CN115541090A - Boiler pipeline stress monitoring system for safety assessment - Google Patents

Boiler pipeline stress monitoring system for safety assessment Download PDF

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Publication number
CN115541090A
CN115541090A CN202211382999.1A CN202211382999A CN115541090A CN 115541090 A CN115541090 A CN 115541090A CN 202211382999 A CN202211382999 A CN 202211382999A CN 115541090 A CN115541090 A CN 115541090A
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stress
analysis module
image
data
image analysis
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CN115541090B (en
Inventor
刘立甲
刘佳春
董胜利
林建锐
杨海涛
伍雨欣
李霜竞
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Zhuhai Xinyingchuang Energy Technology Co ltd
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Zhuhai Xinyingchuang Energy Technology Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
    • G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/14—Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection

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  • Engineering & Computer Science (AREA)
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Abstract

The invention provides a boiler pipeline stress monitoring system for safety assessment, which comprises a detection module, an image acquisition module, an image analysis module and a data analysis module, wherein the detection module is used for reacting stress generated by a boiler pipeline, the image acquisition module is used for acquiring reaction image data of the detection module, the image analysis module is used for analyzing and processing the image data, and the data analysis module calculates to obtain a safety assessment conclusion of the pipeline based on an image processing result; this system is through installing the circle by the magnetic ring wall outside the monitoring point to obtain the gap width between the magnetic ring through image processing, and then calculate the stress that the pipeline received, monitor the security of pipeline through to stress analysis, in time discover the problem.

Description

Boiler pipeline stress monitoring system for safety assessment
Technical Field
The invention relates to the field of general measurement of force or stress, in particular to a boiler pipeline stress monitoring system for safety assessment.
Background
The boiler pipe is made of steel with two open ends and a hollow cross section, the length of the steel is larger than that of the periphery of the steel, the boiler pipe can be used for pipelines, thermal equipment, mechanical industry, petroleum geological exploration, containers, chemical industry and special purposes, the boiler pipe generates stress due to the fact that high-pressure gas often passes through the pipeline and extrudes the bypass pipe outwards, and when the generated stress is abnormal, the problem that how to better monitor the stress of the boiler pipe is the problem which needs to be solved at present is explained.
The foregoing discussion of the background art is intended only to facilitate an understanding of the present invention. This discussion is not an acknowledgement or admission as to part of the common general knowledge of any of the materials referred to.
A number of boiler tube monitoring systems have been developed, and through a great deal of search and reference, it is found that the existing monitoring system is disclosed as CN114034415B, and these systems generally include a computer, a single chip, a signal generator, a pre-gain amplifier, a power amplifier and a yoke detector, which are electrically connected in sequence, and the yoke detector can generate an excitation signal: the detection method comprises the following steps: inputting a regulation function in the singlechip; inputting a preset magnetization direction angle variation and magnetic flux measured by a magnetic yoke detector into a computer to regulate and control the pre-gain amplification factor of an excitation signal; placing a magnetic yoke detector on the surface of the aviation liquid pressure pipeline and performing pressing measurement to obtain a detection signal; the root mean square of the detection signal is input to a function preset in a computer to obtain a relative anisotropy and stress distribution function. However, the process of the system is complicated when the surface of the pipeline is pressed and measured, data on one position can be obtained on one monitoring point, comprehensive stress information cannot be mastered, and the situation that safety problems cannot be found in time exists.
Disclosure of Invention
The invention aims to provide a boiler pipeline stress monitoring system for safety assessment, aiming at the existing defects.
The invention adopts the following technical scheme:
a boiler pipeline stress monitoring system for safety assessment comprises a detection module, an image acquisition module, an image analysis module and a data analysis module, wherein the detection module is used for reacting to stress generated by a boiler pipeline, the image acquisition module is used for acquiring reaction image data of the detection module, the image analysis module is used for analyzing and processing the image data, and the data analysis module calculates and obtains a pipeline safety assessment conclusion based on an image processing result;
the detection module comprises magnetic rings, at least two magnetic rings are enclosed into a circle and sleeved outside the boiler pipeline, the image acquisition module comprises a camera, the camera shoots gaps between the magnetic rings and sends shot pictures to the image analysis module, and the image analysis module analyzes the gaps to obtain the width value of the gaps in each picture;
the camera continuously moves and shoots a magnetic ring on a monitoring point, and the image analysis module records the gap width value of continuous n pictures as a group of arrays
Figure 661285DEST_PATH_IMAGE001
And in an array
Figure 365935DEST_PATH_IMAGE001
Sending the data to the data analysis module as a unit, wherein n is the number of magnetic rings on a monitoring point;
the data analysis module comprises a data memory, a calculation processor and an output unit, the data memory is used for receiving and storing image analysis data of the image analysis module on all monitoring points, the calculation processor executes calculation tasks based on the image analysis data, and the output unit is used for outputting evaluation results or warning information;
the calculation processor calculates the real-time stress value on the monitoring point according to the following formula
Figure 907775DEST_PATH_IMAGE002
：
Figure 938048DEST_PATH_IMAGE003
；
Wherein the content of the first and second substances,
Figure 565338DEST_PATH_IMAGE004
in order to obtain the stress conversion factor,
Figure 542522DEST_PATH_IMAGE005
is the initial gap width;
the calculation processor calculates a first safety index of a single monitoring point according to the following formula
Figure 735606DEST_PATH_IMAGE006
：
Figure 202359DEST_PATH_IMAGE007
；
Wherein the content of the first and second substances,
Figure 316946DEST_PATH_IMAGE008
in order to be the stress threshold value,
Figure 97820DEST_PATH_IMAGE009
in order to achieve a degree of spatial stability,
Figure 348673DEST_PATH_IMAGE010
time stability;
when the first safety index is larger than a first safety threshold value, the output unit outputs an alarm;
further, the calculation processor calculates the spatial stability of the monitoring point according to the following formula
Figure 723678DEST_PATH_IMAGE009
：
Figure 325560DEST_PATH_IMAGE011
；
Wherein the content of the first and second substances,
Figure 706863DEST_PATH_IMAGE012
is an array of
Figure 77802DEST_PATH_IMAGE013
Average of (d);
further, the calculation processor calculates the time stability according to a plurality of real-time stress values Fr on the same monitoring point
Figure 824041DEST_PATH_IMAGE010
：
Figure 444378DEST_PATH_IMAGE014
；
Wherein m is the number of continuous real-time stress values employed,
Figure 567055DEST_PATH_IMAGE015
the jth real-time stress value is represented,
Figure 589237DEST_PATH_IMAGE016
the average of the m real-time stress values is adopted;
furthermore, the image acquisition module further comprises an installation rod and a ring rail, the installation rod is parallel to the boiler pipeline, the ring rail is installed on the installation rod and is in one-to-one correspondence with the monitoring points, the camera is installed in the ring rail and can slide in the ring rail, a control assembly is arranged on the ring rail and is used for controlling the sliding of the camera, a first communication assembly is arranged on the camera, and the first communication assembly can wirelessly send the shot picture to the image analysis module;
further, the calculation processor calculates a second safety index of the entire pipeline according to the following formula
Figure 771957DEST_PATH_IMAGE017
：
Figure 348432DEST_PATH_IMAGE018
；
Wherein the content of the first and second substances,
Figure 9220DEST_PATH_IMAGE019
representing the maximum real-time stress value in all monitoring points at the same time stamp,
Figure 900558DEST_PATH_IMAGE020
representing the minimum real-time stress value in all monitoring points under the same timestamp;
when the second safety index is larger than a second safety threshold value, the output unit outputs an alarm.
The beneficial effects obtained by the invention are as follows:
the system is connected with the magnetic rings to form a ring sleeve outside the boiler pipeline to react on stress, the comprehensive stress on the monitoring point is estimated according to the synthesis of gaps among the magnetic rings, the difference of the stress on different positions on the monitoring point is obtained according to the difference of the gaps among the magnetic rings, the stress information obtained through analysis is more comprehensive, more accurate safety assessment is obtained based on the stress information, the number of the magnetic rings forming the ring is more, the beating result is more accurate, the system obtains the specific numerical value of the width among the gaps through image analysis, and the system has the capability of identifying micro changes.
For a better understanding of the features and technical content of the present invention, reference should be made to the following detailed description of the invention and accompanying drawings, which are provided for purposes of illustration and description only and are not intended to limit the invention.
Drawings
FIG. 1 is a schematic view of the overall structural framework of the present invention;
FIG. 2 is a schematic view of the magnetic ring of the present invention connected to form a ring;
FIG. 3 is a schematic view of an image acquisition module according to the present invention;
FIG. 4 is a schematic diagram of an image analysis module according to the present invention;
FIG. 5 is a schematic diagram of a data analysis module according to the present invention.
Detailed Description
The following is a description of embodiments of the present invention with reference to specific embodiments, and those skilled in the art will understand the advantages and effects of the present invention from the disclosure of the present specification. The invention is capable of other and different embodiments and its several details are capable of modification in various other respects, all without departing from the spirit and scope of the present invention. The drawings of the present invention are for illustrative purposes only and are not intended to be drawn to scale. The following embodiments are further detailed to explain the technical matters related to the present invention, but the disclosure is not intended to limit the scope of the present invention.
The first embodiment.
The embodiment provides a boiler pipeline stress monitoring system for safety assessment, which, with reference to fig. 1, includes a detection module, an image acquisition module, an image analysis module and a data analysis module, wherein the detection module is used for making a reaction on stress generated by a boiler pipeline, the image acquisition module is used for acquiring reaction image data of the detection module, the image analysis module is used for analyzing and processing the image data, and the data analysis module calculates a safety assessment conclusion of the pipeline based on an image processing result;
the detection module comprises magnetic rings, at least two magnetic rings are enclosed into a circle and sleeved outside the boiler pipeline, the image acquisition module comprises a camera, the camera shoots gaps between the magnetic rings and sends shot pictures to the image analysis module, and the image analysis module analyzes the gaps to obtain the width value of the gaps in each picture;
the camera continuously moves and shoots a magnetic ring on a monitoring point, and the image analysis module records the gap width value of continuous n pictures as a group of arrays
Figure 519758DEST_PATH_IMAGE021
And in an array
Figure 52371DEST_PATH_IMAGE021
Sending the data to the data analysis module for a unit, wherein n is the number of magnetic rings on a monitoring point;
the data analysis module comprises a data memory, a calculation processor and an output unit, the data memory is used for receiving and storing image analysis data of the image analysis module on all monitoring points, the calculation processor executes calculation tasks based on the image analysis data, and the output unit is used for outputting evaluation results or warning information;
the calculation processor calculates the real-time stress value on the monitoring point according to the following formula
Figure 48008DEST_PATH_IMAGE022
：
Figure 248046DEST_PATH_IMAGE023
；
Wherein the content of the first and second substances,
Figure 834885DEST_PATH_IMAGE024
in order to obtain the stress conversion factor,
Figure 589214DEST_PATH_IMAGE025
is the initial gap width;
the calculation processor calculates a first safety index of a single monitoring point according to the following formula
Figure 919701DEST_PATH_IMAGE026
：
Figure 708666DEST_PATH_IMAGE027
；
Wherein the content of the first and second substances,
Figure 404089DEST_PATH_IMAGE028
in order to be the stress threshold value,
Figure 176873DEST_PATH_IMAGE029
in order to achieve a degree of spatial stability,
Figure 45472DEST_PATH_IMAGE030
time stability;
when the first safety index is larger than a first safety threshold value, the output unit outputs an alarm;
the calculation processor calculates the space stability of the monitoring point according to the following formula
Figure 691873DEST_PATH_IMAGE029
：
Figure 823777DEST_PATH_IMAGE031
；
Wherein the content of the first and second substances,
Figure 818278DEST_PATH_IMAGE032
is an array of
Figure 490567DEST_PATH_IMAGE033
Average of (d);
the calculation processor calculates the time stability according to a plurality of real-time stress values Fr on the same monitoring point
Figure 519703DEST_PATH_IMAGE030
：
Figure 291350DEST_PATH_IMAGE034
；
Wherein m is the number of continuous real-time stress values employed,
Figure 835464DEST_PATH_IMAGE035
the jth real-time stress value is represented,
Figure 780286DEST_PATH_IMAGE036
the average of the m real-time stress values is adopted;
the image acquisition module further comprises an installation rod and a ring rail, the installation rod is parallel to the boiler pipeline, the ring rail is installed on the installation rod and corresponds to the monitoring points one by one, the camera is installed in the ring rail and can slide in the ring rail, a control assembly is arranged on the ring rail and used for controlling the sliding of the camera, a first communication assembly is arranged on the camera, and the first communication assembly can wirelessly send a shot picture to the image analysis module;
the calculation processor calculates a second safety index of the entire pipeline according to the following formula
Figure 663929DEST_PATH_IMAGE037
：
Figure 606477DEST_PATH_IMAGE038
；
Wherein the content of the first and second substances,
Figure 575570DEST_PATH_IMAGE039
representing the maximum real-time stress value in all monitoring points at the same time stamp,
Figure 589662DEST_PATH_IMAGE040
representing the minimum real-time stress value in all monitoring points under the same timestamp;
when the second safety index is larger than a second safety threshold value, the output unit outputs an alarm.
Example two.
The embodiment includes all contents in the first embodiment, and provides a boiler pipeline stress monitoring system for safety assessment, which includes a detection module, an image acquisition module, an image analysis module and a data analysis module, wherein the detection module is used for making a reaction on stress generated by a boiler pipeline, the image acquisition module is used for acquiring reaction image data of the detection module, the image analysis module is used for analyzing and processing the image data, and the data analysis module calculates a safety assessment conclusion of the pipeline based on an image processing result;
with reference to fig. 2, the detection module includes magnetic rings, an even number of the magnetic rings surround a circle outside the boiler pipeline, two adjacent magnetic rings are connected with each other through a synonym magnetic pole, the radius of the inner ring of the magnetic ring is the radius of the outer wall of the boiler pipeline, the magnetic ring surrounding the circle is called a magnetic ring, the boiler pipeline is provided with a plurality of monitoring points, each monitoring point is provided with a magnetic ring, the inner side of the magnetic ring is provided with a layer of heat insulation film, the influence of the temperature of the boiler pipeline on the magnetic rings is reduced, and the more the number of the magnetic rings forming the magnetic ring is, the more accurate the detection is;
with reference to fig. 3, the image acquisition module includes an installation rod, a ring rail and a camera, the installation rod is parallel to the boiler pipeline, the ring rail is installed on the installation rod and is in one-to-one correspondence with the monitoring points, the camera is installed in the ring rail and can slide in the ring rail, the camera is used for shooting a gap between magnetic rings, when the gap is located in the middle of a picture, the camera sends the shot picture to the image analysis module, a control component is arranged on the ring rail and is used for controlling the sliding of the camera, a first communication component is arranged on the camera, and the first communication component can send the shot picture to the image analysis module in a wireless manner;
with reference to fig. 4, the image analysis module includes an image memory, a grayscale processor and a statistical processor, the image memory is configured to store a received image, the grayscale processor is configured to perform graying processing on the image, the statistical processor is configured to perform statistical calculation on the grays of the pixels and obtain a gap width value, and the image analysis module sends the width value to the data analysis module and then deletes the corresponding image in the image processor to release a storage space;
with reference to fig. 5, the data analysis module includes a data storage for receiving and storing image analysis data on all monitoring points by the image analysis module, a calculation processor for executing calculation tasks based on the image analysis data, and an output unit for outputting evaluation results or warning information;
the image analysis module and the data analysis module can be integrated in an electronic device, the electronic device comprises a second communication component matched with the image acquisition module, and the second communication component can receive the image data sent by the first communication component and identify monitoring point information corresponding to the first communication component;
the process of controlling the sliding of the camera by the control assembly comprises the following steps:
s1, fixing the position of a camera, shooting a picture and sending the picture to the image analysis module, and analyzing the picture by the image analysis module to obtain position information of a gap
Figure 330741DEST_PATH_IMAGE041
Returning to the control component;
s2, the control component controls the camera to slide
Figure 506507DEST_PATH_IMAGE042
Fixing after the angle, shooting a picture and sending the picture to the image analysis module, and analyzing by the image analysis module to obtain the position information of the gap
Figure 962896DEST_PATH_IMAGE043
Returning to the control component;
s3, the control component controls the camera to slide
Figure 452784DEST_PATH_IMAGE044
The angle is fixed after the angle is fixed,
Figure 311018DEST_PATH_IMAGE044
comprises the following steps:
Figure 657686DEST_PATH_IMAGE045
；
s4, the control assembly controls the camera to slide at a fixed angular speed
Figure 335792DEST_PATH_IMAGE046
The angle is fixed after the angle is fixed,
Figure 691687DEST_PATH_IMAGE046
comprises the following steps:
Figure 670007DEST_PATH_IMAGE047
；
wherein n is the number of magnetic rings contained in one magnetic ring;
s5, the camera is
Figure 453155DEST_PATH_IMAGE048
Stopping stably within time and shooting an uploaded picture;
s6, continuously repeating the step S4 and the step S5;
the image analysis module grays the acquired picture, then counts the gray value with the maximum number of pixel points, the pixel point corresponding to the gray value is called a background point, the image analysis module intercepts a rectangle based on the background point, counts the number of pixel points with the gray value of the middle part of the rectangle different from the background point, and records the pixel points as the background point
Figure 418225DEST_PATH_IMAGE049
The image analysis module calculates the gap width of the picture according to the following formula
Figure 515494DEST_PATH_IMAGE050
：
Figure 817162DEST_PATH_IMAGE051
；
Wherein the content of the first and second substances,
Figure 771212DEST_PATH_IMAGE052
in order to cut the height of the rectangle,
Figure 158331DEST_PATH_IMAGE053
is a proportionality coefficient;
the proportionality coefficient
Figure 856028DEST_PATH_IMAGE053
The focal length of the camera and the shooting distance of the camera are related;
a group of gap widths obtained by shooting pictures based on one circle of sliding of camera are recorded as
Figure 277782DEST_PATH_IMAGE054
And i has a value of
Figure 402733DEST_PATH_IMAGE055
The image analysis module uses a set of data
Figure 277148DEST_PATH_IMAGE054
Sending the data to the data analysis module in units, and the data storage stores the data based on the monitoring point position and the time stamp of the picture
Figure 512958DEST_PATH_IMAGE054
Storing;
the data analysis module is used for analyzing each group of data
Figure 585956DEST_PATH_IMAGE054
Continuing to analyze the stress, the calculation processor calculates the real-time stress value according to the following formula
Figure 607440DEST_PATH_IMAGE056
：
Figure 969151DEST_PATH_IMAGE057
；
Wherein the content of the first and second substances,
Figure 274230DEST_PATH_IMAGE058
in order to obtain the stress conversion factor,
Figure 936156DEST_PATH_IMAGE059
is the initial gap width;
the stress conversion coefficient
Figure 402909DEST_PATH_IMAGE058
The magnetic strength of the magnetic ring is related, and the magnetic strength is obtained by testing the magnetic ring;
the calculation processor calculates the space stability of the monitoring point according to the following formula
Figure 517496DEST_PATH_IMAGE060
：
Figure 360687DEST_PATH_IMAGE061
；
Wherein the content of the first and second substances,
Figure 408277DEST_PATH_IMAGE062
is an array of
Figure 983615DEST_PATH_IMAGE063
An average of;
the calculation processor calculates the time stability according to a plurality of real-time stress values Fr on the same monitoring point
Figure 119586DEST_PATH_IMAGE064
：
Figure 704151DEST_PATH_IMAGE065
；
Wherein m is the number of continuous real-time stress values employed,
Figure 809510DEST_PATH_IMAGE066
the jth real-time stress value is represented,
Figure 821329DEST_PATH_IMAGE067
the average of the m real-time stress values is adopted;
the calculation processor calculates a first safety index of a single monitoring point according to the following formula
Figure 707245DEST_PATH_IMAGE068
：
Figure 564342DEST_PATH_IMAGE069
；
Wherein the content of the first and second substances,
Figure 55367DEST_PATH_IMAGE070
is the stress threshold;
when the first safety index is larger than a first safety threshold value, the output unit outputs an alarm;
the first safety threshold is a negative value and is set by a person skilled in the art according to experience;
the calculation processor calculates a second safety index of the entire pipeline according to the following formula
Figure 959125DEST_PATH_IMAGE071
：
Figure 270021DEST_PATH_IMAGE072
；
Wherein the content of the first and second substances,
Figure 196388DEST_PATH_IMAGE073
represents the maximum real-time stress value at the same time stamp,
Figure 338657DEST_PATH_IMAGE074
representing the minimum real-time stress value under the same timestamp;
when the second safety index is larger than a second safety threshold value, the output unit outputs an alarm.
The disclosure is only a preferred embodiment of the invention, and is not intended to limit the scope of the invention, so that all equivalent technical changes made by using the contents of the specification and the drawings are included in the scope of the invention, and further, the elements thereof can be updated as the technology develops.

Claims (5)

1. A boiler pipeline stress monitoring system for safety assessment is characterized by comprising a detection module, an image acquisition module, an image analysis module and a data analysis module, wherein the detection module is used for making a reaction on stress generated by a boiler pipeline, the image acquisition module is used for acquiring reaction image data of the detection module, the image analysis module is used for analyzing and processing the image data, and the data analysis module calculates a safety assessment conclusion of the pipeline based on an image processing result;
the detection module comprises magnetic rings, at least two magnetic rings are enclosed into a circle and sleeved outside the boiler pipeline, the image acquisition module comprises a camera, the camera shoots gaps between the magnetic rings and sends shot pictures to the image analysis module, and the image analysis module analyzes the gaps to obtain the width value of the gaps in each picture;
the camera continuously moves and shoots a magnetic ring on a monitoring point, and the image analysis module records the gap width value of continuous n pictures as a group of arrays
Figure 601457DEST_PATH_IMAGE001
And in an array
Figure 134070DEST_PATH_IMAGE001
Sending the data to the data analysis module for a unit, wherein n is the number of magnetic rings on a monitoring point;
the data analysis module comprises a data memory, a calculation processor and an output unit, the data memory is used for receiving and storing image analysis data of the image analysis module on all monitoring points, the calculation processor executes calculation tasks based on the image analysis data, and the output unit is used for outputting evaluation results or warning information;
the above-mentionedThe calculation processor calculates the real-time stress value on the monitoring point according to the following formula
Figure 864129DEST_PATH_IMAGE002
：
Figure 595324DEST_PATH_IMAGE003
；
Wherein the content of the first and second substances,
Figure 651005DEST_PATH_IMAGE004
in order to obtain the stress conversion coefficient,
Figure 936493DEST_PATH_IMAGE005
is the initial gap width;
the calculation processor calculates a first safety index of a single monitoring point according to the following formula
Figure 266980DEST_PATH_IMAGE006
：
Figure 55944DEST_PATH_IMAGE007
；
Wherein the content of the first and second substances,
Figure 82194DEST_PATH_IMAGE008
in order to be the stress threshold value,
Figure 386136DEST_PATH_IMAGE009
in order to achieve a high degree of spatial stability,
Figure 192418DEST_PATH_IMAGE010
time stability;
when the first safety index is larger than a first safety threshold value, the output unit outputs an alarm.
2. A method for fitting as claimed in claim 1A fully-evaluated boiler pipeline stress monitoring system, wherein the calculation processor calculates the spatial stability of the monitoring points according to the following formula
Figure 898206DEST_PATH_IMAGE009
：
Figure 764531DEST_PATH_IMAGE011
；
Wherein, the first and the second end of the pipe are connected with each other,
Figure 555769DEST_PATH_IMAGE012
is an array of
Figure 165742DEST_PATH_IMAGE013
Average of (d).
3. The boiler tube stress monitoring system for safety assessment according to claim 2, wherein said calculation processor calculates the time stability from a plurality of real-time stress values Fr on the same monitoring point
Figure 726036DEST_PATH_IMAGE010
：
Figure 763263DEST_PATH_IMAGE014
；
Wherein m is the number of continuous real-time stress values employed,
Figure 779148DEST_PATH_IMAGE015
the jth real-time stress value is represented,
Figure 989549DEST_PATH_IMAGE016
is the average of the m real-time stress values used.
4. The boiler pipe stress monitoring system for safety assessment according to claim 3, wherein the image acquisition module further comprises a mounting rod and a ring rail, the mounting rod is parallel to the boiler pipe, the ring rail is mounted on the mounting rod and corresponds to the monitoring points one by one, the camera is mounted in the ring rail and can slide in the ring rail, a control component is arranged on the ring rail and is used for controlling the sliding of the camera, a first communication component is arranged on the camera, and the first communication component can wirelessly send the shot picture to the image analysis module.
5. The boiler tube stress monitoring system for safety assessment according to claim 4, wherein said calculation processor calculates a second safety index for the entire tube according to
Figure 404350DEST_PATH_IMAGE017
：
Figure 612477DEST_PATH_IMAGE018
；
Wherein the content of the first and second substances,
Figure 581570DEST_PATH_IMAGE019
representing the maximum real-time stress value in all monitoring points at the same time stamp,
Figure 595663DEST_PATH_IMAGE020
representing the minimum real-time stress value in all monitoring points under the same timestamp;
when the second safety index is larger than a second safety threshold value, the output unit outputs an alarm.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2014105256A (en) * 2014-02-13 2015-08-20 Сергей Степанович Шаклеин METHOD FOR MONITORING TECHNICAL CONDITION OF PIPELINE AND SYSTEM FOR ITS IMPLEMENTATION
US20160231278A1 (en) * 2012-11-12 2016-08-11 Valerian Goroshevskiy System and method for inspecting subsea vertical pipeline
CN110763380A (en) * 2019-10-30 2020-02-07 煤炭科学技术研究院有限公司 One-hole multi-point type stress and displacement monitoring system based on fiber bragg grating measurement
CN113075065A (en) * 2021-03-05 2021-07-06 天津大学 Deep sea pipeline crack propagation monitoring and reliability evaluation system based on image recognition
CN113155015A (en) * 2021-03-24 2021-07-23 中国石油大学(华东) Strain monitoring method and system during pipeline operation
CN114294570A (en) * 2021-12-23 2022-04-08 中国特种设备检测研究院 Oil-gas pipeline stress monitoring and early warning method and system, storage medium and electronic device

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160231278A1 (en) * 2012-11-12 2016-08-11 Valerian Goroshevskiy System and method for inspecting subsea vertical pipeline
RU2014105256A (en) * 2014-02-13 2015-08-20 Сергей Степанович Шаклеин METHOD FOR MONITORING TECHNICAL CONDITION OF PIPELINE AND SYSTEM FOR ITS IMPLEMENTATION
CN110763380A (en) * 2019-10-30 2020-02-07 煤炭科学技术研究院有限公司 One-hole multi-point type stress and displacement monitoring system based on fiber bragg grating measurement
CN113075065A (en) * 2021-03-05 2021-07-06 天津大学 Deep sea pipeline crack propagation monitoring and reliability evaluation system based on image recognition
CN113155015A (en) * 2021-03-24 2021-07-23 中国石油大学(华东) Strain monitoring method and system during pipeline operation
CN114294570A (en) * 2021-12-23 2022-04-08 中国特种设备检测研究院 Oil-gas pipeline stress monitoring and early warning method and system, storage medium and electronic device

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