CN112699583B - A data space block processing method for heat map technology - Google Patents

Abstract

The invention discloses a data space block processing method, device, electronic equipment and storage medium for heat map technology. The method distinguishes the heat map into effective data and background noise according to the identification model boundary, and forces the background noise to be Then, according to the factors affecting heat flow measurement and space isolation, the effective image is divided into several independent blocks, and after determining the key parameters of heat flow calculation of each block, heat flow data processing is carried out for each block; The local heat flow results are corrected by the boundary heat flow ratio, and combined to obtain the global heat flow distribution on the model surface. While shortening the post-processing time, the accuracy of the heat flow calculation is improved, and the efficiency and accuracy of the stitching process are improved.

Description

A data space block processing method for heat map technology

technical field

The present invention relates to the technical field of data processing, in particular to a data space block processing method, device, electronic equipment and storage medium for heat map technology.

Background technique

For the prediction of the thermal environment of hypersonic vehicles, traditional test and measurement methods use point or integral heat flow sensors, which can only obtain the distribution of heat flow at discrete points, and it is easy to damage the surface structure of the model and cause interference to the flow field; The graph technology adopts non-contact measurement method, which can obtain large-area heat flow data without disturbing the flow field, and has become an important direction for the development of heat flow measurement technology.

At present, the processing of heat map data generally processes the image as a whole, which will certainly simplify the process of data processing algorithms, but it brings the following problems:

(1) Invalid pixel information in the background also participates in the data processing flow, which brings a lot of redundant calculations and greatly increases the data processing time;

(2) When the light source causes the initial light intensity to be uneven, a large error will be generated when the temperature is calculated from the light intensity;

(3) When the thermophysical parameters of the model surface are not exactly the same, they must be calculated in multiple times and combined manually, which reduces the efficiency and accuracy of the combination process.

Contents of the invention

The purpose of the present invention is to provide a data space block processing method for heat map technology, which can improve the accuracy of heat flow calculation and algorithm adaptability while shortening the post-processing time.

In the first aspect, an embodiment of the present invention provides a data space block processing method for heat map technology, and the block processing method includes the following steps:

Perform boundary recognition on the image, and divide the image into valid areas and background noise areas according to the identified boundaries;

Force the pixels in the background noise area to be empty;

Divide the image in the effective area into multiple independent blocks according to the factors affecting the heat flow measurement and the spatial isolation;

Determine the key parameters of each block in the calculation of heat flow;

Calculate the local heat flow distribution of each block according to the key parameters of heat flow calculation corresponding to each block;

According to the local heat flow calculation results of each block, the coincident boundaries of each block are compared, corrected and merged to obtain the global heat flow distribution results on the model surface.

Optionally, performing boundary recognition on the image includes:

According to the known model boundary curve and the light intensity distribution in the heat map, a set of pixel points mapped by the model boundary curve in the image is obtained.

Optionally, in the boundary heat flow ratio correction method, the heat flow of points in the neighborhood S2 of any point (X0, Y0) in the pixel point set S1 mapped on the same finite model boundary L1 satisfies the following conditions:

For the set of all pixels satisfying |X－X0|<Δ, |Y－Y0|<Δ,

Max(q(X, Y)|(X, Y)∈S1)－Min(q(X, Y)|(X, Y)∈S1)<ε, where ε is the set boundary heat flow tolerance;

Among them, X±Δ, Y±Δ, Δ are boundary blur coefficients.

Optionally, factors affecting heat flow measurement include base material and initial light intensity.

Optionally, the key parameters when calculating the heat flow include the thermophysical parameter ρ _ck and the initial light intensity I ₀ of the calibration curve adopted.

In the second aspect, an embodiment of the present invention provides a data space block processing device for heat map technology, and the block processing device includes:

The processing module is used to identify and identify the boundary of the image, and divide the image into an effective area and a background noise area according to the identified boundary, and force the pixels in the background noise area to be empty;

A division module, which is used to divide the image in the effective area into multiple independent blocks according to factors affecting heat flow measurement and spatial isolation;

Calculation module, used to calculate the local heat flow distribution of each block according to the key parameters of heat flow calculation corresponding to each block;

The correction module is used to compare, correct and combine the coincident boundaries of each block according to the local heat flow calculation results of each block, and obtain the global heat flow distribution result on the model surface.

Optionally, the processing module includes:

The identification unit is configured to obtain a set of pixel points mapped by the model boundary curve in the image according to the known model boundary curve and the light intensity distribution in the heat map.

Optionally, the correction method of the correction module satisfies the following conditions for the heat flow of points in the neighborhood S2 of any point (X0, Y0) in the pixel point set S1 mapped on the same finite model boundary L1:

For the set of all pixels satisfying |X－X0|<Δ, |Y－Y0|<Δ,

Max(q(X, Y)|(X, Y)∈S1)－Min(q(X, Y)|(X, Y)∈S1)<ε, where ε is the set boundary heat flow tolerance;

Among them, X±Δ, Y±Δ, Δ are boundary blur coefficients.

In a third aspect, an embodiment of the present invention provides an electronic device, including:

processor;

memory for storing processor-executable instructions;

Wherein, the processor implements the data space block processing method for heat map technology described in any one of the above methods by running the executable instructions.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and the computer program is used for: executing the above-mentioned data space block processing method for heat map technology.

Beneficial effect

The present invention proposes a data space block processing method for heat map technology. First, the heat map is divided into effective data and background noise according to the identification model boundary, and the background noise is forced to be empty; then, according to the factors affecting the heat flow measurement (such as substrate material, initial light intensity, etc.) and space isolation divide the effective image into several independent blocks, and determine the key parameters of heat flow calculation of each block (such as thermal physical parameters ρck, initial light intensity I ₀ , etc.) Perform heat flow data processing for each block; finally, perform boundary heat flow comparison correction on the local heat flow results of each block, and combine to obtain the global heat flow distribution on the model surface, shorten post-processing time and improve the accuracy of heat flow calculation , improving the efficiency and accuracy of the flattening process.

Description of drawings

Fig. 1 is a flowchart of an embodiment of a data space block processing method for heat map technology in the present invention;

Fig. 2 is a schematic flow chart of heat map processing by a data space block processing method for heat map technology according to the present invention;

3 is a structural block diagram of an embodiment of a data space block processing device for heat map technology in the present invention;

Fig. 4 is the structural block diagram of processing module in Fig. 3;

Fig. 5 is a structural block diagram of an electronic device according to an embodiment of the present invention.

Detailed ways

The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

In describing the present invention, it is to be understood that the terms "thickness", "upper", "lower", "front", "rear", "left", "right", "inner", "outer", etc. The indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or system referred to must have a specific orientation, and must have a specific orientation. construction and operation, therefore, should not be construed as limiting the invention.

In addition, the terms "first" and "second" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of said features. Those of ordinary skill in the art can understand the specific meanings of the above terms in the present invention in specific situations.

In order to solve the problem that the post-processing of the heat map technology takes too long and the light intensity of the model surface is uneven caused by the light source, the present invention provides a spatial block processing method for the heat map technology, which shortens the post-processing time and at the same time, Improve the accuracy and algorithm adaptability of heat flow calculation.

The present invention will be further described below in conjunction with accompanying drawing description and specific embodiment:

Fig. 1 shows a schematic flowchart of a data space block processing method for heat map technology according to an embodiment of the present invention, and Fig. 2 shows a data space block processing method for heat map technology according to the present invention for thermal Schematic flow chart of image processing; as shown in Figure 1-2, the block processing method includes the following steps:

S20. Perform boundary recognition on the image, and divide the image into valid regions and background noise regions according to the recognized boundaries;

S40, forcing the pixels in the background noise area to be empty;

The pixels in the background noise area will no longer participate in the subsequent calculations, and directly avoid the pixel data at the background noise from participating in the calculation, which can directly improve the speed of later heat map calculations and reduce the occupation of hardware (such as memory).

S60. Divide the image in the effective area into a plurality of independent blocks according to factors affecting heat flow measurement and spatial isolation;

In some embodiments, according to the initial light intensity (factors that affect the measurement of heat flow), the temperature is inversely calculated by using calibration curves with different initial light intensities, which reduces the calculation error caused by uneven light intensity irradiation and improves the heat flow. The accuracy of the calculation can handle the data environment caused by the light source; in addition, the calculated boundary comparison can not only verify the correctness of the calculation of each block, but also significantly improve the efficiency and accuracy of image stitching.

In some embodiments, by dividing the heat flow into blocks according to the thermal physical parameters of the material and using different thermal physical parameters to calculate the heat flow, the heat flow of surfaces with different thermal physical properties can be calculated at the same time, which improves the accuracy of the heat flow calculation, and can handle more problems caused by different model materials. For the complex data environment; in addition, through the boundary comparison and flattening algorithm, compared with manual flattening, it not only improves the efficiency, but also has higher spatial flattening accuracy.

S80. Determine the key parameters of each block when calculating the heat flow;

S100. Calculate the local heat flow distribution of each block according to the key parameters of heat flow calculation corresponding to each block;

S120. Comparing, correcting and merging overlapping boundaries of each block according to the local heat flow calculation results of each block to obtain a global heat flow distribution result on the model surface.

Specifically, performing boundary recognition on an image includes:

According to the known model boundary curve and the light intensity distribution in the heat map, a set of pixel points mapped by the model boundary curve in the image is obtained.

Specifically in step S120, in the boundary heat flow ratio correction method, the heat flow of points in the neighborhood S2 of any point (X0, Y0) in the pixel point set S1 mapped on the same finite model boundary L1 satisfies the following conditions:

For the set of all pixels satisfying |X－X0|<Δ, |Y－Y0|<Δ,

Max(q(X, Y)|(X, Y)∈S1)－Min(q(X, Y)|(X, Y)∈S1)<ε, where ε is the set boundary heat flow tolerance;

Among them, X±Δ, Y±Δ, Δ are boundary blur coefficients. The maximum and minimum values of heat flow in the neighborhood are used, and the comparison efficiency is high.

The present invention has the advantage over prior art that:

(1) The present invention directly prevents the pixel data at the background noise from participating in the calculation by forcing the pixels at the background noise to be empty, which can directly improve the speed of later heat map calculation and reduce the occupation of hardware (such as memory).

(2) The present invention reduces the calculation error caused by uneven light intensity irradiation in principle and improves the accuracy of heat flow calculation by dividing the initial light intensity into blocks and adopting calibration curves with different initial light intensities to calculate the temperature inversely; The data environment caused by the light source; in addition, the calculated boundary comparison can not only verify the correctness of the calculation of each block, but also significantly improve the efficiency and accuracy of image stitching.

(3) The present invention calculates the heat flow by dividing into blocks according to the thermal physical parameters of the material and adopting different thermal physical parameters, so that the heat flow of surfaces with different thermal physical properties can be calculated at the same time, the accuracy of the heat flow calculation is improved, and it is possible to deal with the problems caused by different model materials. Complex data environment; in addition, through the boundary comparison and flattening algorithm, compared with manual flattening, not only the efficiency is improved, but also the spatial flattening accuracy is higher.

As shown in FIG. 3, an embodiment of the present invention provides a data space block processing device for heat map technology, and the block processing device includes:

The processing module 20 is used to identify and identify the boundary of the image, and divide the image into an effective area and a background noise area according to the identified boundary, and force the pixels in the background noise area to be empty;

A division module 40, configured to divide the image in the effective area into a plurality of independent blocks according to factors affecting heat flow measurement and spatial isolation;

Calculation module 60, for calculating the local heat flow distribution of each block respectively according to the key parameters of heat flow calculation corresponding to each block;

The correction module 80 is used for comparing, correcting and combining the overlapped boundaries of each block according to the local heat flow calculation results of each block, and obtaining the global heat flow distribution result of the model surface.

Preferably, as shown in Figure 4, the processing module 20 includes:

The recognition unit 201 is configured to obtain a set of pixel points mapped by the model boundary curve in the image according to the known model boundary curve and the light intensity distribution in the heat map.

In some embodiments, according to the initial light intensity (factors that affect the measurement of heat flow), the temperature is inversely calculated by using calibration curves with different initial light intensities, which reduces the calculation error caused by uneven light intensity irradiation and improves the heat flow. The accuracy of the calculation can handle the data environment caused by the light source; in addition, the calculated boundary comparison can not only verify the correctness of the calculation of each block, but also significantly improve the efficiency and accuracy of image stitching.

In some embodiments, by dividing the heat flow into blocks according to the thermal physical parameters of the material and using different thermal physical parameters to calculate the heat flow, the heat flow of surfaces with different thermal physical properties can be calculated at the same time, which improves the accuracy of the heat flow calculation, and can handle more problems caused by different model materials. For the complex data environment; in addition, through the boundary comparison and flattening algorithm, compared with manual flattening, it not only improves the efficiency, but also has higher spatial flattening accuracy.

Preferably, the correction method of the correction module satisfies the following conditions for the heat flow of points in the neighborhood S2 of any point (X0, Y0) in the pixel point set S1 mapped on the same finite model boundary L1:

For the set of all pixels satisfying |X－X0|<Δ, |Y－Y0|<Δ,

Max(q(X, Y)|(X, Y)∈S1)－Min(q(X, Y)|(X, Y)∈S1)<ε, where ε is the set boundary heat flow tolerance;

Among them, X±Δ, Y±Δ, Δ are boundary blur coefficients.

The present invention proposes a data space block processing device for heat map technology. First, the processing module 20 recognizes the boundary of the image, and divides the image into an effective area and a background noise area according to the identified boundary, and divides the background noise The pixels in the area are forced to be empty; the division module 40 divides the image in the effective area into multiple independent blocks according to the factors affecting the heat flow measurement and the spatial isolation; the calculation module 60 calculates the key parameters of the heat flow calculation corresponding to each block. The local heat flow distribution of the block; the correction module 80 compares, corrects and merges the overlapped boundaries of each block according to the local heat flow calculation results of each block, and obtains the global heat flow distribution result of the model surface, and improves the heat flow while shortening the post-processing time. The calculation accuracy improves the efficiency and accuracy of the stitching process.

The embodiment of the present application also provides a computer electronic device. FIG. 5 shows a schematic structural diagram of the electronic device to which the embodiment of the present application can be applied. As shown in FIG. 5 , the computer electronic device includes a central processing unit (CPU) 301 , which can execute various appropriate actions and processes according to a program stored in a read only memory (ROM) 302 or a program loaded from a storage section 308 into a random access memory (RAM) 303 . In the RAM 303, various programs and data necessary for the operation of the system 300 are also stored. The CPU 301 , ROM 302 , and RAM 303 are connected to each other via a bus 304 . An input/output (I/O) interface 305 is also connected to the bus 304 .

The following components are connected to the I/O interface 305: an input section 1006 including a keyboard, a mouse, etc.; an output section 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 308 including a hard disk, etc. and a communication section 309 including a network interface card such as a LAN card, a modem, or the like. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I/O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 310 as necessary so that a computer program read therefrom is installed into the storage section 308 as necessary.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or portion of code that contains one or more logic devices for implementing the specified Executable instructions for a function. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified functions or operations , or may be implemented by a combination of dedicated hardware and computer instructions.

As another aspect, the present application also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the software installation device in the above-mentioned embodiments; it may also be a separate , a computer-readable storage medium not incorporated into an electronic device. The computer-readable storage medium stores one or more programs, and the programs are used by one or more processors to execute the data space block processing method for heat map technology described in this application.

The above description is only a preferred embodiment of the present application and an illustration of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solution formed by the specific combination of the above-mentioned technical features, but should also cover the technical solution formed by the above-mentioned technical features without departing from the inventive concept. Other technical solutions formed by any combination of or equivalent features thereof. For example, a technical solution formed by replacing the above-mentioned features with technical features with similar functions disclosed in (but not limited to) this application.

Claims (10)

1. A data space block processing method for thermal map technology, characterized in that, the block processing method comprises the following steps: Perform boundary recognition on the image, and divide the image into valid areas and background noise areas according to the identified boundaries; Force the pixels in the background noise area to be empty; Divide the image in the effective area into multiple independent blocks according to the factors affecting the heat flow measurement and the spatial isolation; Determine the key parameters of each block in the calculation of heat flow; Calculate the local heat flow distribution of each block according to the key parameters of heat flow calculation corresponding to each block; According to the local heat flow calculation results of each block, the coincident boundaries of each block are compared, corrected and merged to obtain the global heat flow distribution results on the model surface. 2. the data space block processing method according to claim 1, is characterized in that, carrying out boundary recognition to image comprises: According to the known model boundary curve and the light intensity distribution in the heat map, a set of pixel points mapped by the model boundary curve in the image is obtained. 3. The data space block processing method according to claim 1, characterized in that, in the described boundary heat flow comparison correction method, for any point (X0, Y0 ) The heat flow of points in the neighborhood S2 of ) satisfies the following conditions: For the set of all pixels satisfying |X－X0|<Δ, |Y－Y0|<Δ, Max(q(X, Y)|(X, Y)∈S1)－Min(q(X, Y)|(X, Y)∈S1)<ε, where ε is the set boundary heat flow tolerance; Among them, X±Δ, Y±Δ, Δ are boundary blur coefficients. 4 . The data space block processing method according to claim 1 , wherein the factors affecting heat flow measurement include substrate material and initial light intensity. 5 . The data space block processing method according to claim 1 , wherein the key parameters when calculating the heat flow include the thermal physical property parameter ρck and the initial light intensity I0 of the calibration curve adopted. 6 . 6. A data space block processing device for heat map technology, characterized in that, the block processing device includes: The processing module is used to identify and identify the boundary of the image, and divide the image into an effective area and a background noise area according to the identified boundary, and force the pixels in the background noise area to be empty; A division module, which is used to divide the image in the effective area into multiple independent blocks according to factors affecting heat flow measurement and spatial isolation; Calculation module, used to calculate the local heat flow distribution of each block according to the key parameters of heat flow calculation corresponding to each block; The correction module is used to compare, correct and combine the coincident boundaries of each block according to the local heat flow calculation results of each block, and obtain the global heat flow distribution result on the model surface. 7. The data space block processing device according to claim 6, wherein the processing module comprises: The identification unit is configured to obtain a set of pixel points mapped by the model boundary curve in the image according to the known model boundary curve and the light intensity distribution in the heat map. 8. The data space block processing device according to claim 6, characterized in that, the correction method of the correction module is for the neighbors of any point (X0, Y0) in the pixel point set S1 mapped to the same finite model boundary L1 The heat flow of points in domain S2 satisfies the following conditions: For the set of all pixels satisfying |X－X0|<Δ, |Y－Y0|<Δ, Max(q(X, Y)|(X, Y)∈S1)－Min(q(X, Y)|(X, Y)∈S1)<ε, where ε is the set boundary heat flow tolerance; Among them, X±Δ, Y±Δ, Δ are boundary blur coefficients. 9. An electronic device comprising: processor; memory for storing processor-executable instructions; Wherein, the processor implements the data space block processing method for heat map technology according to any one of claims 1-5 by running the executable instructions. 10. A computer-readable storage medium, on which a computer program is stored, and the computer program is used for: executing the data space block processing method for heat map technology according to any one of claims 1-5.

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