CN115830106A - Auxiliary positioning method for electrified cleaning of machine room equipment - Google Patents
Auxiliary positioning method for electrified cleaning of machine room equipment Download PDFInfo
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Abstract
The invention relates to the technical field of image data processing, in particular to an auxiliary positioning method for electrified cleaning of machine room equipment, which comprises the following steps: acquiring a target thermal infrared image of equipment in a machine room to be cleaned, and determining a gray level histogram of the target thermal infrared image; processing image data of the gray level histogram, and determining a self-adaptive cutting threshold value; screening out a highlight pixel point set from the target thermal infrared image; screening and growing the highlight pixel points; screening edge pixel points from a heat source area and a radiation range area, and determining a radiation length set; screening a heat radiation area set to be cleaned from the heat radiation area set; and determining target cleaning position information corresponding to equipment in the machine room to be cleaned, and cleaning the position corresponding to the target cleaning position information. The invention improves the accuracy of cleaning the machine room equipment by processing the data of the target thermal infrared image, and is mainly applied to cleaning the machine room equipment.
Description
Technical Field
The invention relates to the technical field of image data processing, in particular to an auxiliary positioning method for electrified cleaning of machine room equipment.
Background
In recent years, abnormal operation of equipment in a machine room is caused by surface pollution, and the surface pollution is one of main hazards influencing the working state of the equipment in the machine room and becomes an inevitable potential safety hazard of the machine room. Among these, surface contamination may include, but is not limited to: dust, soot, moisture, accumulated static electricity, and various charged particles. When the surface attached to the machine room equipment is polluted more, the temperature of the machine room equipment during operation is often hotter, the machine room equipment is prone to failure, and potential safety hazards are caused. Therefore, machine room equipment is often required to be cleaned, and the electrified cleaning is a common method for cleaning the machine room equipment. At present, when the machine room equipment is cleaned, the mode generally adopted is as follows: the infrared thermal imaging sensor is used for shooting images of the machine room equipment, identifying the temperature of the machine room equipment and cleaning the machine room equipment according to the temperature of the machine room equipment.
However, when the above-described manner is adopted, there are often technical problems as follows:
cause the factor that computer lab equipment generates heat often not only this computer lab equipment upper surface pollution's increase, still can be the generating heat that computer lab equipment used for a long time and caused, consequently, only according to the temperature of computer lab equipment, often be difficult to pinpoint to treat abluent surface pollution region on this computer lab equipment to it is low often to lead to carrying out abluent degree of accuracy to computer lab equipment, and then leads to the waste of clean resource.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
The invention provides an auxiliary positioning method for electrified cleaning of machine room equipment, and aims to solve the technical problem that the accuracy of cleaning of the machine room equipment is low.
The invention provides an auxiliary positioning method for electrified cleaning of equipment in a machine room, which comprises the following steps:
acquiring a target thermal infrared image of equipment in a machine room to be cleaned, and determining a gray level histogram of the target thermal infrared image;
processing image data of the gray level histogram, and determining a self-adaptive cutting threshold value;
screening out a highlight pixel point set from the target thermal infrared image according to a self-adaptive cutting threshold value;
screening and growing the highlight pixel points in the highlight pixel point set to obtain a heat radiation area set, wherein the heat radiation area in the heat radiation area set comprises: a heat source region and a radiation range region;
for each heat radiation area in the heat radiation area set, screening edge pixel points from a heat source area and a radiation range area which are included in the heat radiation area, and determining a radiation length set corresponding to the heat radiation area according to the screened edge pixel points;
screening a heat radiation area set to be cleaned from the heat radiation area set according to a heat source area included in each heat radiation area in the heat radiation area set and a radiation length set corresponding to the heat radiation area;
and determining target cleaning position information corresponding to the equipment of the machine room to be cleaned according to the set of the heat radiation areas to be cleaned, and cleaning the position corresponding to the target cleaning position information.
Further, the processing the image data of the gray histogram and determining the adaptive cutting threshold includes:
determining an average brightness index and a deviation brightness index according to the gray level histogram;
determining the ratio of the average brightness index to the biased brightness index as an integral biased brightness index;
when the integral deviation brightness index is larger than or equal to a preset brightness uniformity value, determining the deviation brightness index as a self-adaptive cutting threshold value;
and when the overall deviation brightness index is smaller than the brightness uniformity value, determining the average brightness index as a self-adaptive cutting threshold value.
Further, the determining an average brightness index and a biased brightness index according to the gray histogram includes:
determining the gray value at the target position in the gray histogram as an average brightness index, wherein the absolute value of the difference between the number of pixels before the target position and the number of pixels after the target position is less than a preset number threshold;
and determining half of the maximum gray value in the gray histogram as a deviation brightness index.
Further, the screening out a set of highlight pixel points from the target thermal infrared image according to a self-adaptive cutting threshold value includes:
and determining pixel points with the gray value larger than or equal to the self-adaptive cutting threshold value in the target thermal infrared image as highlight pixel points.
Further, the screening, growing and processing the highlight pixels in the highlight pixel set to obtain a heat radiation area set includes:
carrying out median filtering on the highlight pixel points in the highlight pixel point set to obtain a filtering value corresponding to the highlight pixel points;
when the filtering value corresponding to the highlight pixel point is equal to the gray value corresponding to the highlight pixel point, determining the highlight pixel point as a seed pixel point;
determining a range value corresponding to the seed pixel point according to a preset target window corresponding to the seed pixel point;
performing region growth according to the corresponding range values of the seed pixel points to obtain a target region set;
determining the mean value of the gray values corresponding to the pixel points in each target region in the target region set as the gray mean value corresponding to the target region;
screening a target area group set of a preset target arrangement mode from the target area set, wherein each target area group in the target area group set comprises two target areas;
and for each target area group in the target area group set, determining a target area with a larger gray mean value in the target area group as a heat source area, determining a target area with a smaller gray mean value in the target area group as a radiation range area, and determining an area where two target areas in the target area group are located as a heat radiation area.
Further, the step of screening out edge pixel points from a heat source area and a radiation range area included in the heat radiation area, and determining a radiation length set corresponding to the heat radiation area according to the screened out edge pixel points includes:
determining edge pixel points screened from a heat source area included in the heat radiation area as heat source edge pixel points to obtain a heat source edge pixel point set corresponding to the heat radiation area;
determining edge pixel points screened from a radiation range area included in the heat radiation area as radiation edge pixel points to obtain a radiation edge pixel point set corresponding to the heat radiation area;
determining a centroid of a heat source area included in the heat radiation area as a centroid corresponding to the heat radiation area;
connecting each heat source edge pixel point in the heat source edge pixel point set corresponding to the heat radiation region with the centroid corresponding to the heat radiation region to obtain a heat source line segment set corresponding to the heat radiation region;
for each heat source line segment in the heat source line segment set corresponding to the heat radiation area, extending one end of the heat source line segment where a heat source edge pixel point is located until the heat source line segment intersects with a radiation edge pixel point in the radiation edge pixel point set corresponding to the heat radiation area to obtain an intersection point, and taking a line segment between a centroid in the heat source line segment and the intersection point as the heat radiation line segment corresponding to the heat source line segment;
and determining the difference value between the length of the heat radiation line segment corresponding to the heat source line segment and the length of the heat source line segment as the radiation length for each heat source line segment in the heat source line segment set corresponding to the heat radiation area.
Further, the screening out a set of thermal radiation regions to be cleaned from the set of thermal radiation regions according to a set of radiation lengths corresponding to the thermal radiation regions and the heat source regions included in each thermal radiation region in the set of thermal radiation regions includes:
determining an identification index to be cleaned corresponding to each heat radiation region according to the heat source region included in each heat radiation region in the heat radiation region set and the radiation length set corresponding to the heat radiation region;
and screening a heat radiation area set to be cleaned from the heat radiation area set according to a preset threshold value to be cleaned and identification indexes to be cleaned corresponding to each heat radiation area in the heat radiation area set.
Further, the formula for determining the identification index to be cleaned corresponding to the heat radiation area is as follows:
wherein F is the identification index to be cleaned corresponding to the heat radiation area,th() Is a function of the hyperbolic tangent,Nis the number of gradation values in the heat source region included in the heat radiation region,vis a number of gradation values in a heat source region included in the heat radiation region,
is that the corresponding gray value in the heat source region included in the heat radiation region is equal to the second gray valuevThe number of pixels of each gray value,His the number of pixel points in the heat source region included in the heat radiation region,ln() Is a logarithmic function with a natural constant as a base number,
is the standard deviation of the radiation lengths in the set of radiation lengths corresponding to the heat radiation area,
in order to take the euclidean norm function,
in order to take the function of the absolute value,AandBis a numerical value that is set in advance,
is an average value of gray values corresponding to pixel points in a heat radiation region included in the heat radiation region,
is the maximum value among the gradation values corresponding to the pixel points in the heat radiation region included in the heat radiation region.
Further, according to a preset threshold value to be cleaned and a to-be-cleaned identification index corresponding to each heat radiation area in the heat radiation area set, a to-be-cleaned heat radiation area set is screened from the heat radiation area set, and the method includes the following steps:
and when the identification index to be cleaned corresponding to the heat radiation area in the heat radiation area set is smaller than or equal to the threshold value to be cleaned, determining the heat source area included in the heat radiation area as the heat radiation area to be cleaned.
Further, the determining, according to the set of to-be-cleaned heat radiation areas, target cleaning position information corresponding to the to-be-cleaned machine room device includes:
and combining the positions of all the heat radiation areas to be cleaned in the heat radiation area set to be cleaned into target cleaning position information corresponding to the equipment of the machine room to be cleaned.
The invention has the following beneficial effects:
according to the auxiliary positioning method for electrified cleaning of the machine room equipment, the technical problem that the accuracy of cleaning the machine room equipment is low is solved by processing the data of the target thermal infrared image, and the accuracy of cleaning the machine room equipment is improved. First, surface contamination that adheres to equipment in a room, which may be contamination to be cleaned, tends to cause the equipment to heat up. Therefore, the target thermal infrared image of the equipment room to be cleaned generated based on the thermal radiation is acquired, and the subsequent positioning of the surface pollution attached to the equipment room to be cleaned can be facilitated. Then, the machine room equipment is prone to generate heat due to surface contamination attached to the machine room equipment, and when a heat-generating area and an unheated area of the machine room equipment are displayed on the target thermal infrared image, the brightness of the heat-generating area and the brightness of the unheated area are different from the gray value corresponding to the gray histogram. Further, when the heat of the heat generation region is different, the luminance and the gradation value corresponding to the gradation histogram are often different. Therefore, the self-adaptive cutting threshold is determined through the gray level histogram, and whether the areas with different heating degrees are the areas to be cleaned or not can be conveniently distinguished in the follow-up process. Then, the surface contamination attached to the machine room equipment often causes the machine room equipment to generate heat, and the heat is often corresponding to the pixel points with higher gray scale values in the target thermal infrared image. Therefore, the highlight pixel point set is screened out, and the subsequent positioning of the surface pollution area on the machine room equipment can be facilitated. And subsequently, only the highlight pixel point set needs to be processed, so that the redundant calculation amount can be reduced, and the occupation of calculation resources is reduced. Continuing, the heat source tends to have a range of radiation to the surroundings. The heat source area may often be a surface contamination area. The radiation range region is often the region where the heat source radiates the surroundings. Therefore, distinguishing the heat source area and the radiation range area can prevent the heat source area and the radiation range area from being entirely regarded as the surface contamination area, and the surface contamination area can be further accurately positioned. Then, when the machine room equipment normally operates, the range of the heat radiation from the edge of the heat source area to the periphery is often uniform, that is, the difference of the radiation lengths in the radiation length set corresponding to the heat radiation area is often small. However, surface contaminants (e.g., dust) tend to randomly accumulate on the machinery of the room and often vary in bulk density. When the stacking density is different, the interference degree on the internal circuit of the machine room equipment is different, so that the machine room equipment generated by dust accumulation is overheated, the difference of the heat radiation range from the edge of the heat source area to the periphery is more, namely, the difference of the radiation lengths in the radiation length set corresponding to the heat radiation area is larger. Therefore, the radiation length set corresponding to the heat radiation area is determined, and whether the heat source area included in the heat radiation area is the surface pollution area to be cleaned or not can be conveniently judged subsequently. And finally, determining target cleaning position information corresponding to the equipment in the machine room to be cleaned according to the set of the heat radiation areas to be cleaned, and cleaning the position corresponding to the target cleaning position information. The heat source area included in the heat radiation area to be cleaned in the heat radiation area set to be cleaned is often the surface contamination area to be cleaned, so the position of the heat source area included in the heat radiation area to be cleaned is often the position to be cleaned. Therefore, the invention solves the technical problem of low accuracy of cleaning the machine room equipment by processing the data of the target thermal infrared image, improves the accuracy of cleaning the machine room equipment and can avoid the waste of cleaning resources.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of an auxiliary positioning method for electrified cleaning of equipment in a machine room according to the invention;
FIG. 2 is a schematic diagram of a target arrangement according to the present invention;
fig. 3 is a schematic view of a heat source line segment and a radiation line segment according to the present invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of the embodiments, structures, features and effects of the technical solutions according to the present invention will be given with reference to the accompanying drawings and preferred embodiments. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides an auxiliary positioning method for electrified cleaning of equipment in a machine room, which comprises the following steps:
acquiring a target thermal infrared image of equipment in a machine room to be cleaned, and determining a gray level histogram of the target thermal infrared image;
processing image data of the gray level histogram, and determining a self-adaptive cutting threshold;
screening out a highlight pixel point set from the target thermal infrared image according to a self-adaptive cutting threshold;
screening and growing the highlight pixel points in the highlight pixel point set to obtain a heat radiation area set;
for each heat radiation area in the heat radiation area set, screening edge pixel points from a heat source area and a radiation range area which are included in the heat radiation area, and determining a radiation length set corresponding to the heat radiation area according to the screened edge pixel points;
screening a heat radiation region set to be cleaned from the heat radiation region set according to a heat source region included in each heat radiation region in the heat radiation region set and a radiation length set corresponding to the heat radiation region;
and determining target cleaning position information corresponding to the equipment of the machine room to be cleaned according to the set of the heat radiation areas to be cleaned, and cleaning the position corresponding to the target cleaning position information.
The following steps are detailed:
referring to fig. 1, a flow of some embodiments of an auxiliary positioning method for live cleaning of equipment in a machine room according to the present invention is shown. The auxiliary positioning method for electrified cleaning of machine room equipment comprises the following steps:
s1, obtaining a target thermal infrared image of equipment in a machine room to be cleaned, and determining a gray level histogram of the target thermal infrared image.
In some embodiments, a target thermal infrared image of equipment in a machine room to be cleaned may be obtained, and a gray level histogram of the target thermal infrared image may be determined.
The equipment in the machine room to be cleaned can be equipment in the machine room to be cleaned. For example, the equipment room to be cleaned may be a cabinet. The target thermal infrared image may be an image after image preprocessing. Image pre-processing may include, but is not limited to: graying, denoising and image enhancement.
As an example, this step may include the steps of:
firstly, a thermal infrared scanner (thermal infrared imager) is used for acquiring a thermal infrared image of equipment in a machine room to be cleaned.
And secondly, filtering and denoising the thermal infrared image to obtain a denoised image.
For example, the filtering denoising may be a 5 × 5 mean filtering denoising.
In actual conditions, complex electromagnetic interference is often received under the computer lab environment, and electromagnetic signals often can form interference to equipment through modes such as conduction, induction, radiation, so often can make hot infrared image produce a large amount of gaussian noises when hot infrared scanner gathers the image, and hot infrared image is the low frequency information mostly, consequently, often does not need too meticulous filtering parameter adjustment when carrying out the filtering and de-noising, can adopt 5 x 5's mean value filtering to de the noise.
And thirdly, graying the denoised image to obtain a target thermal infrared image.
Because the thermal infrared image is often a single-color image, the thermal infrared image after noise reduction can be grayed for convenience of calculation and reduction of image saturation and other redundant information.
In the actual conditions, present server and network equipment often all can produce a lot of heats at the operation in-process, in order to distribute away these heats, can adopt the mode heat of discharging of initiative heat dissipation usually, because the space of computer lab is narrow and small, these equipment adopt forced air cooling's mode to dispel the heat usually, and the louvre often brings the dust into computer lab equipment inside with the air-assisted of convection current. Dust often can carry moisture and corrosive substance along with get into computer lab equipment inside, cover on electronic component, cause electronic component heat-sinking capability to descend, accumulate a large amount of heats for a long time often can lead to equipment operation unstability. When a maintainer uses a special cleaning agent to perform charged cleaning, the cleaning difficulty is often high because dust at the dead angle inside equipment (such as a cabinet) of a machine room is difficult to observe. The infrared thermal imager carried by the temperature abnormity alarm system installed in the machine room can detect the specific heating position of the machine room equipment, the more positions of dust adhesion are easy to heat, and then the dust adhesion dead angles can be accurately positioned by utilizing the thermal infrared image, but the thermal infrared image is based on thermal radiation imaging, so that a radiation range exists around the heat source, the boundary of the heat source is fuzzy, the position of the heat source cannot be accurately positioned, and the accumulated heat of the heat source is difficult to judge because of dust accumulation or other reasons, wherein the temperature abnormity alarm system is generally installed at the top of the machine room. Therefore, the invention can reduce redundant calculation by cutting the target thermal infrared image in gray scale, set seed pixel points and growth rules for the cut image by using median filtering to realize segmentation of fuzzy regions, obtain heat source regions, construct a formula for determining the identification indexes to be cleaned, distinguish heat source forming reasons, accurately position dust accumulation regions, enable the electrified cleaning of machine room equipment to be more efficient, and save clean resources.
And S2, processing image data of the gray level histogram and determining a self-adaptive cutting threshold value.
In some embodiments, the gray histogram may be subjected to image data processing to determine an adaptive cut threshold.
Wherein the adaptive clipping threshold may be an adaptive luminance clipping threshold.
As an example, this step may include the steps of:
firstly, determining an average brightness index and a deviation brightness index according to the gray level histogram.
For example, this step may include the following sub-steps:
the first substep determines the gray value at the target position in the gray histogram as an average brightness index.
The absolute value of the difference between the number of pixels before the target position and the number of pixels after the target position may be smaller than a preset number threshold. The target position may be a center position of a previously set gray histogram. For example, the position of the last pixel point in half of the pixel points in the gray histogram is located. The quantity threshold may be a preset quantity. For example, the quantity threshold may be 2.
For example, the number of pixel points in the target thermal infrared image may be 50. The gray histogram may include: 10 pixels with the gray value of 100, 20 pixels with the gray value of 180 and 20 pixels with the gray value of 200. The target position may be a position where a 25 th pixel point from left to right in the gray histogram is located. The position of the 25 th pixel point from left to right in the gray level histogram may be the position of the pixel point with the gray level value of 180. The average brightness index may be 180.
As another example, the average luminance indicator may be counted from left to right on the gray histogram to
At a gray level at which, among other things,Gis the number of pixel points in the target thermal infrared image.
A second substep of determining half of the maximum gradation value in the gradation histogram as a biased brightness index.
For example, the formula for determining the biased brightness index may be:
wherein,
is a biased luminance indicator.
Is the largest gray value in the gray histogram.
In practical cases, the maximum gray value in the gray histogram
The larger the index is, the more biased the brightness index is
The larger.
And secondly, determining the ratio of the average brightness index to the biased brightness index as an integral biased brightness index.
For example, the formula for determining the overall bias brightness index may be:
wherein,Kis an overall biased luminance index.
Is flatThe average brightness index.
Is a biased brightness indicator.
In the actual case, it is necessary, because,
can be characterized as counting from left to right on the gray histogram to
At a gray level at which, among other things,Gis the number of pixel points in the target thermal infrared image.
May be half the maximum gray value in the gray histogram. Therefore, when
In the process, the center of gravity of the target thermal infrared image is biased to the highlight gray level, and the highlight area on the target thermal infrared image is more. When in use
In this case, it may be represented that the center of gravity of the target thermal infrared image is biased toward the gray level of dark, or that there are fewer highlight areas on the target thermal infrared image.
And thirdly, when the integral deviation brightness index is larger than or equal to a preset brightness uniform value, determining the deviation brightness index as a self-adaptive cutting threshold value.
Wherein the brightness uniformity value may be a preset value. For example, the luminance uniformity value may be 1.
And fourthly, when the overall deviation brightness index is smaller than the brightness uniformity value, determining the average brightness index as a self-adaptive cutting threshold value.
And S3, screening out a highlight pixel point set from the target thermal infrared image according to the self-adaptive cutting threshold.
In some embodiments, the set of highlighted pixel points may be screened from the target thermal infrared image according to a self-adaptive cut threshold.
As an example, a pixel point in the target thermal infrared image whose gray value is greater than or equal to the adaptive cutting threshold may be determined as a highlight pixel point. The corresponding gray value of the pixel point with the gray value smaller than the adaptive cutting threshold value in the target thermal infrared image can be set to be 0.
And S4, screening and growing the highlight pixel points in the highlight pixel point set to obtain a heat radiation area set.
In some embodiments, the highlight pixel points in the highlight pixel point set may be subjected to a screening growth process to obtain a heat radiation region set.
Wherein the heat radiation region in the set of heat radiation regions may include: a heat source region and a radiation range region. The heat source region may be a region where the heat source is located. The radiation range region may be a region where the heat source region radiates outward.
As an example, this step may include the steps of:
the method comprises the following steps of firstly, carrying out median filtering on highlight pixel points in the highlight pixel point set to obtain filtering values corresponding to the highlight pixel points.
For example, 5 × 5 median filtering may be performed on the highlighted pixel, so as to obtain a filtering value corresponding to the highlighted pixel.
In practical situations, the reason for adopting the median filtering is that when an isolated highlight pixel is located in the center of the 5 × 5 window, since there are no or only a few other highlight pixels around the highlight pixel, the filtering value corresponding to the highlight pixel is often 0. Isolated highlight pixel points are often not pixel points in a heat source area or a radiation range area, so the isolated highlight pixel points can be avoided by adopting median filtering. When the highlight pixel is located in the center of the 5 × 5 window, if there are more other highlight pixels in the 5 × 5 window, the filter value corresponding to the highlight pixel is often not 0.
And secondly, when the filtering value corresponding to the highlight pixel point is equal to the gray value corresponding to the highlight pixel point, determining the highlight pixel point as a seed pixel point.
In an actual situation, the gray values corresponding to the pixels in the heat source region or the radiation range region are often stable, that is, the gray values corresponding to the pixels in the heat source region or the radiation range region are often not changed much, so that when the filter value corresponding to the highlight pixel point is equal to the gray value corresponding to the highlight pixel point, the highlight pixel point is stable and may be a pixel in the heat source region or the radiation range region, and therefore, the seed pixel point may be a pixel in the heat source region or the radiation range region.
And thirdly, determining a corresponding range value of the seed pixel point according to a preset target window corresponding to the seed pixel point.
Wherein the target window may be a preset window. For example, the target window may be a 5 × 5 window.
For example, the maximum gray value and the minimum gray value may be screened from the target window corresponding to the seed pixel point, and the difference between the maximum gray value and the minimum gray value is determined as the range value corresponding to the seed pixel point.
And fourthly, performing region growing according to the corresponding polarization value of each seed pixel point to obtain a target region set.
For example, when the absolute value of the difference between the gray value corresponding to the seed pixel point and the gray value corresponding to the adjacent pixel point is less than or equal to the extreme difference corresponding to the seed pixel point, the two pixel points may be grown into the same region. That is, the range corresponding to the seed pixel point can be used as the growth rule of the seed pixel point. When a plurality of seed pixel points in the same region are grown, respective growth rules are often compatible with each other. If the growth rules are very different, the growth will be stopped and an edge will be formed.
And fifthly, determining the mean value of the gray values corresponding to the pixel points in each target area in the target area set as the mean value of the gray values corresponding to the target area.
And sixthly, screening out a target area group set of preset target arrangement modes from the target area set.
Wherein each target zone group in the set of target zone groups comprises two target zones. The arrangement of the targets may be such that there is an edge overlap of the two target regions. The target arrangement mode may be that the relation of the connected domains of the two target areas is an inclusion relation.
As shown in fig. 2, 3 target area groups can be obtained. Wherein the area where the two concentric circles are located may represent a target area group. The area in which the two concentric rectangles are located may represent a group of target areas. The area in which the two concentric ellipses are located may represent a target area group. The smaller of the two concentric circles may characterize the target area and the area between the two concentric circles may characterize the target area. The smaller of the two concentric rectangles may characterize the target region, and the region between the two concentric rectangles may characterize the target region. The smaller of the two concentric ellipses may characterize the target region, and the region between the two concentric ellipses may characterize the target region. Fig. 2 may be used as a schematic diagram of the target arrangement.
And seventhly, determining the target area with larger gray mean value in the target area group as a heat source area, determining the target area with smaller gray mean value in the target area group as a radiation range area, and determining the areas where the two target areas in the target area group are located as heat radiation areas for each target area group in the target area group set.
And S5, screening edge pixel points from a heat source region and a radiation range region included in the heat radiation region for each heat radiation region in the heat radiation region set, and determining a radiation length set corresponding to the heat radiation region according to the screened edge pixel points.
In some embodiments, for each thermal radiation region in the thermal radiation region set, edge pixel points may be screened from a heat source region and a radiation range region included in the thermal radiation region, and a radiation length set corresponding to the thermal radiation region is determined according to the screened edge pixel points.
The edge pixel points may be pixel points on the edge in the heat source region or the radiation range region.
As an example, this step may include the steps of:
the method comprises the steps of firstly, determining edge pixel points screened from a heat source area included in the heat radiation area as heat source edge pixel points, and obtaining a heat source edge pixel point set corresponding to the heat radiation area.
And secondly, determining edge pixel points screened out from a radiation range area included by the heat radiation area as radiation edge pixel points to obtain a radiation edge pixel point set corresponding to the heat radiation area.
And thirdly, determining the mass center of the heat source area included in the heat radiation area as the mass center corresponding to the heat radiation area.
And fourthly, connecting each heat source edge pixel point in the heat source edge pixel point set corresponding to the heat radiation area with the mass center corresponding to the heat radiation area to obtain a heat source line segment set corresponding to the heat radiation area.
And fifthly, for each heat source line segment in the heat source line segment set corresponding to the heat radiation area, extending one end of the heat source line segment where the heat source edge pixel point is located until the heat source edge pixel point in the heat radiation edge pixel point set corresponding to the heat radiation area is intersected to obtain an intersection point, and taking a line segment between a centroid in the heat source line segment and the intersection point as the heat radiation line segment corresponding to the heat source line segment.
And sixthly, determining the difference value between the length of the heat radiation line segment corresponding to the heat source line segment and the length of the heat source line segment as the radiation length for each heat source line segment in the heat source line segment set corresponding to the heat radiation area.
Wherein the radiation length may be the length of a radiation line segment. The radiation line segment may be a line segment other than the heat source line segment in the heat radiation line segment. As shown in fig. 3, the smaller of the two concentric circles may represent a heat source area, and the area between the two concentric circles may represent a radiation range area. The solid points may represent the centroid of the heat source region. The dashed line segments may represent heat source line segments. The solid line segments may characterize the radiating line segments. The line segment connecting the imaginary line segment and the real line segment may be a heat radiation line segment.
Optionally, a center of mass point of the heat source area may be marked, a connection direction from the center of mass point to each edge pixel point of the heat source area is used as an outward radiation direction of the edge pixel point, each edge pixel point is searched outward according to the radiation direction until 0 pixel point is searched, and a search distance of each edge pixel point is recorded as a radiation length.
And S6, screening a heat radiation region set to be cleaned from the heat radiation region set according to the heat source region included in each heat radiation region in the heat radiation region set and the radiation length set corresponding to the heat radiation region.
In some embodiments, a set of heat radiation regions to be cleaned may be screened from the set of heat radiation regions according to a set of radiation lengths corresponding to the heat source region and the heat radiation region included in each heat radiation region in the set of heat radiation regions.
Wherein, the heat radiation area to be cleaned in the heat radiation area set to be cleaned can be the area to be cleaned.
As an example, this step may include the steps of:
firstly, determining an identification index to be cleaned corresponding to each heat radiation area according to the heat source area included in each heat radiation area in the heat radiation area set and the radiation length set corresponding to the heat radiation area.
For example, the formula for determining the identification index to be cleaned corresponding to the heat radiation area may be:
and F is the identification index to be cleaned corresponding to the heat radiation area.th() Is a hyperbolic tangent function.NIs the number of gradation values in the heat source region included in the above-described heat radiation region. The number of gray values in the heat source region may be different gray levels in the heat source regionThe number of values. For example, the different gray scale values in the heat source regions may be 180, 200, 210, and 240. At this time, the number of gray values in the heat source region may be 4.vThe gradation values are assigned to the heat source regions included in the heat radiation region.
The corresponding gray value in the heat source region included in the heat radiation region is equal to the second gray valuevThe number of pixels of each gray value.HThe number of the pixel points in the heat source region included in the heat radiation region is set.ln() Is a logarithmic function based on natural constants.
Is the standard deviation of the radiation lengths in the radiation length set corresponding to the above-mentioned heat radiation region.
Is to take the euclidean norm function.
Is a function of the absolute value.AAndBis a preset numerical value. For example,
。
。
is an average value of gradation values corresponding to pixel points in the heat radiation region included in the above-mentioned heat radiation region.
Is the maximum value among the gradation values corresponding to the pixel points in the heat radiation region included in the above-described heat radiation region.
In actual conditions, when components in the equipment room normally operate, corresponding thermal infrared images are often bright, and the situation may be confused with overheating caused by dust accumulation. If the component normally runs, the heat source area of the thermal infrared imageThe gray value of the domain is often more uniform, and the heat radiation range from the edge of the heat source region to the periphery is often more uniform, but when dust is randomly accumulated on the components, the interference degree of the dust on the internal circuits of the components is often different due to different accumulation densities, so that the components are overheated due to dust accumulation, the inside of the heat source region is often not uniform, and the heat radiation range from the edge of the heat source region to the periphery is often more different. The smaller the identification index F to be cleaned corresponding to the heat radiation area is, the more likely the heat source area included in the heat radiation area is to be a dust accumulation area.
The entropy value can be squared and can represent the expansion entropy of the gray level in the heat source region, the gray value corresponding to the pixel point of which the gray value is smaller than the self-adaptive cutting threshold value in the target thermal infrared image is set to be 0, in order to highlight the uniformity degree of the gray level in the heat source region, the entropy value can be squared, when the interior of the heat source region is almost completely uniform and the entropy value is smaller than 1, the expansion entropy after being squared is smaller, but when the heat source region has relatively large non-uniformity, the expansion entropy after being squared is larger when the entropy value is larger. The larger the expansion entropy, the more it tends to overheat the components due to dust accumulation.
For normalization with a hyperbolic tangent function. Standard deviation of radiation lengths in a set of radiation lengths corresponding to a heat radiation region
The larger the difference, the larger the difference of the heat radiation range from the edge of the heat source area to the periphery, and the overheating of components caused by dust accumulation tends to be more prone.
For normalization with a hyperbolic tangent function.
Can represent the Euclidean norm calculated by the expansion entropy and the standard deviation of the radiation length in the set of radiation lengthsMaximum value of
。
The larger the gradation value, the more the gradation value in the heat source region tends to become larger, and the higher the gradation value in the heat source region tends to be, the more likely the abnormal heat dissipation due to the accumulation of dust tends to be.
The more toward 1, the more likely the heat source area is to be a component area where dust is deposited. Therefore, the first and second electrodes are formed on the substrate,
the smaller the heat source area tends to be the more likely it is to be a dust accumulation area, i.e., the more likely it is that the heat source area is to be a heat radiation area to be cleaned.
And secondly, screening a heat radiation area set to be cleaned from the heat radiation area set according to a preset threshold value to be cleaned and identification indexes to be cleaned corresponding to each heat radiation area in the heat radiation area set.
Wherein, the threshold to be cleaned may be a preset threshold. For example, the threshold to be cleaned may be 0.2.
For example, when the identification index to be cleaned corresponding to the heat radiation region in the heat radiation region set is less than or equal to the threshold to be cleaned, the heat source region included in the heat radiation region is determined as the heat radiation region to be cleaned.
And S7, determining target cleaning position information corresponding to equipment in the machine room to be cleaned according to the set of the heat radiation areas to be cleaned, and cleaning the position corresponding to the target cleaning position information.
In some embodiments, target cleaning position information corresponding to the equipment room to be cleaned may be determined according to the set of heat radiation areas to be cleaned, and a position corresponding to the target cleaning position information may be cleaned.
As an example, the positions of the heat radiation areas to be cleaned in the heat radiation area set to be cleaned are combined into target cleaning position information corresponding to the equipment room to be cleaned, and the positions corresponding to the target cleaning position information are cleaned. For example, the heat radiation region to be cleaned may be cleaned directly.
In summary, the invention proposes that because a radiation range exists on a heat source on a target thermal infrared image of equipment in a machine room to be cleaned, the boundary of the heat source is fuzzy, the position of the heat source cannot be accurately positioned, and whether accumulated heat of the heat source is caused by dust accumulation or other reasons is difficult to judge. According to the invention, through cutting the gray level of the image, redundant calculation can be reduced, seed pixel points are set for the cut image by utilizing median filtering, the segmentation of a fuzzy region is realized by utilizing a growth rule, a heat source region is obtained, a formula for determining an identification index to be cleaned is constructed, the reason for forming the heat source can be distinguished, a dust accumulation region can be accurately positioned, the electrified cleaning of machine room equipment is more efficient, and clean resources are saved.
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; the modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present application, and are included in the protection scope of the present application.
Claims (10)
1. An auxiliary positioning method for electrified cleaning of equipment in a machine room is characterized by comprising the following steps:
acquiring a target thermal infrared image of equipment in a machine room to be cleaned, and determining a gray level histogram of the target thermal infrared image;
processing image data of the gray level histogram, and determining a self-adaptive cutting threshold value;
screening out a highlight pixel point set from the target thermal infrared image according to a self-adaptive cutting threshold value;
screening and growing the highlight pixel points in the highlight pixel point set to obtain a heat radiation area set, wherein the heat radiation area in the heat radiation area set comprises: a heat source region and a radiation range region;
for each heat radiation area in the heat radiation area set, screening edge pixel points from a heat source area and a radiation range area which are included in the heat radiation area, and determining a radiation length set corresponding to the heat radiation area according to the screened edge pixel points;
screening a heat radiation region set to be cleaned from the heat radiation region set according to a heat source region included in each heat radiation region in the heat radiation region set and a radiation length set corresponding to the heat radiation region;
and determining target cleaning position information corresponding to the equipment of the machine room to be cleaned according to the set of the heat radiation areas to be cleaned, and cleaning the position corresponding to the target cleaning position information.
2. The auxiliary positioning method for machine room equipment live cleaning according to claim 1, wherein the performing image data processing on the gray histogram and determining an adaptive cutting threshold comprises:
determining an average brightness index and a deviation brightness index according to the gray level histogram;
determining the ratio of the average brightness index to the biased brightness index as an integral biased brightness index;
when the integral deviation brightness index is larger than or equal to a preset brightness uniformity value, determining the deviation brightness index as a self-adaptive cutting threshold value;
and when the overall deviation brightness index is smaller than the brightness uniformity value, determining the average brightness index as a self-adaptive cutting threshold value.
3. The auxiliary positioning method for electrified cleaning of equipment in a machine room according to claim 2, wherein the determining of the average brightness index and the biased brightness index according to the gray histogram comprises:
determining the gray value at the target position in the gray histogram as an average brightness index, wherein the absolute value of the difference between the number of pixels before the target position and the number of pixels after the target position is less than a preset number threshold;
and determining half of the maximum gray value in the gray histogram as a deviation brightness index.
4. The auxiliary positioning method for machine room equipment live cleaning according to claim 1, wherein the screening out a set of highlight pixel points from the target thermal infrared image according to an adaptive cutting threshold comprises:
and determining pixel points with the gray values larger than or equal to the self-adaptive cutting threshold value in the target thermal infrared image as highlight pixel points.
5. The auxiliary positioning method for machine room equipment live cleaning according to claim 1, wherein the step of performing screening growth processing on the highlight pixel points in the highlight pixel point set to obtain a heat radiation area set comprises:
performing median filtering on the highlight pixel points in the highlight pixel point set to obtain filtering values corresponding to the highlight pixel points;
when the filtering value corresponding to the highlight pixel point is equal to the gray value corresponding to the highlight pixel point, determining the highlight pixel point as a seed pixel point;
determining a range value corresponding to the seed pixel point according to a preset target window corresponding to the seed pixel point;
performing region growth according to the corresponding range values of the seed pixel points to obtain a target region set;
determining the mean value of the gray values corresponding to the pixel points in each target region in the target region set as the gray mean value corresponding to the target region;
screening a target area group set of a preset target arrangement mode from the target area set, wherein each target area group in the target area group set comprises two target areas;
for each target area group in the target area group set, determining a target area with a larger gray mean value in the target area group as a heat source area, determining a target area with a smaller gray mean value in the target area group as a radiation range area, and determining an area where two target areas in the target area group are located as a heat radiation area.
6. The auxiliary positioning method for machine room equipment live cleaning according to claim 1, wherein the step of screening edge pixel points from a heat source area and a radiation range area included in the heat radiation area, and determining a radiation length set corresponding to the heat radiation area according to the screened edge pixel points comprises:
determining edge pixel points screened from a heat source area included in the heat radiation area as heat source edge pixel points to obtain a heat source edge pixel point set corresponding to the heat radiation area;
determining edge pixel points screened from a radiation range area included in the heat radiation area as radiation edge pixel points to obtain a radiation edge pixel point set corresponding to the heat radiation area;
determining a mass center of a heat source area included in the heat radiation area as a mass center corresponding to the heat radiation area;
connecting each heat source edge pixel point in the heat source edge pixel point set corresponding to the heat radiation area with the mass center corresponding to the heat radiation area to obtain a heat source line segment set corresponding to the heat radiation area;
for each heat source line segment in the heat source line segment set corresponding to the heat radiation area, extending one end of the heat source line segment where a heat source edge pixel point is located until the heat source line segment intersects with a radiation edge pixel point in the radiation edge pixel point set corresponding to the heat radiation area to obtain an intersection point, and taking a line segment between a centroid in the heat source line segment and the intersection point as a heat radiation line segment corresponding to the heat source line segment;
and determining the difference value between the length of the heat radiation line segment corresponding to the heat source line segment and the length of the heat source line segment as the radiation length for each heat source line segment in the heat source line segment set corresponding to the heat radiation area.
7. The auxiliary positioning method for machine room equipment live cleaning according to claim 1, wherein the screening out a set of thermal radiation areas to be cleaned from the set of thermal radiation areas according to a set of radiation lengths corresponding to a heat source area and a thermal radiation area included in each thermal radiation area in the set of thermal radiation areas comprises:
determining an identification index to be cleaned corresponding to each heat radiation region according to the heat source region included in each heat radiation region in the heat radiation region set and the radiation length set corresponding to the heat radiation region;
and screening a heat radiation area set to be cleaned from the heat radiation area set according to a preset threshold value to be cleaned and identification indexes to be cleaned corresponding to each heat radiation area in the heat radiation area set.
8. The auxiliary positioning method for electrified cleaning of equipment room according to claim 7, wherein the formula for determining the identification index to be cleaned corresponding to the heat radiation area is as follows:
wherein F is the identification index to be cleaned corresponding to the heat radiation area,th() Is a function of the hyperbolic tangent,Nis the number of gradation values in the heat source region included in the heat radiation region,vis a number of gradation values in a heat source region included in the heat radiation region,
is that the corresponding gray value in the heat source region included in the heat radiation region is equal to the second gray valuevThe number of pixels of each gray value,His the number of pixel points in the heat source region included in the heat radiation region,ln() Is a logarithmic function with a natural constant as the base number,
is the standard deviation of the radiation lengths in the set of radiation lengths corresponding to the heat radiation area,
in order to take the euclidean norm function,
in order to take the function of the absolute value,AandBis a numerical value that is set in advance,
is an average value of gray values corresponding to pixel points in a heat radiation region included in the heat radiation region,
is the maximum value among the gradation values corresponding to the pixel points in the heat radiation region included in the heat radiation region.
9. The auxiliary positioning method for machine room equipment live cleaning according to claim 7, wherein the screening out a set of thermal radiation areas to be cleaned from the set of thermal radiation areas according to a preset threshold to be cleaned and an identification index to be cleaned corresponding to each thermal radiation area in the set of thermal radiation areas comprises:
and when the identification index to be cleaned corresponding to the heat radiation area in the heat radiation area set is smaller than or equal to the threshold value to be cleaned, determining the heat source area included in the heat radiation area as the heat radiation area to be cleaned.
10. The auxiliary positioning method for electrified cleaning of machine room equipment according to claim 9, wherein the determining of the target cleaning position information corresponding to the machine room equipment to be cleaned according to the set of heat radiation areas to be cleaned comprises:
and combining the positions of all the heat radiation areas to be cleaned in the heat radiation area set to be cleaned into target cleaning position information corresponding to the equipment of the machine room to be cleaned.
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