CN114049353B - Furnace tube temperature monitoring method - Google Patents
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 126
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- VGGSQFUCUMXWEO-UHFFFAOYSA-N Ethene Chemical compound C=C VGGSQFUCUMXWEO-UHFFFAOYSA-N 0.000 description 3
- 239000005977 Ethylene Substances 0.000 description 3
- 238000009529 body temperature measurement Methods 0.000 description 3
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- 238000004939 coking Methods 0.000 description 1
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- ZZUFCTLCJUWOSV-UHFFFAOYSA-N furosemide Chemical compound C1=C(Cl)C(S(=O)(=O)N)=CC(C(O)=O)=C1NCC1=CC=CO1 ZZUFCTLCJUWOSV-UHFFFAOYSA-N 0.000 description 1
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Abstract
The invention belongs to the technical field of on-line monitoring, and particularly relates to a furnace tube temperature monitoring method.
Description
Technical Field
The invention belongs to the technical field of on-line monitoring, and particularly relates to a furnace tube temperature monitoring method.
Background
The ethylene cracking furnace plays a significant role in industrial production of petrochemical enterprises, is a tap of petrochemical production, and the quality of operation directly relates to whether a production device can safely, efficiently and periodically operate. The radiant chamber is the core part of the ethylene cracking furnace, fuel sprayed from the burner is combusted in the radiant chamber, and the furnace tubes for conveying materials are arranged close to the flame, and simultaneously, the flame is ensured not to directly combust the furnace tubes, so that the materials are heated in a radiation mode. The two sides of the furnace tube in the radiation chamber are radiated by high temperature, and if the material with high viscosity is coked in the furnace tube, the local temperature of the tube wall of the furnace tube can be increased, so that the creep, carburization and even cracking of the furnace tube are easily caused, and the furnace tube needs to be stopped for maintenance, thereby influencing the production efficiency and the cost.
The thesis "application effect of infrared monitoring system for surface temperature of furnace tube of ethylene cracking furnace" discloses that the infrared monitoring system is used for realizing the measurement and visualization of the surface temperature of the furnace tube and realizing the overtemperature alarm function, however, in practical use, if the set alarm temperature is too high, the furnace tube may be seriously damaged during alarm, and if the set alarm temperature is too low, frequent alarm affects production and the alarm function cannot be realized. It is also disclosed in the paper that the char process can be continuously tracked using visualization techniques, which require personnel to continuously observe the effects that existing monitoring systems cannot automatically analyze abnormal temperature rise based on existing data.
Disclosure of Invention
The invention aims to provide a furnace tube temperature monitoring method capable of giving an alarm in time when the temperature of a furnace tube is abnormally increased.
In order to realize the purpose, the invention adopts the technical scheme that: a furnace tube temperature monitoring method comprises the following steps:
A. acquiring temperature values of all positions of a furnace tube under a normal working state to form a template image;
B. the image acquisition device acquires a monitoring image in a monitoring working state, and identifies a furnace tube image in the monitoring image, wherein the furnace tube image consists of furnace tube pixel points;
C. comparing the temperature value of each furnace tube pixel point in the monitoring image with the temperature value of the same position of the template image,
if the temperature value of a certain furnace tube pixel point in the monitoring image is larger than the temperature value of the corresponding point position in the template image, recording the difference of the two temperature values at the point position as a temperature rise change value,
if the temperature value of a certain furnace tube pixel point in the monitoring image is less than or equal to the temperature value of the corresponding point position in the template image, the temperature rise change value of the point position is not counted,
recording the temperature rise change value of the nth pixel point as
Substituting the formula to obtain a temperature rise index R,
and N is the total number of pixel points forming the furnace tube image in the monitoring image, and the monitoring system sends out a warning instruction when the temperature rise index exceeds a set threshold value.
Compared with the prior art, the invention has the following technical effects: the monitoring system can analyze and identify the temperature rise condition of the furnace tube according to the template image, thereby accurately and timely warning the abnormal temperature rise of the furnace tube, enabling operators to timely handle the abnormal condition and guaranteeing the production safety and the production continuity.
Drawings
The contents of the description and the references in the drawings are briefly described as follows:
FIG. 1 is a schematic diagram of the temperature rise index change;
FIG. 2 is a schematic view of the furnace at the time when the temperature rise index indicated by the arrow in FIG. 1 abnormally increases;
FIG. 3 is a schematic diagram of hot spot proportion trend;
FIG. 4 is a schematic view of the longitudinal uniformity of the furnace tube;
FIG. 5 is a schematic view of the lateral uniformity of the furnace tube;
FIG. 6 is a schematic view of a furnace chamber temperature trend curve;
FIG. 7 is a schematic view of a template image;
FIG. 8 is a schematic view of a monitored image;
FIG. 9 is a schematic diagram of a calibration image for marking the image area of the furnace tube.
In the figure: 10. template image, 11 key points, 12 matching area, 13 interference area, 20 monitoring image, 20a correction image, 21 monitoring key points, 22 furnace area monitoring area, 23 monitoring analysis area.
Detailed Description
The following description of the embodiments of the present invention will be made in detail with reference to the accompanying drawings.
A furnace tube temperature monitoring method comprises the following steps:
A. acquiring temperature values of all parts of a furnace tube under a normal working state to form a template image 10;
B. the image acquisition device acquires the monitoring image 20 in a monitoring working state, and identifies a furnace tube image in the monitoring image 20, wherein the furnace tube image consists of furnace tube pixel points;
C. comparing the temperature value of each furnace tube pixel point in the monitoring image 20 with the temperature value of the co-located position of the template image 10, wherein the co-located position refers to the consistent coordinate in the image, or the relative coordinate with a certain position/a certain point as the central point is consistent, and the co-located tube body of the furnace tubes on different images is substantially the same.
If the temperature value of a certain furnace tube pixel point in the monitoring image 20 is greater than the temperature value of the corresponding point location in the template image 10, recording the difference of the two temperature values at the point location as a temperature rise change value,
if the temperature value of a certain furnace tube pixel point in the monitoring image 20 is less than or equal to the temperature value of the corresponding point position in the template image 10, the temperature rise variation value of the point position is not counted,
recording the temperature rise change value of the nth pixel point as
Substituting the formula to obtain a temperature rise index R,
wherein N is the total number of pixels constituting the furnace tube image in the monitoring image 20,
when the temperature rise index exceeds a set threshold value, the temperature rise index indicates that coking possibly occurs due to abnormal temperature rise of a tube body at a certain position of the furnace tube in the monitoring image 20, and the monitoring system sends out a warning instruction.
The furnace tube temperature of each furnace tube in the template image 10 is the temperature of the furnace tube in the normal working state, and in the monitoring working state, the obtained monitoring image 20 can analyze the temperature rise condition of the furnace tube body based on the template image 10, so as to warn the working personnel in time when the temperature rise of the furnace tube body is too high.
The reliability of the furnace tube body temperature data in the template image 10 will directly affect the monitoring effect. The template image 10 may be calculated based on the furnace tube image analysis. For example, in a normal operating state of the furnace tube, the fixedly installed image capturing device obtains a plurality of furnace tube images, matches each furnace tube image and calculates the maximum/average temperature value of each pixel point of the co-located furnace tube, and applies the maximum/average temperature value of each pixel point of the furnace tube to draw the template image 10. The co-located pixel points refer to pixel points forming the co-located image of the furnace tube in each furnace tube image. Or after identifying the furnace tube image in the furnace tube image, manually calibrating the template temperature values of the furnace tube pixel points forming the furnace tube image and drawing the template image 10, wherein the template temperature values are obtained according to the historical temperature data of the furnace tube, for example, the maximum value in the historical temperature data of the furnace tube region where the furnace tube pixel points are marked is the template temperature value. Or directly selecting the image of the furnace tube in the normal working state from the furnace tube images as the template image 10.
In order to more intuitively show the abnormal temperature rise region, as shown in fig. 2, the temperature rise condition is marked on the corresponding monitoring image 20 according to the temperature rise value. The temperature rise condition is shown by a common temperature rise color cloud graph, and the maximum temperature rise area shown in the graph is an abnormal temperature rise area.
As shown in fig. 8, the monitoring image only includes images of some furnace tubes in the furnace chamber, and in order to obtain the temperature rise of all furnace tubes in the furnace chamber, in the embodiments in this market, a plurality of image acquisition devices are provided, and images acquired by different image acquisition devices at the same time are spliced to obtain the temperature information of all furnace tubes in the furnace chamber, so as to obtain the temperature rise index of the furnace chamber. In the step C, the temperature rise index of the furnace chamber is obtained according to the temperature information of all furnace tubes in the furnace chamber, as shown in fig. 1, a temperature rise index change diagram is drawn by taking time as a horizontal axis and the temperature rise index of the furnace chamber as a vertical axis, and the case where the rising slope of the temperature rise index curve exceeds the threshold or the temperature rise index value exceeds the threshold is indicated that the temperature of the furnace tubes in the furnace chamber is abnormal.
In order to further analyze the temperature rise condition, the method further comprises a step D of comparing the total number of pixels of the temperature exceeding the set threshold in the monitoring image 20 with the total number of pixels of the furnace tube image in the monitoring image 20 to obtain the heat duty ratio of the corresponding furnace tube, and drawing a hot spot duty ratio trend graph by taking time as a horizontal axis and the heat duty ratio as a vertical axis. The heat duty is calculated based on the absolute temperature values of the furnace tubes. The temperature threshold for calculating the heat ratio is set empirically, and the points in the furnace tube image that exceed the temperature threshold are hot spots. The ratio of the temperature super-high region to the furnace tube region in the monitoring image 20 can be obtained according to the heat ratio. The temperature rise condition can be further known by combining the heat duty ratio and the temperature rise index. For example, if the temperature rise index is high and the heat duty ratio is small, it indicates that the temperature of the furnace tube in the monitoring image 20 or a certain position in the furnace chamber is abnormally increased, and a focus may exist; and if the temperature rise index is high and the heat ratio is large, the integral temperature in the furnace chamber is increased, and the temperature of the furnace chamber needs to be adjusted.
In order to further know the comprehensive temperature condition of the furnace tube, in the step A, marking key points 11 on the template image 10 according to target monitoring points on the furnace tube; in the step B, the key points 11 on the template image 10 are compared to locate the monitoring key points 21 on the monitoring image 20. The target monitoring points are actual monitoring areas selected on the furnace tube body according to experience or temperature measurement requirements, and the key points 11 and the monitoring key points 21 are smaller graphic image areas where the target monitoring points on the corresponding images are located.
In the monitoring state, the monitoring state is set,
e1, forming the monitoring key points 21 at different tube passes on the same furnace tube into longitudinal key point groups, calculating the standard deviation of the temperature values of the monitoring key points 21 in each longitudinal key point group to obtain the longitudinal uniformity of the furnace tube, and drawing a schematic diagram of the longitudinal uniformity of the furnace tube by taking the transverse arrangement sequence of each furnace tube as a transverse axis and the longitudinal uniformity of each furnace tube as a longitudinal axis. Whether the temperature of each furnace tube from top to bottom is uniform can be obtained according to the schematic diagram of the longitudinal uniformity of the furnace tubes.
E2, forming the monitoring key points 21 at the same height into a transverse key point group, and drawing a furnace tube transverse uniformity schematic diagram by taking the transverse arrangement sequence of each monitoring key point 21 as a transverse axis and the temperature value of each monitoring key point 21 as a longitudinal axis. According to the schematic diagram of the transverse uniformity of the furnace tubes, whether the temperature of each furnace tube at the same height is uniform can be obtained.
And calculating the standard deviation of the temperature values of the monitoring key points 21 in each transverse key point group to obtain the transverse uniformity of the furnace tube and marking the schematic diagram of the transverse uniformity of the furnace tube.
E3, obtaining the average value of all the monitoring key points 21 to obtain the current temperature, and drawing the temperature trend curve chart of the furnace chamber by taking the time as the horizontal axis and the current temperature value of the key points as the vertical axis. The temperature trend graph is drawn based on the absolute temperature value of the furnace tube, and the actual temperature fluctuation condition of the whole furnace tube can be obtained according to the temperature trend graph.
It should be noted that the accurate identification of the furnace tube region is the basis of the accurate analysis of the monitoring system, and in order to avoid false alarm or missing report caused by identification error when the algorithm identifies the furnace tube image in the monitoring image 20, the following method may be applied to process the monitoring image 20 to obtain the accurate furnace tube image region:
example 1
An image processing method comprising the steps of:
k1, the interference region 13 and the matching region 12 are calibrated on the template image 10. The template image 10 includes furnace tube pixels constituting furnace tube images and non-furnace tube pixels constituting non-furnace tube images.
K2, acquiring the monitoring image 20. In specific implementation, the image acquisition device is fixedly installed on a furnace wall, and after the template image 10 is obtained, the posture of the image acquisition device is maintained to perform furnace tube monitoring operation to obtain a monitoring image 20. That is, the viewing angles of the monitoring image 20 and the template image 10 should be similar or consistent, so that the accurate identification of the furnace tube region can be ensured.
And matching the monitoring image 20 with the template image 10 to obtain a corrected image 20a, wherein the corrected image 20a has a monitoring matching area corresponding to the image of the matching area 12, then shielding the image area corresponding to the interference area 13 on the corrected image 20a and analyzing the non-shielded area to obtain a monitoring furnace area 22.
Image matching refers to a method of finding similar image objects by corresponding relationships to image contents, features, structures, relationships, textures, gray levels, and the like. Namely, after the monitoring image 20 is matched with the template image 10, a correction image 20a for eliminating the influence of image acquisition device shake, furnace tube swing or furnace wall vibration is obtained.
In this embodiment, the matching area 12 includes a furnace tube pixel point, that is, the matching area 12 includes an image area of a furnace tube image, so that in step K2, a monitoring matching area on the monitoring image 20 that is close to or consistent with the image of the template image matching area 12 can be obtained, and thus a correction image 20a with a high overlap ratio between the furnace tube image area and the furnace tube image area on the template image 10 can be obtained, so that the furnace tube is prevented from being mistakenly shielded when swinging to the interference area 13 on the template image 10, and the accuracy of identifying the furnace tube influence area in the furnace tube swinging state is ensured.
The interference region 13 is composed of pixels with small difference in pixel information between the pixels in the non-furnace tube and the pixels in the furnace tube. The pixel information includes information such as gray value, contrast, brightness, etc. of the pixel point, and if the difference between the pixel information values of the non-furnace tube pixel point and the furnace tube pixel point is small, it is difficult to apply algorithm segmentation to obtain an accurate furnace tube image and a non-furnace tube image. Therefore, the interference area 13 of the misjudgment-prone area on the image is marked first, and then the interference area 13 in the monitoring image 20 is shielded to carry out furnace tube identification operation in the monitoring working state, so that the accuracy of furnace tube identification can be improved, and the processing amount in the identification process can be reduced to improve the analysis rate.
Since the jitter amplitude of the image acquisition device or the furnace tube is small and is integral jitter, the jitter influence can be eliminated only by translation, so that the monitoring image 20 and the template image 10 are matched by applying a template matching method in the embodiment. The template is a known small image, the template matching is to search for a target in a large image, the target to be found in the image is known, the target and the template have the same size, direction and image elements, and the target can be found in the image through an algorithm to determine the coordinate position of the target. Template matching has its own limitations, mainly in that it can only do parallel translation, if the matching target in the original image rotates or changes in size, the algorithm is invalid. The matching method of the monitoring image 20 and the template image 10 in the embodiment is specifically as follows:
a template matching algorithm is used to match the monitored image 20 to the matching region 12,
defining the width W and the height H of the monitoring image 20, setting the maximum offset (xmax, ymax), traversing the monitoring image 20 to solve an objective function
Displacement at minimum
，
Wherein,
for the coordinates of a certain pixel point in the matching region 12 on the standard image 10,
for the pixel value of a pixel in the matching region 12,
for monitoring the image 20
A pixel value of the location;
each coordinate of the monitored image 20 plus the dither displacement amplitude
Resulting in a corrected image 20a.
K3, removing the edge of the monitoring furnace area 22 to obtain the monitoring analysis area 23.
The monitoring furnace area 22 is a furnace tube image area in the monitoring image 20/the correction image 20a, and the pixel information of the edge pixel points is greatly influenced by the furnace wall, so that the actual temperature of the furnace body cannot be accurately reflected, and the accuracy of the analysis result is influenced. The monitoring analysis area 23 obtained by removing the pixel points at the edge of the monitoring furnace tube area 22 is compared with the pixel information of the pixel points of the furnace tube at the same position in the template image 10 in each pixel point of the furnace tube in the monitoring analysis area 23, so that the comparison analysis data amount is small, the accuracy of the analysis result is higher, the false alarm can be reduced, and the false alarm can not be caused under the condition of continuous monitoring.
In this embodiment, after the binarization processing and the segmentation are performed on the monitor image 20 in step K2 to obtain the furnace tube image, the process proceeds to step K3. In step K3, the edge of the monitoring furnace tube region 22 is processed by applying the etching operation of morphological image processing, so that the bulge of the edge of the monitoring furnace tube region 22 can be eliminated, and the monitoring analysis region 23 with smoother edge can be obtained. In other embodiments, other algorithms may be applied to remove the edge of the monitoring furnace region 22 to eliminate the influence of the region edge image on the temperature measurement result.
Example 2
The present embodiment is different from embodiment 1 in that the monitored furnace zone area 22 is obtained by removing the image area corresponding to the interference area 13 after analyzing the monitored image 20 or the corrected image 20a in step K2. Namely, the monitoring image 20 or the correction image 20a is analyzed, and then the image area corresponding to the interference area 13 in the identified image area is removed, so that the adverse effect on the image identification effect when the interference area 13 is shielded for image analysis can be avoided, and the reliability of furnace tube area identification is ensured.
Example 3
In this embodiment, in step K1, the furnace tube image 10 is obtained first, and the template image 10 is obtained based on the analysis and calculation of the furnace tube image 10 or the furnace tube image 10 when the furnace tube is in the normal operating state is selected as the template image 10. That is, the furnace tube temperature of each furnace tube in the template image 10 is the temperature of the furnace tube in the normal working state, so that the furnace tube pixel points of the monitoring analysis area 23 and the collocated pixel points on the template image 10 can be compared one by one in the monitoring working state to calculate the temperature change condition of the furnace tube pixel points. The co-located pixels refer to pixels forming the images at the co-located positions of the furnace tubes in each furnace tube image 10.
The template image 10 may be computed based on the analysis of the furnace tube image 10. For example, in a normal operating state of the furnace tube, the fixedly installed image capturing device obtains a plurality of furnace tube images 10, matches each furnace tube image 10, calculates the maximum/average temperature value of the pixel points of each co-located furnace tube, and uses the maximum/average temperature value of the pixel points of each furnace tube to draw the template image 10. Or after identifying the furnace tube image in the furnace tube image 10, manually calibrating the template temperature values of the furnace tube pixel points forming the furnace tube image and drawing the template image 10, wherein the template temperature values can be obtained according to the historical temperature records of the furnace tube, for example, the maximum value in the historical temperature data of the furnace tube region where the furnace tube pixel points are marked is the template temperature value. Or directly selecting the furnace tube image 10 when the furnace tube is in the normal working state as the template image 10.
To facilitate analysis of the furnace tube temperature, keypoints 11 are calibrated on the template image 10. The key points 11 are small graphic areas, and are marked according to experience or temperature measurement requirements and are consistent with the actual monitoring area selected on the tube body of the furnace tube.
The specific marking method of the interference area 13 in this embodiment is as follows:
in step K1, the furnace tube image 10 is analyzed to obtain a preliminary identification image, non-furnace tube pixel points identified as furnace tubes on the preliminary identification image are manually marked, and the marked non-furnace tube pixel points form the interference region 13. That is, the interference region 13 is composed of a set of non-furnace pixel points that are identified as furnace pixel points during algorithm segmentation. In step K2, the same algorithm is applied to identify the monitored image 20 after the interference region 13 is masked, so that the monitored furnace tube region 22 more consistent with the preliminary identified image can be obtained, which is beneficial to the analysis of the furnace tube temperature.
For example, the salix method is applied to binarize the plurality of furnace tube images 10 to obtain corresponding preliminary identification images. The preliminary identification image is shown in fig. 2, in which the white regions are identified as furnace tubes and the black regions are identified as non-furnace tubes. It can be known from fig. 1 that the non-furnace tube region identified as the furnace tube includes the tuyere image exposed from the gap between the furnace tube bodies and the furnace wall images located at the left and right lower corners of the image. For the convenience of analysis, the tuyere image region exposed from the furnace tube gap and the furnace wall image region located below the furnace tube image are marked as interference regions 13 in this embodiment.
As shown in fig. 1 and 2, the ohr method divides an image into a background part and a foreground part with the largest inter-class variance according to the gray characteristics of the image. In other embodiments, the interference region 13 may also be marked based on color, intensity, etc. pixel information.
Claims (6)
1. A furnace tube temperature monitoring method comprises the following steps:
A. acquiring temperature values of all positions of a furnace tube under a normal working state to form a template image (10);
calibrating a matching region (12) and an interference region (13) on the template image (10), wherein the matching region (12) comprises furnace tube pixel points, and the interference region (13) consists of pixel points with small pixel information difference from the furnace tube pixel points in non-furnace tube pixel points;
B. the image acquisition device acquires a monitoring image (20) in a monitoring working state, and identifies a furnace tube image in the monitoring image (20), wherein the furnace tube image consists of furnace tube pixel points;
the monitoring image (20) is matched with the matching area (12) on the template image (10) to obtain a corrected image (20 a), the image acquisition device or the furnace tube is integrally shaken, the shaking influence can be eliminated through translation, and the template matching algorithm is adopted to match the monitoring image (20) with the matching area (12) to obtain the shaking displacement amplitude
Monitoring each coordinate of the image (20) plus the dither displacement amplitude
Obtaining a corrected image (20 a);
the corrected image (20 a) is provided with a monitoring matching area which is consistent with the image of the matching area (12) on the template image (10), then the pixel information of the area which is consistent with the interference area (13) on the corrected image (20 a) is shielded, and the non-shielded area of the corrected image (20 a) is analyzed to obtain the furnace tube image in the monitoring image (20);
C. comparing the temperature value of each furnace tube pixel point in the monitoring image (20) with the temperature value of the same position of the template image (10),
if the temperature value of a certain furnace tube pixel point in the monitoring image (20) is larger than the temperature value of the corresponding point position in the template image (10), the difference of the two temperature values at the point position is recorded as a temperature rise change value,
if the temperature value of a certain furnace tube pixel point in the monitoring image (20) is less than or equal to the temperature value of the corresponding point position in the template image (10), the temperature rise change value of the point position is not counted,
recording the temperature rise change value of the nth pixel point as
Substituting the formula to obtain a temperature rise index R,
wherein N is the total number of pixels constituting the furnace tube image in the monitoring image (20),
and when the temperature rise index exceeds a set threshold value, the monitoring system sends out a warning instruction.
2. The furnace tube temperature monitoring method of claim 1, wherein: in the step C, the temperature rise index of the furnace chamber is obtained according to the temperature information of all the furnace tubes in the furnace chamber, and a temperature rise index change graph is drawn by taking time as a horizontal axis and the temperature rise index of the furnace chamber as a vertical axis;
and marking the temperature rise condition at the furnace tube image according to the temperature rise value on the corresponding monitoring image (20).
3. The furnace tube temperature monitoring method of claim 1, wherein: and D, comparing the total number of pixels with the temperature exceeding a set threshold value in the monitoring image (20) with the total number of pixels forming the furnace tube image in the monitoring image (20) to obtain the heat proportion of the corresponding furnace tube, and drawing a hot spot proportion trend graph by taking time as a horizontal axis and the heat proportion as a vertical axis.
4. The furnace tube temperature monitoring method of claim 1, wherein: in the step A, under the normal working state of the furnace tube, a plurality of furnace tube images are obtained by a fixedly installed image acquisition device, and the furnace tube images comprise furnace tube pixel points forming furnace tube images; and matching the furnace tube images, calculating the maximum value/average value of the temperature of the pixel point of each co-located furnace tube and drawing a template image (10).
5. The furnace tube temperature monitoring method of claim 1, wherein: in the step A, the fixedly installed image acquisition device acquires a furnace tube image, identifies the furnace tube image in the furnace tube image, calibrates the template temperature value of each furnace tube pixel point forming the furnace tube image and draws a template image (10).
6. The furnace tube temperature monitoring method of claim 1, wherein: the step A comprises marking key points (11) on the template image (10) according to target monitoring points on the furnace tube,
in the step B, comparing key points (11) on the template image (10) to position monitoring key points (21) on the monitoring image (20);
the method also comprises the following steps of,
e1, forming longitudinal key point groups by using the monitoring key points (21) at different tube passes on the same furnace tube, calculating the standard deviation of the temperature values of the monitoring key points (21) in each longitudinal key point group to obtain the longitudinal uniformity of the furnace tube, and drawing a schematic diagram of the longitudinal uniformity of the furnace tube by taking the transverse arrangement sequence of each furnace tube as a transverse axis and the longitudinal uniformity of each furnace tube as a longitudinal axis;
e2, forming monitoring key points (21) of different furnace tubes at the same height into a transverse key point group, and drawing a furnace tube transverse uniformity schematic diagram by taking the transverse arrangement sequence of each monitoring key point (21) as a transverse axis and the temperature value of each monitoring key point (21) as a longitudinal axis;
calculating the standard deviation of the temperature values of the monitored key points (21) in each transverse key point group to obtain the transverse uniformity of the corresponding transverse key point group and marking the transverse uniformity schematic diagram of the furnace tube;
e3, obtaining the average value of all the monitoring key points (21) to obtain the current temperature, and drawing the temperature trend curve chart of the furnace chamber by taking time as a horizontal axis and the current temperature values of the key points as a vertical axis.
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| RU2139482C1 (en) * | 1998-03-12 | 1999-10-10 | Открытое акционерное общество "Комбинат Магнезит" | Method of control of raw material roasting process in rotary furnace |
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| CN105042599A (en) * | 2015-06-18 | 2015-11-11 | 惠州东江威立雅环境服务有限公司 | Security monitoring and emergency processing method of incinerator rotary kiln |
| US10546207B2 (en) * | 2016-04-11 | 2020-01-28 | North Carolina Agricultural And Technical State University | Normalized defect characterization of pulse thermographic nondestructive evaluation |
| CN107025648A (en) * | 2017-03-20 | 2017-08-08 | 中国人民解放军空军工程大学 | A kind of board failure infrared image automatic testing method |
| CN107271044B (en) * | 2017-05-03 | 2020-10-23 | 北京海顿中科技术有限公司 | Thermal imaging temperature monitoring device and method |
| KR20190041678A (en) * | 2017-10-13 | 2019-04-23 | 삼성전자주식회사 | Semiconductor chips inspection apparatus |
| WO2019213279A1 (en) * | 2018-05-03 | 2019-11-07 | Quantum IR Technologies, LLC | Infrared imaging systems and methods for oil leak detection |
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| CN110487414A (en) * | 2019-08-16 | 2019-11-22 | 云南电网有限责任公司电力科学研究院 | Breaker temperature monitoring method and system based on infrared image technology |
| CN110648489B (en) * | 2019-09-11 | 2021-01-26 | 国网山东省电力公司 | Storehouse early warning system based on infrared thermal imaging ignition point identification |
| CN111862019B (en) * | 2020-07-11 | 2023-04-11 | 北京唯实兴邦科技有限公司 | Intelligent detection and fault diagnosis method for thermoelectric and photoelectric soft multidimensional information fusion circuit |
| CN113108921B (en) * | 2021-04-19 | 2023-11-24 | 巴斯夫新材料有限公司 | Method, device and system for monitoring the temperature of a subject |
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