CN113899973A - Power generation equipment fault diagnosis method based on infrared thermal imaging and visible light image - Google Patents

Power generation equipment fault diagnosis method based on infrared thermal imaging and visible light image Download PDF

Info

Publication number
CN113899973A
CN113899973A CN202111183379.0A CN202111183379A CN113899973A CN 113899973 A CN113899973 A CN 113899973A CN 202111183379 A CN202111183379 A CN 202111183379A CN 113899973 A CN113899973 A CN 113899973A
Authority
CN
China
Prior art keywords
value
temperature
setting
timer1
fault
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202111183379.0A
Other languages
Chinese (zh)
Inventor
杨洋
钟希望
张鹏程
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sichuan Huaneng Jialingjiang Hydropower Co Ltd
Original Assignee
Sichuan Huaneng Jialingjiang Hydropower Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sichuan Huaneng Jialingjiang Hydropower Co Ltd filed Critical Sichuan Huaneng Jialingjiang Hydropower Co Ltd
Priority to CN202111183379.0A priority Critical patent/CN113899973A/en
Publication of CN113899973A publication Critical patent/CN113899973A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01JMEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00Radiation pyrometry, e.g. infrared or optical thermometry
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01JMEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J2005/0077Imaging

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Radiation Pyrometers (AREA)

Abstract

The invention discloses a power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images, which comprises the steps of obtaining infrared thermal imaging data and visible light image data of inspection equipment; judging whether the infrared thermal imaging data has pixel points exceeding a standard temperature value; judging whether the number of all pixel points exceeding the standard temperature value is greater than the minimum analysis pixel value; analyzing the visible light image to obtain a contour reference function; calculating a contour difference factor C according to the contour reference function; judging whether C is greater than or equal to a threshold value Mmin in the set contour factor and is less than or equal to a threshold value Mmax in the set contour factor; comparing and judging to obtain multiple fault grades; data analysis is carried out through the infrared thermograph and the visible light image, front end and rear end processing is carried out through monitoring and detection, intelligent identification and intelligent fault diagnosis are carried out on the equipment, and the data processing efficiency is improved while intellectualization is achieved.

Description

Power generation equipment fault diagnosis method based on infrared thermal imaging and visible light image
Technical Field
The invention relates to the technical field of power generation equipment fault diagnosis, in particular to a power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images.
Background
The power equipment mainly comprises power generation equipment and power supply equipment, and the planned maintenance system adopted by most power equipment in a power system has serious defects, such as frequent temporary maintenance, insufficient maintenance or excessive maintenance, blind maintenance and the like, so that the equipment maintenance cost is huge in all countries in the world every year. How to rationally arrange the maintenance of power equipment, save the maintenance expense, reduce the maintenance cost, guarantee simultaneously that the system has higher reliability, be an important subject to system operation personnel. The thermal infrared imager is used as a non-contact temperature measuring tool and is increasingly applied to live-line maintenance of power generation equipment. However, in the current application, the problem is basically found by manual inspection by experienced workers, and when some parts are monitored by an online thermal infrared imager, only the temperature can be alarmed, and then manual observation is needed to confirm whether the fault exists.
Therefore, it is necessary to develop a power generation equipment fault diagnosis method based on infrared thermal imaging and visible light imaging to solve the above problems.
Disclosure of Invention
The invention aims to solve the problems and designs a power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images.
The invention realizes the purpose through the following technical scheme:
the power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images comprises the following steps:
s1, acquiring infrared thermal imaging data and visible light image data of the power generation equipment during inspection; proceeding to step S2;
s2, judging whether the infrared thermal imaging data has pixel points exceeding a standard temperature value; if yes, the method goes to step S3, otherwise, the method goes to step S1 to continuously inspect the next device;
s3, judging whether the number of all the pixel points exceeding the standard temperature value is larger than the minimum analysis pixel value; if yes, the step S4 is proceeded, otherwise, the step S1 is proceeded;
s4, analyzing the visible light image to obtain a contour reference function; proceeding to step S5;
s5, calculating a contour difference factor C according to the contour reference function; proceeding to step S6;
s6, judging whether C is larger than or equal to a threshold value Mmin in the set contour factor and smaller than or equal to a threshold value Mmax in the set contour factor; if yes, determining that the device matching is successful, and entering step S7; if not, determining that the equipment matching fails, sending an equipment matching error message to the server, automatically recording and alarming by the server background, and then jumping to the step S1;
s7, setting a temperature threshold value W1, a temperature difference threshold value V2, a temperature rise threshold value A3, a temperature rise recording unit time value U3, a temperature rise time threshold value N3 and a delay time value T according to power generation equipment needing to be diagnosed, and judging to obtain multiple fault levels after acquiring temperature and time period data of the power generation equipment through an infrared thermal imager and comparing the data with the set temperature threshold value W1, the temperature difference threshold value V2, the temperature rise threshold value A3, the temperature rise recording unit time value U3, the temperature rise time threshold value N3 and the delay time value T.
The invention has the beneficial effects that:
data analysis is carried out through the infrared thermograph and the visible light image, front end and rear end processing is carried out through monitoring and detection, intelligent identification and intelligent fault diagnosis are carried out on the equipment, and the data processing efficiency is improved while intellectualization is achieved.
Drawings
Fig. 1 is a schematic flow diagram of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "inside", "outside", "left", "right", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, or the orientations or positional relationships that the products of the present invention are conventionally placed in use, or the orientations or positional relationships that are conventionally understood by those skilled in the art, and are used for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Furthermore, the terms "first," "second," and the like are used merely to distinguish one description from another, and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is also to be noted that, unless otherwise explicitly stated or limited, the terms "disposed" and "connected" are to be interpreted broadly, and for example, "connected" may be a fixed connection, a detachable connection, or an integral connection; can be mechanically or electrically connected; the connection may be direct or indirect via an intermediate medium, and may be a communication between the two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The following detailed description of embodiments of the invention refers to the accompanying drawings.
As shown in figure 1 of the drawings, in which,
server configuration monitoring fault event information table
Figure BDA0003298223280000041
Monitoring target information table
Figure BDA0003298223280000042
Fault grade information table
Figure BDA0003298223280000043
The server sends the monitoring fault event information table to an industrial personal computer of which the front end is connected with the infrared thermal imaging equipment and the visible light equipment;
the infrared thermal imaging equipment and the visible light equipment start to acquire data; the industrial personal computer sets a data acquisition period, acquires data according to the period, and analyzes the data according to information configured by the monitoring fault event information table;
the analysis method is a power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images, and comprises the following steps:
s1, acquiring infrared thermal imaging data and visible light image data of the power generation equipment during inspection;
and S11, judging whether the detected object has obvious arcing and discharging according to the collected visible light image data, if so, judging the fault level as the level S, otherwise, entering the step S2.
S2, judging whether the infrared thermal imaging data has pixel points exceeding a standard temperature value; if yes, the method goes to step S3, otherwise, the method goes to step S1 to continuously inspect the next device;
s3, judging whether the number of all the pixel points exceeding the standard temperature value is larger than the minimum analysis pixel value; if yes, the step S4 is proceeded, otherwise, the step S1 is proceeded;
s4, analyzing the visible light image to obtain a contour reference function; proceeding to step S5; step S4 specifically includes:
f (i, j) is used for representing the digital image, the horizontal resolution of the image is H1, the value range of i is 0- (H1-1), the vertical resolution of the image is V1, and the value range of j is 0- (V1-1);
setting G (i) as a horizontal pixel evaluation array, G (i) as a vertical pixel evaluation array, and calculating each G (i) and G (i) according to the actual resolution of the image, wherein the calculation method comprises the following steps:
when i is 0 and j is 0,
or
When i is 0 and j is V1-1,
or
When i is H1-1, and j is 0,
or
When i is H1-1 and j is V1-1:
G(i)=f(i,j);
G(j)=f(i,j);
0, and 0< j < V1-1:
Figure BDA0003298223280000051
G(j)=f(0,j);
j is 0, and 0< i < H1-1:
G(i)=f(i,0);
Figure BDA0003298223280000061
0< i < H1-1, and 0< j < V1-1:
Figure BDA0003298223280000062
Figure BDA0003298223280000063
calculating a comparative evaluation function based on the values of G (i) and G (j)
Figure BDA0003298223280000064
If the value of P (i, J) is less than or equal to a predefined contour decision parameter J, then L (i, J) ═ P (i, J);
if P (i, J) is greater than the predefined contour decision parameter J, then L (i, J) is 0;
thereby obtaining the profile reference function L (x, y).
S5, calculating a contour difference factor C according to the contour reference function; proceeding to step S6; step S5 specifically includes:
the profile difference factor C is calculated by the following formula,
Figure BDA0003298223280000065
where F (i, j) is the profile function in the profile factor in the table of monitored fault event information.
S6, judging whether C is larger than or equal to a threshold value Mmin in the set contour factor and smaller than or equal to a threshold value Mmax in the set contour factor; if yes, determining that the device matching is successful, and entering step S7; if not, determining that the equipment matching fails, sending an equipment matching error message to the server, automatically recording and alarming by the server background, and then jumping to the step S1;
s7, setting a temperature threshold value W1, a temperature difference threshold value V2, a temperature rise threshold value A3, a temperature rise recording unit time value U3, a temperature rise time threshold value N3 and a delay time value T according to power generation equipment needing to be diagnosed, and judging to obtain multiple fault levels after acquiring temperature and time period data of the power generation equipment through an infrared thermal imager and comparing the data with the set temperature threshold value W1, the temperature difference threshold value V2, the temperature rise threshold value A3, the temperature rise recording unit time value U3, the temperature rise time threshold value N3 and the delay time value T.
The fault grade comprises a grade S, and the machine must be stopped for serious defects; grade A, which is a more serious defect, is to be confirmed manually; class B, which is a general defect, may be left unprocessed for the moment, and statistical data must be included; grade C, normal.
The fault grade judging method comprises the following steps:
when the highest temperature collected by the thermal infrared imager is higher than W1, starting a Timer1, setting the value of Timer1 as T, and stopping the Timer if the highest temperature is lower than W1 during the running period of the Timer 1; during the running period of the Timer1, if the highest temperature is continuously higher than W1, when the Timer1 is up, setting the current fault level to be B, and starting to record the difference value Vm between the highest temperature and the lowest temperature acquired by the thermal infrared imager;
when the fault level is B, if the value of the highest temperature is lower than W1, starting a Timer1, setting the value of the Timer1 to be T, if the value of the highest temperature is higher than W1 in the running process of the Timer1, stopping the Timer1, if the value of the highest temperature is continuously lower than W1, and setting the current fault level to be C when the Timer1 is up;
when the fault grade is B, if the difference value Vm of the highest temperature and the lowest temperature is higher than V2, a Timer2 is started, the value of Timer2 is set to be T, and during the running period of the Timer2, if the temperature difference value Vm is lower than V2, the Timer is stopped; during the running of the Timer2, if the temperature difference value is continuously higher than V2 and the maximum temperature value is larger than W1, setting the fault level to be A when the Timer2 is up;
when the fault level is A, if the value of the highest temperature is lower than W1, starting a Timer1, setting the value of the Timer1 to be T, if the value of the highest temperature is higher than W1 in the running process of the Timer1, stopping the Timer1, if the value of the highest temperature is continuously lower than W1, and setting the fault level to be C when the Timer1 is up;
when the fault level is A, if the temperature difference value is lower than V2, starting a Timer2, setting the value of Timer2 as T, if the temperature difference value is higher than V2 in the running process of the Timer2, stopping the Timer2, if the temperature difference value is continuously lower than V2, judging whether the current highest temperature value is larger than W1 when the Timer2 is in the running process, if so, setting the fault level as B, and if not, setting the fault level as C;
when the fault level is A, setting a timer Period3, setting the value of Period3 As U3, recording the current highest temperature value Wx, simultaneously starting the timer Period3, recording the current highest temperature value Wy when the timer Period3 arrives, calculating the temperature rise value As1 of the current unit time As Wy-Wx, periodically starting the timer Period3, recording the current highest temperature value each time arrives, and so on, recording the temperature rise value sequences As2 and As3 … … AsN. Comparing the temperature rise value AsN with a temperature rise threshold value A3, and if the number of the temperature rise values continuously exceeding the threshold value A3 is larger than or equal to N3, the highest temperature value is larger than W1, and the temperature difference value is larger than V2, setting the fault level as S;
when the fault level is S, if the value of the highest temperature is lower than W1, starting a Timer1, setting the value of the Timer1 to be T, if the value of the highest temperature is higher than W1 in the running process of the Timer1, stopping the Timer1, if the value of the highest temperature is continuously lower than W1, and setting the fault level to be C when the Timer1 is up;
when the fault level is S, if the temperature difference value is lower than V2, starting a Timer2, setting the value of Timer2 as T, if the temperature difference value is higher than V2 in the running process of the Timer2, stopping the Timer2, if the temperature difference value is continuously lower than V2, judging whether the current highest temperature value is larger than W1 when the Timer2 is in the running process, if so, setting the fault level as B, and if not, setting the fault level as C;
when the fault level is S, if the temperature rise value is less than A3 and the number of the temperature rise values which are continuously less than the threshold value A3 is greater than or equal to N3, judging the temperature difference value and the highest temperature value;
if the temperature difference value is greater than or equal to V2 and the value of the highest temperature is greater than or equal to W1, setting the fault level to A;
if the temperature difference value is less than or equal to V2 and the value of the highest temperature is greater than or equal to W1, setting the fault level to B;
if the value of the highest temperature is less than W1, the failure level is set to C.
And finally, according to the fault grade given in the monitoring fault event information table, when the monitored fault grade is the same as the fault grade, sending a monitoring report to a server, wherein the monitoring report comprises a monitoring ID, a monitoring target ID and the fault grade.
The technical solution of the present invention is not limited to the limitations of the above specific embodiments, and all technical modifications made according to the technical solution of the present invention fall within the protection scope of the present invention.

Claims (6)

1. The power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images is characterized by comprising the following steps of:
s1, acquiring infrared thermal imaging data and visible light image data of the power generation equipment during inspection; proceeding to step S2;
s2, judging whether the infrared thermal imaging data has pixel points exceeding a standard temperature value; if yes, the method goes to step S3, otherwise, the method goes to step S1 to continuously inspect the next device;
s3, judging whether the number of all the pixel points exceeding the standard temperature value is larger than the minimum analysis pixel value; if yes, the step S4 is proceeded, otherwise, the step S1 is proceeded;
s4, analyzing the visible light image to obtain a contour reference function; proceeding to step S5;
s5, calculating a contour difference factor C according to the contour reference function; proceeding to step S6;
s6, judging whether C is larger than or equal to a threshold value Mmin in the set contour factor and smaller than or equal to a threshold value Mmax in the set contour factor; if yes, determining that the device matching is successful, and entering step S7; if not, determining that the equipment matching fails, sending an equipment matching error message to the server, automatically recording and alarming by the server background, and then jumping to the step S1;
s7, setting a temperature threshold value W1, a temperature difference threshold value V2, a temperature rise threshold value A3, a temperature rise recording unit time value U3, a temperature rise time threshold value N3 and a delay time value T according to power generation equipment needing to be diagnosed, and judging to obtain multiple fault levels after acquiring temperature and time period data of the power generation equipment through an infrared thermal imager and comparing the data with the set temperature threshold value W1, the temperature difference threshold value V2, the temperature rise threshold value A3, the temperature rise recording unit time value U3, the temperature rise time threshold value N3 and the delay time value T.
2. The power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images as claimed in claim 1, wherein step S4 specifically comprises:
f (i, j) is used for representing the digital image, the horizontal resolution of the image is H1, the value range of i is 0- (H1-1), the vertical resolution of the image is V1, and the value range of j is 0- (V1-1);
setting G (i) as a horizontal pixel evaluation array, G (i) as a vertical pixel evaluation array, and calculating each G (i) and G (i) according to the actual resolution of the image, wherein the calculation method comprises the following steps:
when i is 0 and j is 0,
or
When i is 0 and j is V1-1,
or
When i is H1-1, and j is 0,
or
When i is H1-1 and j is V1-1:
G(i)=f(i,j);
G(j)=f(i,j);
0, and 0< j < V1-1:
Figure FDA0003298223270000021
G(j)=f(0,j);
j is 0, and 0< i < H1-1:
G(i)=f(i,0);
Figure FDA0003298223270000022
0< i < H1-1, and 0< j < V1-1:
Figure FDA0003298223270000023
Figure FDA0003298223270000024
calculating a comparative evaluation function based on the values of G (i) and G (j)
Figure FDA0003298223270000025
If the value of P (i, J) is less than or equal to a predefined contour decision parameter J, then L (i, J) ═ P (i, J);
if P (i, J) is greater than the predefined contour decision parameter J, then L (i, J) is 0;
thereby obtaining the profile reference function L (x, y).
3. The power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images as claimed in claim 1, wherein step S5 specifically comprises:
the profile difference factor C is calculated by the following formula,
Figure FDA0003298223270000031
where F (i, j) is the profile function in the profile factor in the table of monitored fault event information.
4. The infrared thermal imaging and visible light image-based power generation equipment fault diagnosis method according to claim 1, wherein the fault grade includes a grade S, and a shutdown is necessary for a serious defect; grade A, which is a more serious defect, is to be confirmed manually; class B, which is a general defect, may be left unprocessed for the moment, and statistical data must be included; grade C, normal.
5. The power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images as claimed in claim 4, wherein the fault level judgment method comprises:
when the highest temperature collected by the thermal infrared imager is higher than W1, starting a Timer1, setting the value of Timer1 as T, and stopping the Timer if the highest temperature is lower than W1 during the running period of the Timer 1; during the running period of the Timer1, if the highest temperature is continuously higher than W1, when the Timer1 is up, setting the current fault level to be B, and starting to record the difference value Vm between the highest temperature and the lowest temperature acquired by the thermal infrared imager;
when the fault level is B, if the value of the highest temperature is lower than W1, starting a Timer1, setting the value of the Timer1 to be T, if the value of the highest temperature is higher than W1 in the running process of the Timer1, stopping the Timer1, if the value of the highest temperature is continuously lower than W1, and setting the current fault level to be C when the Timer1 is up;
when the fault grade is B, if the difference value Vm of the highest temperature and the lowest temperature is higher than V2, a Timer2 is started, the value of Timer2 is set to be T, and during the running period of the Timer2, if the temperature difference value Vm is lower than V2, the Timer is stopped; during the running of the Timer2, if the temperature difference value is continuously higher than V2 and the maximum temperature value is larger than W1, setting the fault level to be A when the Timer2 is up;
when the fault level is A, if the value of the highest temperature is lower than W1, starting a Timer1, setting the value of the Timer1 to be T, if the value of the highest temperature is higher than W1 in the running process of the Timer1, stopping the Timer1, if the value of the highest temperature is continuously lower than W1, and setting the fault level to be C when the Timer1 is up;
when the fault level is A, if the temperature difference value is lower than V2, starting a Timer2, setting the value of Timer2 as T, if the temperature difference value is higher than V2 in the running process of the Timer2, stopping the Timer2, if the temperature difference value is continuously lower than V2, judging whether the current highest temperature value is larger than W1 when the Timer2 is in the running process, if so, setting the fault level as B, and if not, setting the fault level as C;
when the fault level is A, setting a timer Period3, setting the value of Period3 As U3, recording the current highest temperature value Wx, simultaneously starting the timer Period3, recording the current highest temperature value Wy when the timer Period3 arrives, calculating the temperature rise value As1 of the current unit time As Wy-Wx, periodically starting the timer Period3, recording the current highest temperature value each time arrives, and so on, recording the temperature rise value sequences As2 and As3 … … AsN. Comparing the temperature rise value AsN with a temperature rise threshold value A3, and if the number of the temperature rise values continuously exceeding the threshold value A3 is larger than or equal to N3, the highest temperature value is larger than W1, and the temperature difference value is larger than V2, setting the fault level as S;
when the fault level is S, if the value of the highest temperature is lower than W1, starting a Timer1, setting the value of the Timer1 to be T, if the value of the highest temperature is higher than W1 in the running process of the Timer1, stopping the Timer1, if the value of the highest temperature is continuously lower than W1, and setting the fault level to be C when the Timer1 is up;
when the fault level is S, if the temperature difference value is lower than V2, starting a Timer2, setting the value of Timer2 as T, if the temperature difference value is higher than V2 in the running process of the Timer2, stopping the Timer2, if the temperature difference value is continuously lower than V2, judging whether the current highest temperature value is larger than W1 when the Timer2 is in the running process, if so, setting the fault level as B, and if not, setting the fault level as C;
when the fault level is S, if the temperature rise value is less than A3 and the number of the temperature rise values which are continuously less than the threshold value A3 is greater than or equal to N3, judging the temperature difference value and the highest temperature value;
if the temperature difference value is greater than or equal to V2 and the value of the highest temperature is greater than or equal to W1, setting the fault level to A;
if the temperature difference value is less than or equal to V2 and the value of the highest temperature is greater than or equal to W1, setting the fault level to B;
if the value of the highest temperature is less than W1, the failure level is set to C.
6. The power generation equipment fault diagnosis method based on infrared thermal imaging and visible light images as claimed in claim 4, further comprising a step S11 between the step S1 and the step S2, wherein the step S11 is: and judging whether the measured object has obvious arcing and discharging according to the collected visible light image data, if so, judging the fault level as a level S, and otherwise, entering the step S2.
CN202111183379.0A 2021-10-11 2021-10-11 Power generation equipment fault diagnosis method based on infrared thermal imaging and visible light image Pending CN113899973A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111183379.0A CN113899973A (en) 2021-10-11 2021-10-11 Power generation equipment fault diagnosis method based on infrared thermal imaging and visible light image

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111183379.0A CN113899973A (en) 2021-10-11 2021-10-11 Power generation equipment fault diagnosis method based on infrared thermal imaging and visible light image

Publications (1)

Publication Number Publication Date
CN113899973A true CN113899973A (en) 2022-01-07

Family

ID=79191251

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111183379.0A Pending CN113899973A (en) 2021-10-11 2021-10-11 Power generation equipment fault diagnosis method based on infrared thermal imaging and visible light image

Country Status (1)

Country Link
CN (1) CN113899973A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115856556A (en) * 2023-03-02 2023-03-28 深圳市帝稳电子有限公司 Product detection method and system for power adapter production
TWI810863B (en) * 2022-03-24 2023-08-01 中華電信股份有限公司 An abnormal inspection system and method for power generation equipment and computer-readable medium thereof
CN117420426A (en) * 2023-10-12 2024-01-19 国网安徽省电力有限公司 Contact state online evaluation method and system applied to GIS isolating switch

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107064751A (en) * 2017-03-10 2017-08-18 北京环境特性研究所 A kind of dual-waveband imaging discharge detector and its application method for high ferro
CN111948501A (en) * 2020-08-05 2020-11-17 广州市赛皓达智能科技有限公司 Automatic inspection equipment for power grid operation
US20210020360A1 (en) * 2019-07-15 2021-01-21 Wuhan University Internal thermal fault diagnosis method of oil-immersed transformer based on deep convolutional neural network and image segmentation
CN112880837A (en) * 2021-01-26 2021-06-01 四川华能宝兴河水电有限责任公司 Equipment fault analysis method
CN112924471A (en) * 2021-01-26 2021-06-08 四川华能宝兴河水电有限责任公司 Equipment fault diagnosis system and diagnosis method thereof
CN213715353U (en) * 2020-12-17 2021-07-16 华北电力大学(保定) Fault detection system for high-voltage distribution board

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107064751A (en) * 2017-03-10 2017-08-18 北京环境特性研究所 A kind of dual-waveband imaging discharge detector and its application method for high ferro
US20210020360A1 (en) * 2019-07-15 2021-01-21 Wuhan University Internal thermal fault diagnosis method of oil-immersed transformer based on deep convolutional neural network and image segmentation
CN111948501A (en) * 2020-08-05 2020-11-17 广州市赛皓达智能科技有限公司 Automatic inspection equipment for power grid operation
CN213715353U (en) * 2020-12-17 2021-07-16 华北电力大学(保定) Fault detection system for high-voltage distribution board
CN112880837A (en) * 2021-01-26 2021-06-01 四川华能宝兴河水电有限责任公司 Equipment fault analysis method
CN112924471A (en) * 2021-01-26 2021-06-08 四川华能宝兴河水电有限责任公司 Equipment fault diagnosis system and diagnosis method thereof

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI810863B (en) * 2022-03-24 2023-08-01 中華電信股份有限公司 An abnormal inspection system and method for power generation equipment and computer-readable medium thereof
CN115856556A (en) * 2023-03-02 2023-03-28 深圳市帝稳电子有限公司 Product detection method and system for power adapter production
CN117420426A (en) * 2023-10-12 2024-01-19 国网安徽省电力有限公司 Contact state online evaluation method and system applied to GIS isolating switch

Similar Documents

Publication Publication Date Title
CN113899973A (en) Power generation equipment fault diagnosis method based on infrared thermal imaging and visible light image
CN108663988B (en) Intelligent monitoring system of numerical control machine tool based on Internet of things
KR101411564B1 (en) System ant method for diagnosing thermal image of 2d array
CN112924471B (en) Equipment fault diagnosis system and diagnosis method thereof
CN104899936B (en) A kind of photovoltaic module fault cues method and system based on image recognition
CN1882078A (en) Image error detection device for monitoring camera
JP5168215B2 (en) Appearance inspection device
CN112734698B (en) Cable terminal abnormality diagnosis method and device based on infrared image
CN117274722B (en) Intelligent detection method for distribution box based on infrared image
CN116308300B (en) Power equipment state monitoring evaluation and command method and system
CN118405019B (en) Fill electric pile system with intelligent operation maintenance function
CN115586458A (en) Method and system for monitoring mistaken hanging prevention of ground wire in contact network maintenance operation
US12092526B2 (en) Apparatus for monitoring a switchgear
CN117713381A (en) Switch board system convenient to overhaul
CN108133479B (en) Automatic spinning machine drawing-in monitoring method and device
JP5302926B2 (en) Smoke detector
KR102587679B1 (en) Solar panel abnormality detection device and method thereof
CN112085724A (en) Cabinet temperature measuring method and device based on BIM and thermal image
CN113992151A (en) Method, device and equipment for determining working state of photovoltaic array and storage medium
JP7136479B2 (en) Inspection device, inspection method and inspection program
CN109064687A (en) A kind of self-service terminal condition monitoring system and method
KR102359985B1 (en) A system and method for data collection
CN114323302A (en) Intelligent fault identification method for zinc oxide arrester
CN114264933B (en) Fault detection method and fault detection system for integrated circuit board
TW201118317A (en) Vision-based method for combustion process monitoring, diagnosis, and computer-readable medium using the same

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination