Method and device for detecting the temperature of extruded rubber of a tyre

Abstract

The application discloses a kind of tire extrusion glue temperature detection method and device.Therein, the method includes: obtaining the infrared thermal imaging image of tire extrusion glue on tire extrusion production line;Determine the first pixel value of all pixels corresponding to the first preset horizontal coordinate in infrared thermal imaging image;All first pixel values are binarized, and a plurality of second pixel values are obtained, and each target longitudinal coordinate corresponding to the first preset horizontal coordinate is determined according to the second pixel value;Determine each target detection area in infrared thermal imaging image according to the first preset horizontal coordinate, the second preset horizontal coordinate and each target longitudinal coordinate;All pixels in each target detection area are traversed, and temperature anomaly area in target detection area is determined according to the pixel value of each pixel;Output temperature detection result.The application solves the technical problems of low real-time accuracy and poor stability of related tire extrusion glue temperature detection scheme.

Description

Technical Field

[0001] This application relates to the field of tire manufacturing technology, and more specifically, to a method and apparatus for detecting the temperature of tire extruded rubber. Background Technology

[0002] With the continuous development of the automotive industry, temperature monitoring of tire extrusion rubber has become increasingly important in the tire manufacturing process. The quality of automotive tires directly affects vehicle safety and performance, especially during high-speed driving and harsh environments. As a key step in tire manufacturing, temperature control of tire extrusion rubber is crucial for ensuring tire quality. During tire production, due to factors such as high-temperature extrusion, friction, and compression, the temperature of the extruded rubber may continuously rise. This not only affects the rheological properties and molding quality of the rubber compound but may also lead to over-curing or under-curing, thus impacting the overall performance and durability of the tire.

[0003] However, traditional temperature detection methods are usually unable to achieve real-time and comprehensive monitoring of the temperature of extruded rubber. These methods typically rely on point thermometers or contact sensors, which usually provide only limited information and cannot fully reflect the temperature status of the extruded rubber.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This application provides a method and apparatus for detecting the temperature of tire extruded rubber, thereby at least solving the technical problems of low real-time accuracy and poor stability of related tire extruded rubber temperature detection schemes.

[0006] According to one aspect of the embodiments of this application, a method for detecting the temperature of tire extruded rubber is provided, comprising: acquiring an infrared thermal imaging image of tire extruded rubber on a tire extrusion production line; determining the first pixel value of all pixels corresponding to a first preset horizontal coordinate in the infrared thermal imaging image, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line; performing binarization processing on all the first pixel values ​​to obtain a plurality of second pixel values, and determining each target vertical coordinate corresponding to the first preset horizontal coordinate based on the second pixel values, wherein the target vertical coordinate is the vertical coordinate of the pixel with a second pixel value of 1 in two adjacent pixels when the second pixel values ​​of two adjacent pixels change from 0 to 1 or from 1 to 0; determining each target detection area in the infrared thermal imaging image based on the first preset horizontal coordinate, the second preset horizontal coordinate, and each target vertical coordinate; traversing all pixels in each target detection area, and determining a temperature anomaly area in the target detection area based on the pixel value of each pixel; and outputting a temperature detection result, wherein the temperature detection result includes at least: the temperature and coordinates of the temperature anomaly area.

[0007] Optionally, acquiring infrared thermal imaging images of tire extruded rubber on the tire extrusion production line includes: acquiring infrared thermal imaging images of tire extruded rubber on the tire extrusion production line using an infrared image acquisition device at a preset acquisition frequency, wherein the infrared image acquisition device is located directly above the tire extrusion production line, the preset acquisition frequency is determined by the rubber extrusion speed of the tire extrusion production line, and tire extruded rubber at any position on the tire extrusion production line will be acquired once by the infrared image acquisition device.

[0008] Optionally, all first pixel values ​​are binarized to obtain multiple second pixel values, including: for each first pixel value, the first pixel value is binarized according to a first preset threshold; if the first pixel value is less than the first preset threshold, the second pixel value corresponding to the first pixel value is determined to be 0; if the first pixel value is not less than the first preset threshold, the second pixel value corresponding to the first pixel value is determined to be 1.

[0009] Optionally, determining the target ordinates corresponding to the first preset horizontal coordinate based on the second pixel value includes: traversing the second pixel values ​​of all pixels corresponding to the first preset horizontal coordinate and comparing the second pixel values ​​of adjacent pixels; if the second pixel values ​​of two adjacent pixels change from 0 to 1, determining the ordinate of the pixel with a second pixel value of 1 among the two adjacent pixels as the ordinate of the first type of target; if the second pixel values ​​of two adjacent pixels change from 1 to 0, determining the ordinate of the pixel with a second pixel value of 1 among the two adjacent pixels as the ordinate of the second type of target; if the second pixel value of the first pixel is 1, determining the ordinate of the first pixel as the ordinate of the first type of target; if the second pixel value of the last pixel is 1, determining the ordinate of the last pixel as the ordinate of the second type of target.

[0010] Optionally, determining each target detection region in the infrared thermal imaging image based on the first preset abscissa, the second preset abscissa, and the ordinates of each target includes: if no first-type target ordinate is detected, determining that there is no target detection region in the infrared thermal imaging image; if at least one first-type target ordinate and one second-type target ordinate are detected, grouping adjacent first-type target ordinates and second-type target ordinates in pairs, and for each group of first-type target ordinates and second-type target ordinates, determining a rectangular target detection region with the first-type target ordinate, the second-type target ordinate, the first preset abscissa, and the second preset abscissa as vertices.

[0011] Optionally, the temperature anomaly region in the target detection area is determined based on the pixel value of each pixel, including: for each pixel in the target detection area, the pixel value of the pixel is matched with multiple preset temperature ranges, and the temperature anomaly level corresponding to the pixel is determined based on the matching result, wherein each preset temperature range corresponds to a temperature anomaly level; pixels with the same temperature anomaly level are divided into a type of temperature anomaly region, resulting in multiple types of temperature anomaly regions corresponding to multiple temperature anomaly levels.

[0012] Optionally, the infrared thermal imaging image is converted into an RGB three-channel image; different colors are used to mark various temperature anomaly areas in the RGB three-channel image.

[0013] Optionally, the pixel values ​​of all pixels in the infrared thermal imaging image are traversed to determine the global maximum temperature, global minimum temperature, and global average temperature of the infrared thermal imaging image, and the regional maximum temperature, regional minimum temperature, and regional average temperature of each target detection area are determined.

[0014] Optionally, the output temperature detection results include: displaying RGB three-channel images marked with various temperature anomaly areas in the display interface, and issuing alarm information corresponding to each type of temperature anomaly area; displaying target detection information in the display interface, wherein the target detection information includes at least one of the following: the global maximum temperature, global minimum temperature, and global average temperature of the infrared thermal imaging image, the regional maximum temperature, regional minimum temperature, and regional average temperature of the target detection area, and the temperature anomaly level corresponding to each type of temperature anomaly area.

[0015] According to another aspect of the embodiments of this application, a tire extrusion rubber temperature detection device is also provided, comprising: an acquisition module for acquiring an infrared thermal imaging image of tire extrusion rubber on a tire extrusion production line; a first determination module for determining the first pixel value of all pixels corresponding to a first preset horizontal coordinate in the infrared thermal imaging image, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line; a second determination module for binarizing all the first pixel values ​​to obtain a plurality of second pixel values, and determining each target vertical coordinate corresponding to the first preset horizontal coordinate based on the second pixel values, wherein the target vertical coordinate is the vertical coordinate of the pixel with a second pixel value of 1 in two adjacent pixels when the second pixel values ​​of two adjacent pixels change from 0 to 1 or from 1 to 0; a third determination module for determining each target detection area in the infrared thermal imaging image based on the first preset horizontal coordinate, the second preset horizontal coordinate, and each target vertical coordinate; a fourth determination module for traversing all pixels in each target detection area and determining a temperature anomaly area in the target detection area based on the pixel value of each pixel; and an output module for outputting a temperature detection result, wherein the temperature detection result includes at least the temperature and coordinates of the temperature anomaly area.

[0016] According to another aspect of the embodiments of this application, a computer program product is also provided, the computer program product comprising: a computer program, wherein the computer program, when executed by a processor, implements the above-described tire extrusion rubber temperature detection method.

[0017] According to another aspect of the embodiments of this application, an electronic device is also provided, the electronic device comprising: a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-described tire extrusion rubber temperature detection method through the computer program.

[0018] In this embodiment, an infrared thermal imaging image of tire extrusion rubber on a tire extrusion production line is acquired; the first pixel value of all pixels corresponding to a first preset horizontal coordinate in the infrared thermal imaging image is determined, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line; all first pixel values ​​are binarized to obtain multiple second pixel values, and each target vertical coordinate corresponding to the first preset horizontal coordinate is determined based on the second pixel values, wherein the target vertical coordinate is the vertical coordinate of the pixel with a second pixel value of 1 in two adjacent pixels when the second pixel values ​​of two adjacent pixels change from 0 to 1 or from 1 to 0; each target detection area in the infrared thermal imaging image is determined based on the first preset horizontal coordinate, the second preset horizontal coordinate, and each target vertical coordinate; all pixels in each target detection area are traversed, and temperature anomaly areas in the target detection area are determined based on the pixel values ​​of each pixel; the temperature detection result is output, wherein the temperature detection result includes at least the temperature and coordinates of the temperature anomaly area. Among them, infrared thermal imaging technology is used to detect the temperature of extruded rubber in the tire extrusion production line. This eliminates the need for physical contact with the sensor, avoids impacting the tire extrusion production line, and improves the flexibility of tire extruded rubber temperature detection. Image processing technology can accurately locate the target detection area on the tire extrusion production line, enabling real-time and comprehensive detection of the temperature of the tire extruded rubber. This effectively solves the technical problems of low real-time accuracy and poor stability in related tire extruded rubber temperature detection solutions. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0020] Figure 1 This is a schematic diagram of the structure of an optional computer terminal according to an embodiment of this application;

[0021] Figure 2 This is a schematic flowchart of an optional tire extrusion rubber temperature detection method according to an embodiment of this application;

[0022] Figure 3 This is a schematic diagram of the positional structure between an optional infrared image acquisition device and a tire extrusion production line according to an embodiment of this application;

[0023] Figure 4 This is a schematic diagram of an optional tire extrusion rubber temperature detection device according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., used in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] Example 1

[0027] According to an embodiment of this application, a method for detecting the temperature of tire extruded rubber is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0028] The methods and embodiments provided in this application can be executed on mobile terminals, computer terminals, or similar computing devices. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing a method for detecting the temperature of extruded rubber in tires is shown. Figure 1As shown, the computer terminal 10 (or mobile device 10) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0029] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0030] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the tire extrusion rubber temperature detection method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the above-mentioned application vulnerability detection method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0031] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0032] The display can be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0033] Under the above operating environment, embodiments of this application provide a method for detecting the temperature of tire extruded rubber, such as... Figure 2 As shown, the method includes the following steps:

[0034] Step S202: Obtain an infrared thermal imaging image of the tire extrusion rubber on the tire extrusion production line;

[0035] Step S204: Determine the first pixel value of all pixels corresponding to the first preset horizontal coordinate in the infrared thermal imaging image, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line.

[0036] Step S206: Binarize all first pixel values ​​to obtain multiple second pixel values, and determine the target ordinates corresponding to the first preset horizontal coordinates based on the second pixel values. The target ordinates are the ordinates of the pixels with a second pixel value of 1 in the two adjacent pixels when the second pixel values ​​of the two adjacent pixels change from 0 to 1 or from 1 to 0.

[0037] Step S208: Determine the detection area of ​​each target in the infrared thermal imaging image based on the first preset horizontal coordinate, the second preset horizontal coordinate, and the vertical coordinate of each target.

[0038] Step S210: Traverse all pixels in each target detection area and determine the temperature anomaly area in the target detection area based on the pixel value of each pixel.

[0039] Step S212: Output the temperature detection results, which include at least the temperature and coordinates of the temperature anomaly area.

[0040] The following describes each step of the tire extrusion rubber temperature detection method in conjunction with the specific implementation process.

[0041] As an optional implementation, infrared thermal imaging images of tire extruded rubber on the tire extrusion production line can be obtained in the following way: infrared thermal imaging images of tire extruded rubber on the tire extrusion production line are acquired using an infrared image acquisition device at a preset acquisition frequency. The infrared image acquisition device is located directly above the tire extrusion production line, and the preset acquisition frequency is determined by the rubber extrusion speed of the tire extrusion production line. Tire extruded rubber at any position on the tire extrusion production line will be acquired once by the infrared image acquisition device.

[0042] Figure 3 A schematic diagram illustrating the positional structure between an optional infrared image acquisition device and a tire extrusion production line is shown, such as... Figure 3 As shown, the extruder and the extruded rubber surface together constitute the tire extrusion production line. The infrared image acquisition device is an infrared thermal imaging camera. By adjusting the position of the infrared thermal imaging camera, a real-time infrared thermal imaging image of the complete tire extruded rubber can be captured. The fact that the tire extruded rubber at any position on the tire extrusion production line will be acquired once by the infrared image acquisition device means that there is no gap or overlap between the acquired infrared thermal imaging images.

[0043] After determining the first pixel value of all pixels corresponding to the first preset horizontal coordinate in the infrared thermal imaging image, multiple second pixel values ​​can be obtained in the following way: For each first pixel value, the first pixel value is binarized according to the first preset threshold. If the first pixel value is less than the first preset threshold, the second pixel value corresponding to the first pixel value is determined to be 0. If the first pixel value is not less than the first preset threshold, the second pixel value corresponding to the first pixel value is determined to be 1.

[0044] For example, for the first pixel value {p1,…,p1} corresponding to the first preset horizontal coordinate x1... k The first preset threshold p, and the specific formula for the corresponding second pixel value are as follows:

[0045]

[0046] Optionally, the target ordinates corresponding to the first preset horizontal coordinate can be determined based on the second pixel value in the following manner: traverse the second pixel values ​​of all pixels corresponding to the first preset horizontal coordinate and compare the second pixel values ​​of adjacent pixels; if the second pixel values ​​of two adjacent pixels change from 0 to 1, determine the ordinate of the pixel with a second pixel value of 1 as the ordinate of the first type of target; if the second pixel values ​​of two adjacent pixels change from 1 to 0, determine the ordinate of the pixel with a second pixel value of 1 as the ordinate of the second type of target; if the second pixel value of the first pixel is 1, determine the ordinate of the first pixel as the ordinate of the first type of target; if the second pixel value of the last pixel is 1, determine the ordinate of the last pixel as the ordinate of the second type of target.

[0047] Understandably, to ensure proper comparison of the second pixel values ​​of adjacent pixels, zeros can be padded before and after the second pixel value array. That is, if the second pixel value of the first pixel is 1, a zero is padded before the corresponding array; if the second pixel value of the last pixel is 1, a zero is padded after the corresponding array. Accordingly, the process of determining the ordinates of each target corresponding to the first preset horizontal coordinate based on the second pixel value is the process of difference operation, and the specific formula is as follows:

[0048] err[i]=p i -p i-1 ,i∈{1,…,k+1}

[0049] Where err[i] represents the difference operation result at the i-th position in the second pixel value array, p i p represents the second pixel value at the i-th position in the second pixel value array. i-1 This represents the second pixel value at the (i-1)th position in the second pixel value array.

[0050] Subsequently, the target detection areas in the infrared thermal imaging image can be determined in the following manner based on the first preset abscissa, the second preset abscissa, and the ordinates of each target: if no first-type target ordinate is detected, it is determined that there is no target detection area in the infrared thermal imaging image; if at least one first-type target ordinate and one second-type target ordinate are detected, adjacent first-type target ordinates and second-type target ordinates are grouped in pairs, and for each group of first-type target ordinates and second-type target ordinates, a rectangular target detection area is determined with the first-type target ordinate, the second-type target ordinate, the first preset abscissa, and the second preset abscissa as vertices.

[0051] Specifically, when all the second pixel values ​​in the second pixel value array are 0, the first type of target ordinate is not detected. In this case, it is determined that there is no target detection area in the infrared thermal imaging image. It should be noted that in some extreme cases, the first type of target ordinate and the second type of target ordinate are the same type of ordinate. In this case, the target detection area is a row of areas.

[0052] For example, given a first preset horizontal coordinate x1 and a second preset horizontal coordinate x2, when a first type of target with vertical coordinate y1 and a second type of target with vertical coordinate y2 are detected, the vertices of a rectangular target detection region are finally determined as: [x1,y1], [x1,y2], [x2,y1], [x2,y2]; when two first type of target with vertical coordinates y1, y1′ and second type of target with vertical coordinates y2, y2′ are detected, the vertices of the two rectangular target detection regions are finally determined as: [x1,y1], [x1,y2], [x2,y1], [x2,y2], and [x1,y1′], [x1,y2′], [x2,y1′], [x2,y2′].

[0053] Optionally, the temperature anomaly region in the target detection area can be determined based on the pixel value of each pixel in the following way: For each pixel in the target detection area, the pixel value of the pixel is matched with multiple preset temperature ranges, and the temperature anomaly level corresponding to the pixel is determined based on the matching result, wherein each preset temperature range corresponds to a temperature anomaly level; pixels with the same temperature anomaly level are divided into a type of temperature anomaly region, resulting in multiple types of temperature anomaly regions corresponding to multiple temperature anomaly levels.

[0054] The preset temperature range can be set according to actual needs. For example, the preset temperature range can be set to [0, t1] and (t1, t2]. Correspondingly, the temperature anomaly level corresponding to [0, t1] can be classified into the yellow temperature anomaly area, and the temperature anomaly level corresponding to (t1, t2) can be classified into the red temperature anomaly area.

[0055] Since infrared image acquisition devices collect infrared radiation emitted or reflected by objects, which consists of only single-channel thermal image information, it is necessary to convert the single-channel thermal image information into a three-channel RGB image for display.

[0056] Specifically, infrared thermal imaging images can be converted into RGB three-channel images; different colors can be used to mark various temperature anomaly areas in the RGB three-channel images.

[0057] Specifically, the thermal image temperature information acquired by the infrared image acquisition device is first normalized to the range of 0-1, using the following formula:

[0058]

[0059] Where temp is the acquired thermal image temperature information, min(temp) is the minimum thermal image temperature, max(temp) is the maximum thermal image temperature, and temp_nor is the final temperature information after normalization to the 0-1 range.

[0060] Next, the normalized temperature information is converted into a single-channel grayscale image, using the following formula:

[0061] grey_img = temp_nor * 255

[0062] Where rey_img is the converted grayscale image.

[0063] Finally, the color mapping is applied to the grayscale image obtained above using OpenCV's applyColorMap, thus obtaining the corresponding RGB three-channel image.

[0064] Optionally, the pixel values ​​of all pixels in the infrared thermal imaging image can be traversed to determine the global maximum temperature, global minimum temperature, and global average temperature of the infrared thermal imaging image, and the regional maximum temperature, regional minimum temperature, and regional average temperature of each target detection area can be determined.

[0065] Optionally, the temperature detection results can be output in the following ways: displaying RGB three-channel images with various temperature anomaly areas marked on the display interface, and issuing alarm information corresponding to each type of temperature anomaly area; displaying target detection information on the display interface, wherein the target detection information includes at least one of the following: the global maximum temperature, global minimum temperature, and global average temperature of the infrared thermal imaging image, the regional maximum temperature, regional minimum temperature, and regional average temperature of the target detection area, and the temperature anomaly level corresponding to each type of temperature anomaly area.

[0066] It should be noted that when a yellow temperature anomaly area exists in the target detection area, the coordinates of the corresponding area will be displayed in a yellow box on the display interface, and a voice alarm will be issued; when a red temperature anomaly area exists in the target detection area, the coordinates of the corresponding area will be displayed in a red box on the display interface, and a voice alarm will be issued.

[0067] In this embodiment, an infrared thermal imaging image of tire extrusion rubber on a tire extrusion production line is acquired; the first pixel value of all pixels corresponding to a first preset horizontal coordinate in the infrared thermal imaging image is determined, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line; all first pixel values ​​are binarized to obtain multiple second pixel values, and each target vertical coordinate corresponding to the first preset horizontal coordinate is determined based on the second pixel values, wherein the target vertical coordinate is the vertical coordinate of the pixel with a second pixel value of 1 in two adjacent pixels when the second pixel values ​​of two adjacent pixels change from 0 to 1 or from 1 to 0; each target detection area in the infrared thermal imaging image is determined based on the first preset horizontal coordinate, the second preset horizontal coordinate, and each target vertical coordinate; all pixels in each target detection area are traversed, and temperature anomaly areas in the target detection area are determined based on the pixel values ​​of each pixel; the temperature detection result is output, wherein the temperature detection result includes at least the temperature and coordinates of the temperature anomaly area. Among them, infrared thermal imaging technology is used to detect the temperature of extruded rubber in the tire extrusion production line. This eliminates the need for physical contact with the sensor, avoids impacting the tire extrusion production line, and improves the flexibility of tire extruded rubber temperature detection. Image processing technology can accurately locate the target detection area on the tire extrusion production line, enabling real-time and comprehensive detection of the temperature of the tire extruded rubber. This effectively solves the technical problems of low real-time accuracy and poor stability in related tire extruded rubber temperature detection solutions.

[0068] Example 2

[0069] According to an embodiment of this application, a tire extrusion rubber temperature detection device is also provided for implementing the tire extrusion rubber temperature detection method in Embodiment 1, such as... Figure 4 As shown, the tire extrusion rubber temperature detection device includes at least: an acquisition module 41, a first determination module 42, a second determination module 43, a third determination module 44, a fourth determination module 45, and an output module 46, wherein:

[0070] The acquisition module 41 can acquire infrared thermal imaging images of the tire extrusion rubber on the tire extrusion production line;

[0071] The first determining module 42 can determine the first pixel value of all pixels corresponding to the first preset horizontal coordinate in the infrared thermal imaging image, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line.

[0072] The second determining module 43 can perform binarization processing on all first pixel values ​​to obtain multiple second pixel values, and determine each target ordinate corresponding to the first preset horizontal coordinate based on the second pixel values. The target ordinate is the ordinate of the pixel with a second pixel value of 1 in two adjacent pixels when the second pixel value of two adjacent pixels changes from 0 to 1 or from 1 to 0.

[0073] The third determining module 44 can determine the detection area of ​​each target in the infrared thermal imaging image based on the first preset horizontal coordinate, the second preset horizontal coordinate and the vertical coordinate of each target.

[0074] The fourth determination module 45 can traverse all pixels in each target detection area and determine the temperature anomaly area in the target detection area based on the pixel value of each pixel.

[0075] The output module 46 can output temperature detection results, which include at least the temperature and coordinates of the temperature anomaly area.

[0076] The following describes the functions of each module of the tire extrusion rubber temperature detection device in conjunction with the specific implementation process.

[0077] As an optional implementation, the acquisition module can acquire infrared thermal imaging images of tire extruded rubber on the tire extrusion production line in the following way: the infrared image acquisition device acquires infrared thermal imaging images of tire extruded rubber on the tire extrusion production line at a preset acquisition frequency, wherein the infrared image acquisition device is located directly above the tire extrusion production line, the preset acquisition frequency is determined by the rubber extrusion speed of the tire extrusion production line, and the tire extruded rubber at any position on the tire extrusion production line will be acquired once by the infrared image acquisition device.

[0078] After determining the first pixel value of all pixels corresponding to the first preset horizontal coordinate in the infrared thermal imaging image, the second determining module can obtain multiple second pixel values ​​in the following way: for each first pixel value, the first pixel value is binarized according to the first preset threshold. If the first pixel value is less than the first preset threshold, the second pixel value corresponding to the first pixel value is determined to be 0. If the first pixel value is not less than the first preset threshold, the second pixel value corresponding to the first pixel value is determined to be 1.

[0079] Optionally, the second determining module can determine the target ordinates corresponding to the first preset horizontal coordinate based on the second pixel value in the following manner: traverse the second pixel values ​​of all pixels corresponding to the first preset horizontal coordinate, and compare the second pixel values ​​of adjacent pixels; if the second pixel values ​​of two adjacent pixels change from 0 to 1, determine the ordinate of the pixel with a second pixel value of 1 in the two adjacent pixels as the ordinate of the first type of target; if the second pixel values ​​of two adjacent pixels change from 1 to 0, determine the ordinate of the pixel with a second pixel value of 1 in the two adjacent pixels as the ordinate of the second type of target; if the second pixel value of the first pixel is 1, determine the ordinate of the first pixel as the ordinate of the first type of target; if the second pixel value of the last pixel is 1, determine the ordinate of the last pixel as the ordinate of the second type of target.

[0080] It is understandable that, in order to make the second pixel values ​​of adjacent pixels comparable, zeros can be padded before and after the second pixel value array. That is, if the second pixel value of the first pixel is 1, zeros are padded before the corresponding array; if the second pixel value of the last pixel is 1, zeros are padded after the corresponding array. Accordingly, the process of determining the vertical coordinates of each target corresponding to the first preset horizontal coordinate based on the second pixel value is the process of difference operation.

[0081] Subsequently, the third determining module can determine the target detection area in the infrared thermal imaging image based on the first preset abscissa, the second preset abscissa, and the ordinates of each target in the following manner: if no first-type target ordinate is detected, it is determined that there is no target detection area in the infrared thermal imaging image; if at least one first-type target ordinate and one second-type target ordinate are detected, adjacent first-type target ordinates and second-type target ordinates are grouped in pairs, and for each group of first-type target ordinates and second-type target ordinates, a rectangular target detection area is determined with the first-type target ordinate, the second-type target ordinate, the first preset abscissa, and the second preset abscissa as vertices.

[0082] Specifically, when all the second pixel values ​​in the second pixel value array are 0, the first type of target ordinate is not detected. In this case, it is determined that there is no target detection area in the infrared thermal imaging image. It should be noted that in some extreme cases, the first type of target ordinate and the second type of target ordinate are the same type of ordinate. In this case, the target detection area is a row of areas.

[0083] For example, given a first preset horizontal coordinate x1 and a second preset horizontal coordinate x2, when a first type of target with vertical coordinate y1 and a second type of target with vertical coordinate y2 are detected, the vertices of a rectangular target detection region are finally determined as: [x1,y1], [x1,y2], [x2,y1], [x2,y2]; when two first type of target with vertical coordinates y1, y1′ and second type of target with vertical coordinates y2, y2′ are detected, the vertices of the two rectangular target detection regions are finally determined as: [x1,y1], [x1,y2], [x2,y1], [x2,y2], and [x1,y1′], [x1,y2′], [x2,y1′], [x2,y2′].

[0084] Optionally, the fourth determining module can determine the temperature anomaly region in the target detection area based on the pixel value of each pixel in the following way: for each pixel in the target detection area, the pixel value of the pixel is matched with multiple preset temperature ranges, and the temperature anomaly level corresponding to the pixel is determined based on the matching result, wherein each preset temperature range corresponds to a temperature anomaly level; pixels with the same temperature anomaly level are divided into a type of temperature anomaly region, resulting in multiple types of temperature anomaly regions corresponding to multiple temperature anomaly levels.

[0085] The preset temperature range can be set according to actual needs. For example, the preset temperature range can be set to [0, t1] and (t1, t2]. Correspondingly, the temperature anomaly level corresponding to [0, t1] can be classified into the yellow temperature anomaly area, and the temperature anomaly level corresponding to (t1, t2) can be classified into the red temperature anomaly area.

[0086] Since infrared image acquisition devices collect infrared radiation emitted or reflected by objects, which consists of only single-channel thermal image information, it is necessary to convert the single-channel thermal image information into a three-channel RGB image for display.

[0087] Specifically, infrared thermal imaging images can be converted into RGB three-channel images; different colors can be used to mark various temperature anomaly areas in the RGB three-channel images.

[0088] Specifically, the thermal image temperature information acquired by the infrared image acquisition device is first normalized to the range of 0-1. Then, the normalized temperature information is converted into a single-channel grayscale image. Finally, the color mapping is applied to the grayscale image obtained above using the applyColorMap function in OpenCV, thus obtaining the corresponding RGB three-channel image.

[0089] Optionally, the device may also include a temperature determination module, which is used to traverse the pixel values ​​of all pixels in the infrared thermal imaging image, determine the global maximum temperature, global minimum temperature and global average temperature of the infrared thermal imaging image, and determine the regional maximum temperature, regional minimum temperature and regional average temperature of each target detection area.

[0090] Optionally, the output module can output the temperature detection results in the following ways: displaying RGB three-channel images with various temperature anomaly areas marked on the display interface, and issuing alarm information corresponding to each type of temperature anomaly area; displaying target detection information on the display interface, wherein the target detection information includes at least one of the following: the global maximum temperature, global minimum temperature, and global average temperature of the infrared thermal imaging image, the regional maximum temperature, regional minimum temperature, and regional average temperature of the target detection area, and the temperature anomaly level corresponding to each type of temperature anomaly area.

[0091] It should be noted that when a yellow temperature anomaly area exists in the target detection area, the coordinates of the corresponding area will be displayed in a yellow box on the display interface, and a voice alarm will be issued; when a red temperature anomaly area exists in the target detection area, the coordinates of the corresponding area will be displayed in a red box on the display interface, and a voice alarm will be issued.

[0092] It should be noted that each module in the tire extrusion rubber temperature detection device in this embodiment corresponds one-to-one with each implementation step of the tire extrusion rubber temperature detection method in Embodiment 1. Since Embodiment 1 has been described in detail, some details not shown in this embodiment can be referred to Embodiment 1, and will not be elaborated further here.

[0093] Example 3

[0094] According to an embodiment of this application, a computer program product is also provided, which includes a computer program, wherein when the computer program is executed by a processor, it implements the tire extrusion rubber temperature detection method in Embodiment 1.

[0095] According to an embodiment of this application, a non-volatile storage medium is also provided, which includes a stored computer program, wherein the device containing the non-volatile storage medium executes the tire extrusion rubber temperature detection method in Embodiment 1 by running the computer program.

[0096] According to an embodiment of this application, a processor is also provided for running a computer program, wherein the computer program executes the tire extrusion rubber temperature detection method of Embodiment 1.

[0097] According to an embodiment of this application, an electronic device is also provided, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the tire extrusion rubber temperature detection method of Embodiment 1 through the computer program.

[0098] Specifically, the computer program executes the following steps during runtime: acquiring an infrared thermal imaging image of the tire extrusion rubber on the tire extrusion production line; determining the first pixel value of all pixels corresponding to a first preset horizontal coordinate in the infrared thermal imaging image, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line; binarizing all the first pixel values ​​to obtain multiple second pixel values, and determining the target vertical coordinates corresponding to the first preset horizontal coordinate based on the second pixel values, wherein the target vertical coordinate is the vertical coordinate of the pixel with a second pixel value of 1 in two adjacent pixels when the second pixel values ​​of two adjacent pixels change from 0 to 1 or from 1 to 0; determining each target detection area in the infrared thermal imaging image based on the first preset horizontal coordinate, the second preset horizontal coordinate, and each target vertical coordinate; traversing all pixels in each target detection area, and determining the temperature anomaly area in the target detection area based on the pixel values ​​of each pixel; outputting the temperature detection result, wherein the temperature detection result includes at least the temperature and coordinates of the temperature anomaly area.

[0099] The sequence numbers of the above embodiments are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0100] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0101] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0102] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0103] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0104] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0105] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for detecting the temperature of tire extruded rubber, characterized in that, include: Acquire infrared thermal imaging images of tire extruded rubber on the tire extrusion production line; Determine the first pixel value of all pixels corresponding to the first preset horizontal coordinate in the infrared thermal imaging image, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line. Binarize all the first pixel values ​​to obtain multiple second pixel values, and determine each target ordinate corresponding to the first preset horizontal coordinate based on the second pixel values. The target ordinate is the ordinate of the pixel with a second pixel value of 1 in the two adjacent pixels when the second pixel value of the two adjacent pixels changes from 0 to 1 or from 1 to 0. The detection areas of each target in the infrared thermal imaging image are determined based on the first preset horizontal coordinate, the second preset horizontal coordinate, and the vertical coordinates of each target. Traverse all pixels in each target detection area and determine the temperature anomaly area in the target detection area based on the pixel value of each pixel; Output temperature detection results, wherein the temperature detection results include at least the temperature and coordinates of the temperature anomaly area.

2. The method according to claim 1, characterized in that, Acquire infrared thermal imaging images of tire extruded rubber on the tire extrusion production line, including: Infrared thermal imaging images of the extruded rubber on the tire extrusion production line are acquired using an infrared image acquisition device at a preset acquisition frequency. The infrared image acquisition device is located directly above the tire extrusion production line, and the preset acquisition frequency is determined by the rubber extrusion speed of the tire extrusion production line. The extruded rubber at any position on the tire extrusion production line will be acquired once by the infrared image acquisition device.

3. The method according to claim 1, characterized in that, Binarize all the first pixel values ​​to obtain multiple second pixel values, including: For each first pixel value, the first pixel value is binarized according to a first preset threshold. If the first pixel value is less than the first preset threshold, the second pixel value corresponding to the first pixel value is determined to be 0. If the first pixel value is not less than the first preset threshold, the second pixel value corresponding to the first pixel value is determined to be 1.

4. The method according to claim 3, characterized in that, Determining the vertical coordinates of each target corresponding to the first preset horizontal coordinate based on the second pixel value includes: Iterate through the second pixel values ​​of all pixels corresponding to the first preset horizontal coordinate, and compare the second pixel values ​​of adjacent pixels; If the second pixel value of two adjacent pixels changes from 0 to 1, the ordinate of the pixel with the second pixel value of 1 in the two adjacent pixels is determined as the ordinate of the first type of target. If the second pixel value of two adjacent pixels changes from 1 to 0, the ordinate of the pixel with the second pixel value of 1 in the two adjacent pixels is determined as the ordinate of the second type of target. If the second pixel value of the first pixel is 1, the ordinate of the first pixel is determined to be the ordinate of the first type of target; If the second pixel value of the last pixel is 1, the ordinate of the last pixel is determined to be the ordinate of the second type of target.

5. The method according to claim 4, characterized in that, Determining each target detection region in the infrared thermal imaging image based on the first preset abscissa, the second preset abscissa, and the ordinates of each target includes: If the first type of target's vertical coordinate is not detected, it is determined that there is no target detection area in the infrared thermal imaging image; If at least one first-type target ordinate and one second-type target ordinate are detected, adjacent first-type target ordinates and second-type target ordinates are grouped in pairs. For each group of first-type target ordinates and second-type target ordinates, a rectangular target detection area is determined with the first-type target ordinate, the second-type target ordinate, the first preset abscissa, and the second preset abscissa as vertices.

6. The method according to claim 1, characterized in that, Determining temperature anomaly regions within the target detection area based on the pixel values ​​of each pixel includes: For each pixel in the target detection area, the pixel value of the pixel is matched with multiple preset temperature ranges, and the temperature anomaly level corresponding to the pixel is determined based on the matching results, wherein each preset temperature range corresponds to a temperature anomaly level. Pixels with the same temperature anomaly level are divided into one type of temperature anomaly region, resulting in multiple types of temperature anomaly regions corresponding to multiple temperature anomaly levels.

7. The method according to claim 6, characterized in that, The method further includes: The infrared thermal imaging image is converted into an RGB three-channel image; Different colors are used to mark various temperature anomaly regions in the RGB three-channel image.

8. The method according to claim 7, characterized in that, The method further includes: By iterating through the pixel values ​​of all pixels in the infrared thermal imaging image, the global maximum temperature, global minimum temperature, and global average temperature of the infrared thermal imaging image are determined, and the regional maximum temperature, regional minimum temperature, and regional average temperature of each target detection area are determined.

9. The method according to claim 8, characterized in that, Output temperature detection results, including: The display interface shows the RGB three-channel images labeled with various types of temperature anomaly areas, and issues alarm information corresponding to each type of temperature anomaly area. The target detection information is displayed in the display interface, which includes at least one of the following: the global highest temperature, global lowest temperature, and global average temperature of the infrared thermal imaging image; the regional highest temperature, regional lowest temperature, and regional average temperature of the target detection area; and the temperature anomaly level corresponding to each type of temperature anomaly area.

10. A tire extrusion rubber temperature detection device, characterized in that, include: The acquisition module is used to acquire infrared thermal imaging images of the extruded rubber from the tire extrusion production line. The first determining module is used to determine the first pixel value of all pixels corresponding to the first preset horizontal coordinate in the infrared thermal imaging image, wherein the horizontal axis of the infrared thermal imaging image is perpendicular to the rubber discharge direction of the tire extrusion production line. The second determining module is used to perform binarization processing on all the first pixel values ​​to obtain multiple second pixel values, and determine each target ordinate corresponding to the first preset horizontal coordinate based on the second pixel values, wherein the target ordinate is the ordinate of the pixel with a second pixel value of 1 in the two adjacent pixels when the second pixel value of the two adjacent pixels changes from 0 to 1 or from 1 to 0. The third determining module is used to determine each target detection area in the infrared thermal imaging image based on the first preset horizontal coordinate, the second preset horizontal coordinate and the vertical coordinate of each target. The fourth determining module is used to traverse all pixels in each of the target detection areas and determine the temperature anomaly areas in the target detection areas based on the pixel values ​​of each pixel. The output module is used to output the temperature detection results, wherein the temperature detection results include at least the temperature and coordinates of the temperature anomaly area.

11. A computer program product, characterized in that, include: A computer program, wherein when executed by a processor, the computer program implements the tire extrusion rubber temperature detection method according to any one of claims 1 to 9.

12. An electronic device, characterized in that, include: A memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the tire extrusion rubber temperature detection method according to any one of claims 1 to 9 via the computer program.

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