Asphalt identification method and system

Abstract

The present invention provides an asphalt identification method and system, including: measuring the temperature data of asphalt through an infrared temperature sensor; wherein the temperature data includes the temperature data of asphalt during the production process and the temperature data of the discharge port; measuring the temperature data of asphalt during the production process through an infrared temperature sensor; determining whether the asphalt is qualified based on the video image data and the temperature data. In this method, machine vision and sensor data can be combined for analysis to automatically identify asphalt, thereby improving the accuracy of asphalt identification; and asphalt can be identified in time when the asphalt is discharged, which has the advantage of high timeliness.

Description

Technical Field

[0001] The present invention relates to the technical field of asphalt identification, and in particular to an asphalt identification method and system. Background Art

[0002] At present, traditional asphalt waste identification methods include appearance observation (manual), chemical analysis (laboratory testing), physical property testing, infrared spectrum detection, etc. However, the above traditional asphalt waste identification methods have problems such as requiring manpower, detection lag, and inability to detect in the production process. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide an asphalt identification method and system, which can use a combination of machine vision and sensor data for analysis, so as to automatically identify asphalt and improve the accuracy of asphalt identification; and can identify asphalt in time when it is unloaded, which has the advantage of high timeliness.

[0004] In the first aspect, an embodiment of the present invention provides an asphalt identification method, which is applied to an asphalt identification system, and the method includes: measuring the temperature data of the asphalt through an infrared temperature sensor; wherein the temperature data includes the temperature data of the asphalt during the production process and the temperature data of the discharge port; measuring the temperature data of the asphalt during the production process through an infrared temperature sensor; and determining whether the asphalt is qualified based on the video image data and the temperature data.

[0005] In an optional embodiment of the present application, the above-mentioned step of collecting video image data of the asphalt discharge port through a camera device includes: starting the camera device; in response to the operation of pressing the material switch, closing the electromagnetic relay, and starting to collect video image data of the asphalt discharge port through the camera device; in response to the operation of releasing the material switch, disconnecting the electromagnetic relay, and stopping collecting video image data of the asphalt discharge port through the camera device.

[0006] In an optional embodiment of the present application, the above-mentioned camera equipment is installed with a polarizing filter and an air-cooled cover; the polarizing filter is used to eliminate the influence of asphalt oil reflection on video image data; the air-cooled cover is used for cooling and dust removal; the infrared temperature sensor is provided with an air cooling system, and the air cooling system is used to remove dust and cool the infrared temperature sensor.

[0007] In an optional embodiment of the present application, the above-mentioned step of determining whether the asphalt is qualified based on the video image data includes: identifying the aggregate and white material in the asphalt based on the video image data, and determining the ratio of the aggregate and white material in the asphalt; if the ratio of the aggregate and white material in the asphalt is greater than a preset ratio threshold, determining that the asphalt is unqualified; if the ratio of the aggregate and white material in the asphalt is less than or equal to the ratio threshold, determining that the asphalt is qualified.

[0008] In an optional embodiment of the present application, the above-mentioned steps of identifying the flower white material in asphalt based on the video image data and determining the proportion of the flower white material in the asphalt include: binarizing the video image data to obtain a binary image; dilating the binary image; identifying the edges of the binary image after the dilation process, and determining the various regions of the binary image after the dilation process based on the edges; removing the regions with an area greater than a first threshold value from the binary image after the dilation process, and then removing the regions with an area less than a second threshold value to obtain a target image; wherein the target image is characterized as the area where the asphalt exists; determining multiple target areas in the target image; wherein the target area is characterized as the area where the flower white material exists; and taking the ratio of the sum of the areas of the multiple target areas to the area of ​​the target image as the proportion of the flower white material in the asphalt.

[0009] In an optional embodiment of the present application, the above-mentioned steps of identifying agglomerates in asphalt based on video image data and determining the proportion of agglomerates in asphalt include: performing Canny operator processing on the video image data to obtain a first image; performing dilation processing on the first image; performing inversion processing on the first image after dilation processing; removing areas with an area greater than a third threshold from the first image after inversion processing, and then removing areas with an area less than a fourth threshold to obtain a target image; wherein the target image is characterized as an area where asphalt exists; determining multiple target areas in the target image; wherein the target area is characterized as an area where agglomerates exist; and taking the ratio of the sum of the areas of the multiple target areas to the area of ​​the target image as the proportion of agglomerates in the asphalt.

[0010] In an optional embodiment of the present application, the above-mentioned step of determining whether the asphalt is qualified based on the temperature data includes: if the temperature data is greater than a preset first temperature threshold, or the temperature data is less than a preset second temperature threshold, determining that the asphalt is unqualified; if the temperature data is less than or equal to the first temperature threshold, and the temperature data is greater than or equal to the second temperature threshold, determining that the asphalt is qualified.

[0011] In an optional embodiment of the present application, after the above step of determining whether the asphalt is qualified based on the video image data and the temperature data, the method further includes: if the asphalt is unqualified, performing an alarm operation.

[0012] In an optional embodiment of the present application, after the above step of determining whether the asphalt is qualified based on the video image data and temperature data, the method also includes: storing the recognition result of the video image data, temperature data and asphalt; wherein the recognition result represents whether the asphalt is qualified.

[0013] In a second aspect, an embodiment of the present invention further provides an asphalt identification system for executing the above-mentioned asphalt identification method.

[0014] The embodiments of the present invention bring the following beneficial effects:

[0015] The embodiment of the present invention provides an asphalt identification method and system, which collects video image data of the asphalt discharge port through a camera device; measures the temperature data of the asphalt during the production process through an infrared temperature sensor; and determines whether the asphalt is qualified based on the video image data and the temperature data. In this method, machine vision and sensor data can be combined for analysis to automatically identify asphalt, thereby improving the accuracy of asphalt identification; and asphalt can be identified in a timely manner when it is discharged, which has the advantage of high timeliness.

[0016] Other features and advantages of the present disclosure will be set forth in the following description, or some features and advantages may be inferred or unambiguously determined from the description, or may be learned by implementing the above-mentioned technology of the present disclosure.

[0017] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 A flowchart of an asphalt identification method provided by an embodiment of the present invention;

[0020] Figure 2 A flow chart of another asphalt identification method provided by an embodiment of the present invention;

[0021] Figure 3 A schematic diagram of video image data provided by an embodiment of the present invention;

[0022] Figure 4 A schematic diagram of a binary image provided by an embodiment of the present invention;

[0023] Figure 5 A schematic diagram of an asphalt recognition result provided by an embodiment of the present invention;

[0024] Figure 6 A schematic diagram of an image provided by an embodiment of the present invention;

[0025] Figure 7 A schematic diagram of a non-uniform illumination correction result provided by an embodiment of the present invention;

[0026] Figure 8A schematic diagram of a binarization processing result provided by an embodiment of the present invention;

[0027] Fig. 9 A schematic diagram of a region screening result provided by an embodiment of the present invention;

[0028] Fig.10 A schematic diagram of another video image data provided by an embodiment of the present invention;

[0029] Fig.11 A schematic diagram of a first image provided by an embodiment of the present invention;

[0030] Fig.12 A schematic diagram of a target image provided by an embodiment of the present invention;

[0031] Fig.13 A schematic diagram of another asphalt recognition result provided by an embodiment of the present invention;

[0032] Fig.14 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] At present, traditional asphalt waste identification methods include appearance observation (manual), chemical analysis (laboratory testing), physical property testing, infrared spectrum detection, etc. However, the above traditional asphalt waste identification methods have problems such as requiring manpower, detection lag, and inability to detect in the production process.

[0035] Based on this, an asphalt identification method and system provided in an embodiment of the present invention specifically provides an asphalt material identification method based on infrared temperature measurement and video analysis, and an asphalt identification system for executing the method. The embodiment of the present invention can use machine vision and sensor data for analysis to automatically identify asphalt and improve the accuracy of asphalt identification; and can identify asphalt in time when it is unloaded, which has the advantage of high timeliness.

[0036] To facilitate understanding of this embodiment, a method for identifying asphalt disclosed in an embodiment of the present invention is first introduced in detail.

[0037] Embodiment 1:

[0038] The embodiment of the present invention provides an asphalt identification method, which is applied to an asphalt identification system. Figure 1 A flowchart of an asphalt identification method is shown, the asphalt identification method comprises the following steps:

[0039] Step S102, collecting video image data of the asphalt discharge port by means of a camera device.

[0040] In this embodiment, multiple cameras can be set at appropriate positions of the asphalt discharge port. The shooting range of the multiple cameras can cover all angles of the asphalt discharge process, and the video image data of the asphalt discharge port can be collected by the multiple cameras.

[0041] Step S104, measuring the temperature data of the asphalt by using an infrared temperature sensor; wherein the temperature data includes the temperature data of the asphalt during the production process and the temperature data of the discharge port.

[0042] In this embodiment, the temperature data of the asphalt can be detected by a sensor. In this embodiment, a high-precision infrared temperature sensor can be used to measure the temperature data of the asphalt, for example, the temperature data of the asphalt during the production process and the temperature data of the discharge port.

[0043] Step S106, determining whether the asphalt is qualified based on the video image data and the temperature data.

[0044] In this embodiment, a comprehensive analysis can be performed based on the video image data collected by the camera device and the temperature data measured by the infrared temperature sensor to determine whether the asphalt is qualified.

[0045] Among them, machine vision can be used to analyze the video image data collected by the camera equipment, and then the temperature data measured by the infrared temperature sensor can be analyzed through threshold comparison, so as to comprehensively judge whether the asphalt is qualified.

[0046] The embodiment of the present invention provides an asphalt identification method, which collects video image data of the asphalt discharge port through a camera device; measures the temperature data of the asphalt during the production process through an infrared temperature sensor; and determines whether the asphalt is qualified based on the video image data and the temperature data. In this method, machine vision and sensor data can be combined for analysis to automatically identify asphalt, thereby improving the accuracy of asphalt identification; and asphalt can be identified in a timely manner when it is discharged, which has the advantage of high timeliness.

[0047] Embodiment 2:

[0048] This embodiment provides another asphalt identification method, which is implemented on the basis of the above embodiment. Figure 2 A flowchart of another asphalt identification method is shown, the asphalt identification method comprises the following steps:

[0049] Step S202: collecting video image data of the asphalt discharge port by means of a camera.

[0050] In some embodiments, the camera device can be started; in response to the material switch being pressed, the electromagnetic relay is closed, and the video image data of the asphalt discharge port is collected through the camera device; in response to the material switch being released, the electromagnetic relay is disconnected, and the video image data of the asphalt discharge port is stopped from being collected through the camera device.

[0051] In the asphalt identification system of this embodiment, the material switch is connected to the electromagnetic relay. When the material switch is pressed, the electromagnetic relay is closed. When the asphalt identification system detects that the electromagnetic relay is closed, it can start to capture the video image data of the asphalt discharge port through the camera device; when the material switch is released, it can stop capturing the video image data of the asphalt discharge port through the camera device. Among them, the camera device can be always started.

[0052] In some embodiments, the camera device is equipped with a polarizing filter and an air-cooling cover; the polarizing filter is used to eliminate the influence of asphalt oil reflection on video image data; the air-cooling cover is used to cool down and remove dust;

[0053] In the production process of asphalt, the oily reflection of asphalt will affect the video analysis, and it is impossible to distinguish the reflection of white material (i.e. white material) from normal material. In addition, the discharge port of asphalt is a dusty environment, and the smoky environment will have a certain impact on the video analysis.

[0054] Therefore, the camera device of this embodiment can be installed with a polarizing filter and an air-cooled cover. The polarizing filter can eliminate the influence of asphalt oil reflection on video image data; the air-cooled cover can cool down and remove dust, so as to adapt to the high temperature, dust and smoke environment of the asphalt production line.

[0055] Step S204, measuring the temperature data of the asphalt by using an infrared temperature sensor; wherein the temperature data includes the temperature data of the asphalt during the production process and the temperature data of the discharge port.

[0056] In some embodiments, the infrared temperature sensor is provided with an air cooling system, and the air cooling system is used to remove dust and cool the infrared temperature sensor.

[0057] In order to adapt to the high temperature environment of the asphalt production line, the infrared temperature sensor in this embodiment can be provided with an air cooling system, which is used to remove dust and cool the infrared temperature sensor, thereby preventing dust from blocking the probe and causing inaccurate readings.

[0058] Step S206, determining whether the asphalt is qualified based on the video image data and the temperature data.

[0059] In this embodiment, the video image data can be analyzed by an asphalt recognition algorithm, and combined with the temperature data to determine whether the asphalt is qualified.

[0060] In some embodiments, the aggregate and white material in the asphalt can be identified based on the video image data, and the ratio of the aggregate and white material in the asphalt can be determined; if the ratio of the aggregate and white material in the asphalt is greater than a preset ratio threshold, the asphalt is determined to be unqualified; if the ratio of the aggregate and white material in the asphalt is less than or equal to the ratio threshold, the asphalt is determined to be qualified.

[0061] First of all, it should be noted that the asphalt is unqualified. If the proportion of the asphalt is too high, it can be determined that the asphalt is waste, that is, the asphalt is unqualified.

[0062] Among them, flower material and white material can be understood as the same thing. If the materials produced by stones without asphalt and stones with asphalt are all coated with asphalt, they are qualified materials; if there are more stones coated with asphalt and fewer stones without asphalt, it is flower material; if there are more stones without asphalt and fewer or almost no stones coated with asphalt, it is white material; flower material and white material can be collectively called flower and white material.

[0063] In some embodiments, the proportion of white matter in asphalt can be determined in the following manner: binarizing video image data to obtain a binary image; dilating the binary image; identifying the edges of the binary image after dilation, and determining the various regions of the binary image after dilation based on the edges; removing regions with an area greater than a first threshold from the binary image after dilation, and then removing regions with an area less than a second threshold to obtain a target image; wherein the target image is characterized as the region where asphalt exists; determining multiple target regions in the target image; wherein the target region is characterized as the region where white matter exists; and taking the ratio of the sum of the areas of the multiple target regions to the area of ​​the target image as the proportion of white matter in asphalt.

[0064] Unlike in the laboratory, the video image data collected in actual production cannot guarantee uniform brightness. Therefore, when binarizing the video image data, the average grayscale method cannot achieve the desired effect. Therefore, a separately set threshold is required to obtain a binary image. Figure 3 A schematic diagram of a video image data shown and Figure 4 A schematic diagram of a binary image is shown.

[0065] After obtaining the binary image, the image is expanded to fill the white material and some irrelevant areas (such as Figure 3 and Figure 4Dilation, also known as expansion, is an image processing technique that can increase the size of an object or change the visual effect of an image by adjusting the pixels of the image.

[0066] After that, the area of ​​the binary image after the expansion process can be calculated by finding the edge. For the area that is too large (i.e., the area that is larger than the first threshold), it is considered to be an irrelevant area and can be discarded. For the area that is too small (i.e., the area that is smaller than the second threshold), it is considered to be the effect of the reflection of the asphalt material and is also discarded, so as to obtain the target image characterized by the existence area of ​​asphalt.

[0067] Finally, the target image is analyzed for area and multiple target areas in the target image are determined. Figure 5 The schematic diagram of the identification result of an asphalt is shown. If the proportion of white material exceeds a certain threshold ratio, the batch of materials is considered to be unqualified, that is, the asphalt is unqualified.

[0068] For example, see Figure 6 The schematic diagram of an image shown in FIG. 1 can be identified by the following specific steps in this embodiment. Figure 6 The white material in the image shown can be used to determine whether the asphalt is qualified:

[0069] The first step is to take the grayscale channel of the image.

[0070] The second step is motion blurred image filtering.

[0071] A return value of the image is obtained through the cv2.Laplacian function. 100 in the return value can be defined as the critical threshold for judging whether it is motion blurred. If the return value is lower than 100, the image is considered to be motion blurred and cannot be recognized; if the return value is higher than 100, the image is considered not to be motion blurred and can enter the subsequent process.

[0072] The third step is to compensate for uneven illumination by using block threshold.

[0073] Calculate the average grayscale value of the entire image as X0; divide the image into multiple blocks of 128×128 pixels, and calculate the average grayscale value of the multiple blocks as X1. Perform illumination compensation on each block separately, and the compensation method is: the grayscale value of each pixel of the block G0=G0+X0-X1. This method can reduce the grayscale of the highlight area, increase the grayscale of the dark area, and make the illumination of the entire image tend to be average. See Figure 7 A schematic diagram of an uneven lighting correction result is shown.

[0074] The fourth step is binarization, which converts the grayscale image into a binary image.

[0075] The principle of binarization is: there are two grayscale thresholds t and maxT, the areas with grayscale lower than t and higher than maxT are marked black, and the areas with grayscale greater than or equal to t and less than or equal to maxT are marked white, to obtain a binary image; t represents the critical grayscale threshold of white material, grayscale greater than t, it is considered to be white material, maxT is the critical grayscale threshold of reflection, grayscale greater than maxT, it is considered to be reflection, and the interference of oily reflection on the image needs to be eliminated. Oily reflection and white material are very similar in the image, but the reflective area will be brighter, that is, the grayscale will be larger. At the same time, the Otsu method is used to obtain a binary image from the average image obtained in the three steps, and then the intersection is taken to obtain a binary image for subsequent processing. See also Figure 8 A schematic diagram of a binarization processing result is shown.

[0076] The fifth step is to dilate the binary image. The binary image is expanded with a 3×3 convolution kernel to fill the internal holes.

[0077] The sixth step is to identify the edges of the binary image after the dilation processing, and determine each area of ​​the binary image after the dilation processing based on the edges.

[0078] The seventh step is area screening. If there are multiple small reflective points in the image, these points need to be excluded and not included in the area ratio calculation method. In the image, there may be large-area reflective or highlighted areas such as the inner wall of the car, the rear logo, and the cross beam. The interference of these areas needs to be excluded. Qualified asphalt is the stone wrapped with asphalt oil, and the area must not be too large. There is a minimum area threshold uzone (i.e. the first threshold) and a maximum area threshold zone (i.e. the second threshold); take each area obtained in the sixth step, calculate their areas respectively, those with an area lower than uzone are considered to be small reflective points and excluded, and those with an area higher than zone are considered to be large-area reflections or highlights caused by various abnormal situations and excluded, thereby obtaining a target image characterized as the area where asphalt exists. The area in the target image is the target area characterized as the area where white material exists. You can refer to Fig. 9 A schematic diagram of a regional screening result is shown.

[0079] The eighth step is to calculate the area ratio. The ratio of the sum of the areas of the multiple target areas obtained in the seventh step to the area of ​​the target image is used as the ratio of the white material in the asphalt. A critical threshold for the area ratio is set. If the area ratio is higher than this threshold, the asphalt is considered unqualified, and if the area ratio is lower than this threshold, the asphalt is considered qualified.

[0080] In some embodiments, the proportion of cement in asphalt can be determined by:

[0081] Perform Canny operator processing on video image data to obtain a first image; perform dilation processing on the first image; perform inversion processing on the first image after dilation processing; remove areas with an area greater than a third threshold from the first image after inversion processing, and then remove areas with an area less than a fourth threshold to obtain a target image; wherein the target image is characterized as an area where asphalt exists; determine multiple target areas in the target image; wherein the target area is characterized as an area where agglomerates exist; and use the ratio of the sum of the areas of the multiple target areas to the area of ​​the target image as the proportion of agglomerates in the asphalt.

[0082] The Canny operator can be used for edge detection. The main goal is to find an optimal edge detection solution, that is, the detected edge should be as close to the actual edge as possible, while detecting as many edges as possible and minimizing the interference of noise on edge detection.

[0083] In this embodiment, after using the Canny operator to obtain the edge of the image, it is found that under a certain threshold (preferably 225 / 300) parameter, the Canny operator will not identify the edge inside the agglomerated material, while the normal material will be covered by the edge. Fig.10 Another schematic diagram of video image data shown in FIG. Fig.11 A schematic diagram of a first image is shown.

[0084] Therefore, in this embodiment, the first image processed by the Canny operator can be expanded and inverted in sequence, and the irrelevant large areas (i.e., areas with an area greater than the third threshold) and irrelevant small areas (i.e., areas with an area less than the fourth threshold) in the first image after the inversion process can be removed to obtain a binary image for further processing, which is called the target image. Fig.12 A schematic diagram of a target image is shown, wherein the target image is characterized by the presence area of ​​asphalt.

[0085] Similar to the above-mentioned method of identifying the white material, for the identification of the knotted material, multiple target areas in the target image that are characterized as the areas where the knotted material exists can also be determined. Fig.13 The schematic diagram of the identification result of another type of asphalt is shown. If the proportion of agglomerates exceeds a certain threshold ratio, the batch of materials is considered to be unqualified, that is, the asphalt is unqualified.

[0086] In addition to using machine vision to analyze the video image data collected by the camera device, this embodiment can also analyze the temperature data measured by the infrared temperature sensor through threshold comparison, so as to comprehensively determine whether the asphalt is qualified.

[0087] In some embodiments, if the temperature data is greater than a preset first temperature threshold, or the temperature data is less than a preset second temperature threshold, the asphalt is determined to be unqualified; if the temperature data is less than or equal to the first temperature threshold, and the temperature data is greater than or equal to the second temperature threshold, the asphalt is determined to be qualified.

[0088] In the asphalt production process, temperature has an important impact on asphalt quality and production efficiency. In asphalt production, the temperature needs to reach 160℃ to 220℃. The specific temperature varies according to different production processes and material properties, but is generally within this range.

[0089] The impact of temperature on asphalt production is mainly reflected in the following three aspects:

[0090] 1. Change the physical properties of asphalt. The increase in temperature will reduce the viscosity of asphalt, enhance its fluidity, make it easier to stir and mix, and facilitate production.

[0091] 2. Affect the chemical properties of asphalt. At high temperatures, asphalt will undergo polymerization, which will reduce its quality, so the production temperature needs to be controlled.

[0092] 3. Impact on environmental protection. During the asphalt production process, attention should be paid to controlling the temperature to avoid the generation of harmful substances such as smoke and volatile organic compounds due to excessively high temperatures.

[0093] The temperature at the discharge port is approximately between 100°C and 170°C. If the temperature data is lower than 100°C, the temperature may drop further during transportation and may not reach the temperature required for construction. If the temperature data is higher than 170°C (most likely because the temperature of the production process is too high, resulting in the material temperature at the discharge port being too high), the above situation will occur.

[0094] Therefore, in this embodiment, a first temperature threshold and a second temperature threshold may be set to detect the temperature data. Preferably, the first temperature threshold may be set to 170°C and the second temperature data may be set to 100°C.

[0095] Step S208: If the asphalt is unqualified, an alarm operation is performed.

[0096] If the asphalt is unqualified, the asphalt identification system in this embodiment can perform an alarm operation, for example, notifying on-site personnel through an on-site loudspeaker.

[0097] In some embodiments, the video image data, temperature data and the recognition result of the asphalt may also be stored; wherein the recognition result indicates whether the asphalt is qualified.

[0098] Therefore, on-site personnel can trace the material unloading process through video image data, temperature data and asphalt identification results.

[0099] In summary, the embodiment of the present invention provides an asphalt identification system that can automatically identify asphalt waste (blown material and agglomerate) and alarm, which can realize unmanned automatic asphalt identification without the need for people to observe the appearance on site.

[0100] Furthermore, the embodiments of the present invention can use a combination of machine vision and sensor data for analysis, thereby automatically identifying asphalt and improving the accuracy of asphalt identification; and can identify asphalt in a timely manner when it is unloaded, thus having the advantage of high timeliness.

[0101] Embodiment three:

[0102] Corresponding to the above method embodiment, an embodiment of the present invention provides an asphalt identification system for executing the asphalt identification method provided by the above embodiment.

[0103] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the asphalt identification system described above can refer to the corresponding process in the aforementioned embodiment of the asphalt identification method, and will not be repeated here.

[0104] Embodiment 4:

[0105] The embodiment of the present invention also provides an electronic device for executing the above-mentioned asphalt identification method; see Fig.14 A structural schematic diagram of an electronic device is shown, which includes a memory 100 and a processor 101, wherein the memory 100 is used to store one or more computer instructions, and the one or more computer instructions are executed by the processor 101 to implement the above-mentioned asphalt identification method.

[0106] Further, Fig.14 The electronic device shown further includes a bus 102 and a communication interface 103 , and the processor 101 , the communication interface 103 and the memory 100 are connected via the bus 102 .

[0107] The memory 100 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 103 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used. The bus 102 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.14 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0108] The processor 101 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 101. The above processor 101 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 100, and the processor 101 reads the information in the memory 100 and completes the steps of the method of the above embodiment in combination with its hardware.

[0109] An embodiment of the present invention also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the above-mentioned asphalt identification method. The specific implementation can be found in the method embodiment, which will not be repeated here.

[0110] The computer program product of the asphalt identification method and system provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods in the previous method embodiments. The specific implementation can be found in the method embodiments and will not be repeated here.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and / or device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0112] In addition, in the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0113] If the function is implemented in the form of 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 the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0114] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0115] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for identifying asphalt, characterized in that: Applied to an asphalt identification system, the method comprises: Collect video image data of the asphalt discharge port through a camera device; The temperature data of the asphalt is measured by an infrared temperature sensor; wherein the temperature data includes the temperature data of the asphalt during the production process and the temperature data of the discharge port; Determining whether the asphalt is qualified based on the video image data and the temperature data; The step of determining whether the asphalt is qualified based on the video image data comprises: identifying the aggregate and the white material in the asphalt based on the video image data, and determining the ratio of the aggregate and the white material in the asphalt; if the ratio of the aggregate and the white material in the asphalt is greater than a preset ratio threshold, determining that the asphalt is unqualified; if the ratio of the aggregate and the white material in the asphalt is less than or equal to the ratio threshold, determining that the asphalt is qualified; The steps of identifying the flower white material in the asphalt based on the video image data and determining the proportion of the flower white material in the asphalt include: binarizing the video image data to obtain a binary image; dilating the binary image; identifying the edges of the binary image after dilation, and determining the various regions of the binary image after dilation based on the edges; removing regions with an area greater than a first threshold from the binary image after dilation, and then removing regions with an area less than a second threshold to obtain a target image; wherein the target image is characterized as the region where the asphalt exists; determining multiple target regions in the target image; wherein the target region is characterized as the region where the flower white material exists; taking the ratio of the sum of the areas of the multiple target regions to the area of ​​the target image as the proportion of the flower white material in the asphalt; The steps of identifying the agglomerates in the asphalt based on the video image data and determining the proportion of the agglomerates in the asphalt include: performing Canny operator processing on the video image data to obtain a first image; performing dilation processing on the first image; performing inversion processing on the first image after dilation processing; removing regions with an area greater than a third threshold value from the first image after inversion processing, and then removing regions with an area less than a fourth threshold value to obtain a target image; wherein the target image is characterized as the area where the asphalt exists; determining multiple target areas in the target image; wherein the target area is characterized as the area where agglomerates exist; and taking the ratio of the sum of the areas of the multiple target areas to the area of ​​the target image as the proportion of the agglomerates in the asphalt.

2. The method according to claim 1, characterized in that The step of collecting video image data of the asphalt discharge port by means of a camera device comprises: Start the camera device; In response to the operation of pressing the material switch, the electromagnetic relay is closed, and the video image data of the asphalt discharge port is collected by the camera device; In response to the operation of releasing the material switch, the electromagnetic relay is disconnected, and the collection of video image data of the asphalt discharge port by the camera device is stopped.

3. The method according to claim 1, characterized in that The camera device is equipped with a polarizing filter and an air-cooling cover; the polarizing filter is used to eliminate the influence of asphalt oil reflection on the video image data; the air-cooling cover is used to cool down and remove dust; The infrared temperature sensor is provided with an air cooling system, and the air cooling system is used to remove dust and cool the infrared temperature sensor.

4. The method according to claim 1, characterized in that: The step of determining whether the asphalt is qualified based on the temperature data comprises: If the temperature data is greater than a preset first temperature threshold, or the temperature data is less than a preset second temperature threshold, it is determined that the asphalt is unqualified; If the temperature data is less than or equal to the first temperature threshold, and the temperature data is greater than or equal to the second temperature threshold, it is determined that the asphalt is qualified.

5. The method according to any one of claims 1 to 4, characterized in that: After the step of determining whether the asphalt is qualified based on the video image data and the temperature data, the method further includes: If the asphalt is unqualified, an alarm operation is performed.

6. The method according to any one of claims 1 to 4, characterized in that: After the step of determining whether the asphalt is qualified based on the video image data and the temperature data, the method further includes: The recognition result stored in the video image data, the temperature data and the asphalt; wherein the recognition result indicates whether the asphalt is qualified.

7. An asphalt identification system, characterized in that: Used to execute the asphalt identification method described in any one of claims 1-6.

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