperature range.

17 . The method of claim 10 , wherein further comprising:

obtaining images of at least one object;

performing image recognition by processing the images and obtaining an image recognition result, wherein the image recognition result represents a distance between the object and the device for temperature measurement;

calibrating the temperature of the object closest to the device for temperature measurement based on the image recognition result.

18 . A system for temperature measurement, comprising:

at least one storage device including a set of instructions; and

at least one processor configured to communicate with the at least one storage device, wherein when executing the set of instructions, the at least one processor is configured to direct the system to perform operations including:

obtaining a specified temperature provided by a blackbody;

obtaining a temperature of a target surface of the blackbody and a temperature of an object detected by a device for temperature measurement; and

calibrating the temperature of the object based on the specified temperature and the temperature of the target surface according to operations including:

obtaining a relationship between a reference temperature and a gray value difference;

determining a temperature difference between the specified temperature and the temperature of the target surface;

determining a calibration value based on the gray value difference and the temperature difference; and

calibrating the temperature of the object based on the calibration value.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 24, 2023
From: ZHEJIANG DAHUA TECHNOLOGY CO., LTD.
To: ZHEJIANG PIXFRA TECHNOLOGY CO., LTD.
Reel/Frame 065330/0665 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 20, 2023
From: WANG, XIAONAN; KONG, LINGRUI; XUE, FEI
To: ZHEJIANG DAHUA TECHNOLOGY CO., LTD.
Reel/Frame 065292/0906 →
Priority Claims (1)
CN 202011445541.7 · Dec 9, 2020 · national
Continuity (2)
Continuation PCTCN2021128370 · Nov 3, 2021
Related Publication 20230204429A1 · Jun 29, 2023
References Cited (29)
US 6112423A · Sheehan · 2000 [cited by examiner]
US 20130306851A1 · Le Noc et al. · 2013 [cited by examiner]
US 20170284869A1 · Dubbs et al. · 2017 [cited by examiner]
US 20210285823A1 · Gao · 2021 [cited by applicant]
US 20220227059A1 · Borras Camarasa et al. · 2022 [cited by examiner]
US 20230075679A1 · Zhang et al. · 2023 [cited by examiner]
CN 1821732A · 2006 [cited by applicant]
CN 103424192B · 2015 [cited by applicant]
CN 107741276A · 2018 [cited by applicant]
CN 109870239A · 2018 [cited by applicant]
CN 207515910U · 2018 [cited by applicant]
CN 110108364A · 2018 [cited by applicant]
CN 108562363A · 2018 [cited by applicant]
CN 110332995A · 2019 [cited by applicant]
CN 110411570A · 2019 [cited by applicant]
CN 110726475A · 2020 [cited by applicant]
CN 110823381A · 2020 [cited by applicant]
CN 211452611U · 2020 [cited by applicant]
CN 211477416U · 2020 [cited by applicant]
CN 111751006A · 2020 [cited by applicant]
CN 112033545A · 2020 [cited by applicant]
CN 112161711A · 2021 [cited by applicant]
JP 2001349786A · 2001 [cited by applicant]
WO 2021262281A1 · 2021 [cited by applicant]
WO 2022121562A1 · 2022 [cited by applicant]
International Search Report in PCT/CN2021/128370 mailed on Jan. 12, 2022, 5 pages. [cited by applicant]
Written Opinion in PCT/CN2021/128370 mailed on Jan. 12, 2022, 7 pages. [cited by applicant]
First Office Action in Chinese Application No. 202011445541.7 malled on Dec. 17, 2021, 19 pages. [cited by applicant]
The Extended European Search Report in European Application No. 21902269.6 mailed on Dec. 5, 2023, 9 pages. [cited by applicant]