A method for monitoring processing temperature of PE insulation pipe

Abstract

The present invention discloses a method for monitoring the processing temperature of a PE insulation pipe, which belongs to the technical field of temperature monitoring and comprises the following steps: S1, using an infrared thermal imager to obtain a temperature distribution diagram of the surface of the PE insulation pipe at each moment during the processing; S2, selecting a predetermined distribution diagram from the temperature distribution diagrams at all moments, and determining the distribution thermal image value of the predetermined distribution diagram; S3, determining whether the surface of the PE insulation pipe is abnormal during the processing according to the distribution thermal image value of the predetermined distribution diagram. The present invention ensures the comprehensiveness and accuracy of the temperature data monitoring of the PE insulation pipe, realizes the precise temperature control of the entire production process of the PE insulation pipe, and reduces the influence of abnormal temperature on product quality.

Description

Technical Field

[0001] The invention belongs to the technical field of temperature monitoring, and in particular relates to a method for monitoring the processing temperature of a PE thermal insulation pipe. Background Art

[0002] PE insulated pipes are widely used in municipal heating, cooling, industrial pipelines and commercial buildings due to their excellent thermal insulation performance and corrosion resistance. In the production and processing of PE insulated pipes, temperature control is one of the key factors to ensure the quality of the insulated pipes. Traditional temperature monitoring methods often have problems such as limited monitoring points and poor real-time data, which makes it difficult to meet the high-precision and high-efficiency production requirements of PE insulated pipes. Therefore, it is particularly important to develop an efficient and accurate PE insulated pipe processing temperature monitoring method. Summary of the invention

[0003] In order to solve the above problems, the present invention proposes a PE insulation pipe processing temperature monitoring method.

[0004] The technical solution of the present invention is: a method for monitoring the processing temperature of a PE thermal insulation pipe comprises the following steps:

[0005] S1. Use an infrared thermal imager to obtain the temperature distribution diagram of the surface of the PE insulation pipe at each moment during the processing;

[0006] S2, selecting a predetermined distribution map from the temperature distribution maps at all times, and determining the distribution thermal image value of the predetermined distribution map;

[0007] S3. Determine whether there is any abnormality on the surface of the PE insulation pipe during the processing according to the distribution thermal image value of the predetermined distribution diagram.

[0008] Use temperature monitoring equipment such as infrared thermal imagers to scan the surface of PE insulation pipes in real time and directly generate a temperature distribution map, which is a chart that displays temperature data in the form of an image. The temperature distribution map is usually displayed in the form of a color image, and different colors represent different temperature ranges. For example, red may represent a high temperature area and blue represents a low temperature area. If there is local overheating or overcooling, these areas will be displayed in the image with obvious color differences; if the surface color is uniform, without obvious color mutations or patches, it indicates that the processing flow of the insulation pipe is normal and the temperature distribution is uniform.

[0009] Furthermore, S2 includes the following sub-steps:

[0010] S21, calculating the degree of change corresponding to the temperature distribution graph at each moment, and taking the temperature distribution graph with the minimum degree of change as the predetermined distribution graph;

[0011] S22, performing grayscale processing on the predetermined distribution map to obtain a predetermined distribution grayscale map, and generating a thermal image relationship equation for the predetermined distribution grayscale map;

[0012] S23. Determine the distributed thermal image value of the predetermined distribution diagram according to the value corresponding to the thermal image relationship.

[0013] The beneficial effect of the above further scheme is: in the present invention, the pixel value changes of adjacent pixel points in the temperature distribution map at each moment are calculated, and the pixel value distribution of the temperature distribution map with the minimum change is relatively uniform, indicating that its temperature distribution is relatively uniform, and it can be used as the most standard temperature distribution map among many moments to extract the distributed thermal image value, which is convenient for comparison with the temperature distribution map at other moments in S3. In the process of determining the distributed thermal image value, the predetermined distribution map is first grayed, and the relationship between the specific temperature value and the image gray value is determined. After the thermal image relationship is determined for the predetermined distribution map, the distributed thermal image value of the predetermined distribution map is determined according to the thermal image relationship. The distributed thermal image value includes the influence of temperature, and is not just a simple pixel value, and can be used to analyze the temperature distribution map at other moments.

[0014] Furthermore, in S21, the calculation formula of the change degree E of the temperature distribution diagram is: ; Where M represents the number of pixels in the temperature distribution map, d m Represents the pixel value of the mth pixel in the temperature distribution map, d m+1 represents the pixel value of the m+1th pixel in the temperature distribution map, and σ represents the standard deviation of the pixel values ​​of all pixels in the temperature distribution map.

[0015] Further, in S22, the thermal image relationship T of the predetermined distribution grayscale image is expressed as: ; Wherein, T1 represents the minimum temperature value obtained by the infrared thermal imager, T2 represents the maximum temperature value obtained by the infrared thermal imager, Y1 represents the minimum grayscale value of the predetermined distribution graph, Y2 represents the maximum grayscale value of the predetermined distribution graph, and Y ave Represents the mean grayscale value of all pixels in the predetermined distribution map.

[0016] When the infrared thermal imager obtains the temperature distribution diagram of the PE insulation pipe at each moment, it will determine the minimum temperature value and the maximum temperature value that have appeared on the surface of the PE insulation pipe at all moments, namely T1 and T2.

[0017] Further, S23 includes the following sub-steps:

[0018] S231, judging whether the value of the thermal image relationship formula belongs to the normal temperature range of the PE insulation pipe, if so, proceeding to S232, otherwise proceeding to S233;

[0019] S232, taking the ratio between the difference between the highest normal temperature and the lowest normal temperature of the PE insulation pipe and the value of the thermal image relationship as the influence weight, and proceeding to S234;

[0020] S233, taking the ratio between the highest normal temperature of the PE insulation pipe and the value of the thermal image relationship as the influence weight, and proceeding to S234;

[0021] S234. Determine the distribution thermal image value of the predetermined distribution map according to the influence weight.

[0022] Due to its own characteristics, PE insulated pipe has a specific normal temperature range. Between the minimum working temperature and the maximum working temperature, PE insulated pipe can work normally.

[0023] Further, in S234, the calculation formula of the distribution thermal image value y of the predetermined distribution diagram is: ; In the formula, R represents the influence weight, d ave Represents the mean pixel value of all pixels in the predetermined distribution map.

[0024] Furthermore, S3 includes the following sub-steps:

[0025] S31, calculating the difference between the temperature distribution map and the distribution thermal image value at other times;

[0026] S32. Calculate whether the sum of all differences is within the normal temperature range of the PE insulation pipe. If so, there is no abnormality on the surface of the PE insulation pipe during the processing; otherwise, there is an abnormality on the surface of the PE insulation pipe during the processing.

[0027] The beneficial effect of the above further solution is that in the present invention, according to the difference between the distributed thermal image values ​​at other times, it is determined whether the sum of all the differences does not belong to the normal temperature range, thereby determining whether there is a temperature anomaly.

[0028] Further, in S31, the difference Z between the temperature distribution map at the i-th moment and the distribution thermal image value is i The calculation formula is: ; In the formula, y represents the distribution thermal image value of the predetermined distribution map, N represents the number of pixels in the temperature distribution map at the i-th moment, e represents the index, d i_n Represents the pixel value of the nth pixel in the temperature distribution map at the i-th moment.

[0029] The beneficial effects of the present invention are as follows: the present invention obtains a predetermined distribution map by screening the temperature distribution map at all times, and determines the distributed thermal image value that can be used to participate in the analysis of the temperature distribution map at other times by using the thermal image relationship between the pixel points and the temperature values ​​of the predetermined distribution map; and determines the final monitoring result by using the difference between the distributed thermal image value and the temperature distribution map at other times; the present invention ensures the comprehensiveness and accuracy of the temperature data monitoring of the PE insulation pipe, realizes the precise temperature control of the whole production process of the PE insulation pipe, and reduces the influence of abnormal temperature on product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of the temperature monitoring method for PE insulation pipe processing;

[0031] Figure 2 Schematic diagram of a predetermined distribution grayscale image. DETAILED DESCRIPTION

[0032] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0033] like Figure 1 As shown, the present invention provides a method for monitoring the processing temperature of a PE thermal insulation pipe, comprising the following steps:

[0034] S1. Use an infrared thermal imager to obtain the temperature distribution diagram of the surface of the PE insulation pipe at each moment during the processing;

[0035] S2, selecting a predetermined distribution map from the temperature distribution maps at all times, and determining the distribution thermal image value of the predetermined distribution map;

[0036] S3. Determine whether there is any abnormality on the surface of the PE insulation pipe during the processing according to the distribution thermal image value of the predetermined distribution diagram.

[0037] Use temperature monitoring equipment such as infrared thermal imagers to scan the surface of PE insulation pipes in real time and directly generate a temperature distribution map, which is a chart that displays temperature data in the form of an image. The temperature distribution map is usually displayed in the form of a color image, and different colors represent different temperature ranges. For example, red may represent a high temperature area and blue represents a low temperature area. If there is local overheating or overcooling, these areas will be displayed in the image with obvious color differences; if the surface color is uniform, without obvious color mutations or patches, it indicates that the processing flow of the insulation pipe is normal and the temperature distribution is uniform.

[0038] In this embodiment of the present invention, S2 includes the following sub-steps:

[0039] S21, calculating the degree of change corresponding to the temperature distribution graph at each moment, and taking the temperature distribution graph with the minimum degree of change as the predetermined distribution graph;

[0040] S22, performing grayscale processing on the predetermined distribution map to obtain a predetermined distribution grayscale map, and generating a thermal image relationship equation for the predetermined distribution grayscale map;

[0041] S23. Determine the distributed thermal image value of the predetermined distribution diagram according to the value corresponding to the thermal image relationship.

[0042] In the present invention, the pixel value changes of adjacent pixel points in the temperature distribution map at each moment are calculated. The pixel value distribution of the temperature distribution map with the minimum change is relatively uniform, indicating that its temperature distribution is relatively uniform. It can be used as the most standard temperature distribution map among many moments to extract the distributed thermal image value, which is convenient for comparison with the temperature distribution map at other moments in S3. In the process of determining the distributed thermal image value, the predetermined distribution map is first grayed, the relationship between the specific temperature value and the image gray value is determined, and after the thermal image relationship is determined for the predetermined distribution map, the distributed thermal image value of the predetermined distribution map is determined according to the thermal image relationship. The distributed thermal image value includes the influence of temperature and is not just a simple pixel value. It can be used to analyze the temperature distribution map at other moments.

[0043] like Figure 2 As shown in the figure, grayscale processing is performed on the color temperature distribution map at a certain moment, and the following is obtained: Figure 2 The predetermined distribution grayscale diagram shown. In the original color temperature distribution diagram, the middle part is red, and the upper and lower parts are blue. After grayscale processing, the grayscale value of the middle part is darker, and the grayscale values ​​of the upper and lower parts are lighter.

[0044] In the embodiment of the present invention, in S21, the calculation formula of the change degree E of the temperature distribution diagram is: ; Where M represents the number of pixels in the temperature distribution map, d m Represents the pixel value of the mth pixel in the temperature distribution map, d m+1 represents the pixel value of the m+1th pixel in the temperature distribution map, and σ represents the standard deviation of the pixel values ​​of all pixels in the temperature distribution map.

[0045] In the embodiment of the present invention, in S22, the thermal image relationship T of the predetermined distribution grayscale image is expressed as: ; Wherein, T1 represents the minimum temperature value obtained by the infrared thermal imager, T2 represents the maximum temperature value obtained by the infrared thermal imager, Y1 represents the minimum grayscale value of the predetermined distribution graph, Y2 represents the maximum grayscale value of the predetermined distribution graph, and Y ave Represents the mean grayscale value of all pixels in the predetermined distribution map.

[0046] When the infrared thermal imager obtains the temperature distribution diagram of the PE insulation pipe at each moment, it will determine the minimum temperature value and the maximum temperature value that have appeared on the surface of the PE insulation pipe at all moments, namely T1 and T2.

[0047] In this embodiment of the present invention, S23 includes the following sub-steps:

[0048] S231, judging whether the value of the thermal image relationship formula belongs to the normal temperature range of the PE insulation pipe, if so, proceeding to S232, otherwise proceeding to S233;

[0049] S232, taking the ratio between the difference between the highest normal temperature and the lowest normal temperature of the PE insulation pipe and the value of the thermal image relationship as the influence weight, and proceeding to S234;

[0050] S233, taking the ratio between the highest normal temperature of the PE insulation pipe and the value of the thermal image relationship as the influence weight, and proceeding to S234;

[0051] S234. Determine the distribution thermal image value of the predetermined distribution map according to the influence weight.

[0052] Due to its own characteristics, PE insulated pipe has a specific normal temperature range. Between the minimum working temperature and the maximum working temperature, PE insulated pipe can work normally.

[0053] In the embodiment of the present invention, in S234, the calculation formula of the distribution thermal image value y of the predetermined distribution diagram is: ; In the formula, R represents the influence weight, d ave Represents the mean pixel value of all pixels in the predetermined distribution map.

[0054] In this embodiment of the present invention, S3 includes the following sub-steps:

[0055] S31, calculating the difference between the temperature distribution diagram and the distribution thermal image value at other times;

[0056] S32. Calculate whether the sum of all differences is within the normal temperature range of the PE insulation pipe. If so, there is no abnormality on the surface of the PE insulation pipe during the processing; otherwise, there is an abnormality on the surface of the PE insulation pipe during the processing.

[0057] In the present invention, according to the differences between the distributed thermal image values ​​at other times, it is determined whether the sum of all the differences does not belong to the normal temperature range, thereby determining whether there is a temperature anomaly.

[0058] In the embodiment of the present invention, in S31, the difference Z between the temperature distribution map at the i-th moment and the distribution thermal image value is i The calculation formula is: ; In the formula, y represents the distribution thermal image value of the predetermined distribution map, N represents the number of pixels in the temperature distribution map at the i-th moment, e represents the index, d i_n Represents the pixel value of the nth pixel in the temperature distribution map at the i-th moment.

[0059] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A method for monitoring the processing temperature of a PE insulation pipe, characterized in that: The following steps are involved: S1. Use an infrared thermal imager to obtain the temperature distribution diagram of the surface of the PE insulation pipe at each moment during the processing; S2, selecting a predetermined distribution map from the temperature distribution maps at all times, and determining the distribution thermal image value of the predetermined distribution map; S3. Determine whether there is any abnormality on the surface of the PE insulation pipe during the processing according to the distribution thermal image value of the predetermined distribution diagram; The S2 comprises the following sub-steps: S21, calculating the degree of change corresponding to the temperature distribution graph at each moment, and taking the temperature distribution graph with the minimum degree of change as the predetermined distribution graph; S22, performing grayscale processing on the predetermined distribution map to obtain a predetermined distribution grayscale map, and generating a thermal image relationship equation for the predetermined distribution grayscale map; S23, determining the distributed thermal image value of the predetermined distribution diagram according to the value corresponding to the thermal image relationship formula; The S23 comprises the following sub-steps: S231, judging whether the value of the thermal image relationship formula belongs to the normal temperature range of the PE insulation pipe, if so, proceeding to S232, otherwise proceeding to S233; S232, taking the ratio between the difference between the highest normal temperature and the lowest normal temperature of the PE insulation pipe and the value of the thermal image relationship as the influence weight, and proceeding to S234; S233, taking the ratio between the highest normal temperature of the PE insulation pipe and the value of the thermal image relationship as the influence weight, and proceeding to S234; S234, determining the distribution thermal image value of the predetermined distribution map according to the influence weight; In S234, the calculation formula of the distribution thermal image value y of the predetermined distribution diagram is: ; In the formula, R represents the influence weight, d ave Represents the mean pixel value of all pixels in the predetermined distribution map.

2. The PE insulation pipe processing temperature monitoring method according to claim 1 is characterized in that: In S21, the calculation formula of the change degree E of the temperature distribution diagram is: ; Where M represents the number of pixels in the temperature distribution map, d m Represents the pixel value of the mth pixel in the temperature distribution map, d m+1 represents the pixel value of the m+1th pixel in the temperature distribution map, and σ represents the standard deviation of the pixel values ​​of all pixels in the temperature distribution map.

3. The PE insulation pipe processing temperature monitoring method according to claim 1 is characterized in that: In S22, the thermal image relationship T of the predetermined distribution grayscale image is expressed as: ; Wherein, T1 represents the minimum temperature value obtained by the infrared thermal imager, T2 represents the maximum temperature value obtained by the infrared thermal imager, Y1 represents the minimum grayscale value of the predetermined distribution graph, Y2 represents the maximum grayscale value of the predetermined distribution graph, and Y ave Represents the mean grayscale value of all pixels in the predetermined distribution map.

4. The PE insulation pipe processing temperature monitoring method according to claim 1 is characterized in that: The S3 comprises the following sub-steps: S31, calculating the difference between the temperature distribution diagram and the distribution thermal image value at other times; S32. Calculate whether the sum of all differences is within the normal temperature range of the PE insulation pipe. If so, there is no abnormality on the surface of the PE insulation pipe during the processing; otherwise, there is an abnormality on the surface of the PE insulation pipe during the processing.

5. The PE insulation pipe processing temperature monitoring method according to claim 4 is characterized in that: In S31, the difference Z between the temperature distribution map at the i-th moment and the distribution thermal image value i The calculation formula is: ; In the formula, y represents the distribution thermal image value of the predetermined distribution map, N represents the number of pixels in the temperature distribution map at the i-th moment, e represents the index, d i_n Represents the pixel value of the nth pixel in the temperature distribution map at the i-th moment.

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