Road surface monitoring system and method based on infrared rays

Abstract

The invention discloses a road surface monitoring system and method based on infrared rays, and relates to the technical field of infrared monitoring, and the system firstly divides a monitored road surface into regions, then monitors each region, analyzes the restoration data of each target region, and then repairs the road surface. According to the method, the monitoring accuracy and reliability can be effectively improved, a proper auxiliary monitoring means is selected for the complex road surface, the limitation of single infrared detection is reduced, and the monitoring accuracy and reliability are improved. The method is advantaged in that high precision of complex pavement results is guaranteed, pavement maintenance material type selection is analyzed, similarity of pavement material characteristics is guaranteed, difficulty of subsequent pavement monitoring by an infrared technology is reduced, pavement monitoring cost is reduced, corresponding feedback and operation are carried out according to pavement repair conditions, and pavement damage is reduced.

Description

Technical Field

[0002] The present invention relates to the field of infrared monitoring technology, and in particular to an infrared-based road surface monitoring system and method. Background Art

[0003] Infrared technology has the advantages of being less affected by lighting conditions, good concealment and high accuracy. It can monitor road conditions in real time and detect road damage and other information, providing important data support and decision-making basis for traffic management, road maintenance and safety assurance.

[0004] Existing technologies, such as the application with publication number CN111739308A, disclose a road abnormality mobile IoT monitoring system and method for vehicle-road collaboration. The system includes road sensors based on narrowband IoT, drones equipped with multispectral cameras, and servers of cloud information systems; road sensors realize information exchange between objects based on narrowband cellular networks; drones are equipped with infrared cameras and visible light cameras to inspect road abnormalities; the servers of cloud information systems are used to receive road sensors and drone inspection information, and are also used for the dispatch of drones and maintenance personnel. This system can sense road and environmental abnormalities; conduct drone abnormality monitoring and scheduled inspections at the same time; transmit data in real time; complete image abnormality recognition and analysis; realize intelligent signal control and road abnormality alarm and release, and provide real-time feedback on the latest and most reliable information of road vehicles, thus building an intelligent transportation system in smart cities.

[0005] The above scheme has at least the following shortcomings: 1. Different road materials have different infrared reflection and absorption characteristics. Therefore, dividing the road surface into sections according to material type or characteristics and conducting separate inspections on different areas can improve the accuracy and reliability of the inspection. However, the above scheme lacks the method of dividing the road surface into sections and then conducting separate inspections. This cannot effectively improve the accuracy and reliability of the inspection, nor can it provide an effective reference for subsequent data processing and road maintenance, thereby reducing the effectiveness of road maintenance.

[0006] 2. In view of the differences in road materials, in roads with more complex materials, infrared detection is combined with other detection methods, such as laser ranging, ultrasonic detection and visual detection, etc., and the advantages of different detection methods are used to complement each other. Comprehensive judgment and analysis of road material differences can be made, which can reduce the limitations of single infrared detection. However, the above scheme only uses infrared cameras and visible light cameras to inspect abnormal road conditions, and does not use the complexity of road material characteristics to select appropriate auxiliary monitoring methods. It is impossible to complement the detection advantages of different detection methods, and it is impossible to reduce the limitations of single infrared detection, which reduces the high accuracy of infrared technology in detecting complex road surfaces.

[0007] 3. When performing road maintenance, selecting material types with similar material properties can reduce the difficulty of subsequent infrared technology monitoring of the road surface. However, the above scheme lacks analysis of the selection of road maintenance material types, cannot guarantee the similarity of road material properties, and cannot reduce the difficulty of subsequent infrared technology monitoring of the road surface, thereby increasing the cost of road monitoring. Summary of the invention

[0008] In view of the above-mentioned technical deficiencies, the object of the present invention is to provide an infrared-based road surface monitoring system and method.

[0009] To solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect, the present invention provides an infrared-based road surface monitoring system, including: a road surface monitoring unit, which is used to divide the monitored road surface into areas, obtain each partition, obtain basic characteristic data of each partition, set monitoring parameters of each partition, and obtain road surface monitoring data of each partition.

[0010] The road surface repair unit is used to analyze whether each zone needs to be repaired based on the road surface monitoring data of each zone, record each zone that needs to be repaired as a target zone, analyze the repair data of each target zone, and then repair the road surface.

[0011] The pavement feedback unit is used to obtain the historical repair records of the monitored pavement, analyze the damage of the monitored pavement, and provide corresponding feedback and prompts.

[0012] In a second aspect, the present invention provides an infrared-based road surface monitoring method, comprising: step one, road surface monitoring: dividing the monitored road surface into areas to obtain partitions, obtaining basic characteristic data of each partition, setting monitoring parameters of each partition, and obtaining road surface monitoring data of each partition.

[0013] Step 2: Road surface repair: Based on the road surface monitoring data of each zone, analyze whether each zone needs to be repaired, record each zone that needs to be repaired as a target zone, analyze the repair data of each target zone, and then repair the road surface.

[0014] Step 3: Road surface feedback: Obtain the historical repair records of the monitored road surface, analyze the damage of the monitored road surface, and provide corresponding feedback and prompts.

[0015] The beneficial effects of the present invention are as follows: the present invention provides an infrared-based road surface monitoring system and method, which first divides the monitored road surface into regions according to the characteristic data of each point in the road surface, then sets the monitoring parameters of each partition, monitors each partition, and then analyzes whether each partition needs to be repaired. When necessary, the repair data of each target partition is analyzed, and then the road surface is repaired. Finally, the repair status of the monitored road surface within a specified period is used to analyze the damage status of the monitored road surface, and corresponding feedback and prompts are given. The present invention can effectively improve the accuracy and reliability of monitoring, select suitable auxiliary monitoring means for complex road surfaces, complement the detection advantages of different detection methods, reduce the limitations of single infrared detection, ensure the high accuracy of complex road surface results, and analyze the selection of road surface maintenance material types to ensure the similarity of road surface material properties, reduce the difficulty of subsequent infrared technology monitoring of the road surface, reduce the cost of road surface monitoring, and give corresponding feedback and operations on the road surface repair status to reduce road surface damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a schematic diagram of the system structure connection of the present invention.

[0018] Figure 2 The present invention is a schematic flow chart of the steps for implementing the method. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0020] See also Figure 1 As shown, the infrared-based road surface monitoring system includes: a road surface monitoring unit, a road surface repair unit, a road surface feedback unit and a database.

[0021] The road surface monitoring unit is used to divide the monitored road surface into regions, obtain each zone, obtain basic characteristic data of each zone, set monitoring parameters of each zone, and obtain road surface monitoring data of each zone.

[0022] In a specific embodiment, the monitored road surface is divided into regions, and the specific process is as follows: a number of points are set on the monitored road surface, and characteristic data corresponding to each point is obtained from the construction record, the characteristic data corresponding to each point is compared with the characteristic data interval corresponding to the material type, and the material type corresponding to each point is obtained, and then the points corresponding to each material type are clustered to obtain each partition, thereby completing the regional division of the monitored road surface, and at the same time, the mode of the characteristic data of each point in each partition is used as the basic characteristic data of each partition.

[0023] Among them, the characteristic data include the reflectivity and absorption rate of infrared light. After the monitored road surface is constructed or repaired, the staff needs to monitor the characteristic data of each point in the monitored road surface and record the characteristic data of each point in the monitored road surface in the construction record.

[0024] Material types include asphalt concrete, cement concrete and gravel pavement, etc.

[0025] Construction records are stored in the pavement monitoring system.

[0026] In another specific embodiment, the monitoring parameters of each partition are set as follows: using the basic characteristic data corresponding to each partition, the complexity corresponding to the monitored road surface is analyzed. When the complexity of the monitored road surface is greater than the preset complexity threshold, it indicates that the monitored road surface is relatively complex, otherwise it indicates that the monitored road surface is not complex.

[0027] Among them, the complexity threshold setting: the complexity threshold is a reference value for judging whether the pavement material properties are complex, which is jointly discussed and formulated by multiple experts. When the complexity is greater than the complexity threshold, it indicates that the pavement material properties are complex, otherwise it indicates that the pavement material properties are not complex. For example: the complexity threshold is 4, and the corresponding complexity of the monitored pavement is 6, 6>4, indicating that the monitored pavement material properties are complex.

[0028] In the above, the analysis process of analyzing the complexity of the monitored road surface is as follows: set the basic characteristic data difference threshold, denoted as ; Subtract the basic characteristic data between each partition to obtain the difference of each basic characteristic data, recorded as , y represents the number of the basic characteristic data difference, and y is a positive integer.

[0029] It should be noted that the basic characteristic data difference threshold is set as follows: the basic special effect data difference between each partition in each road surface with uncomplicated road surface is obtained from historical monitoring records, and the maximum basic special effect data difference is selected as the basic characteristic data difference threshold.

[0030] Using the analytical formula: , and obtain the complexity of the monitored road surface , where z represents the number of basic characteristic data differences, x represents the number corresponding to each partition, x is a positive integer, and q represents the number of partitions. represents the area corresponding to the xth partition, S represents the area of ​​the monitored road surface, Indicates the preset partition quantity threshold.

[0031] It should be noted that the camera can be used to collect pictures of the monitored road surface, and the area of ​​each partition and the area of ​​the monitored road surface can be obtained through image recognition technology; the setting process of the partition quantity threshold is the same as the basic characteristic data difference threshold setting, which will not be repeated here.

[0032] When the monitored road surface is more complex, obtain historical monitoring records, predict the monitoring effect values ​​of each auxiliary monitoring method in the monitored road surface, select the auxiliary monitoring method corresponding to the maximum monitoring effect value as the target auxiliary monitoring method, and confirm the control data of the infrared equipment and the target auxiliary monitoring method when monitoring each partition based on the historical monitoring records, and use the control data of the infrared equipment and the target auxiliary monitoring method when monitoring each partition as the monitoring parameters of each partition.

[0033] Historical monitoring records are stored in the pavement monitoring system.

[0034] In the above, the prediction process of the monitoring effect value of each auxiliary monitoring method in the monitored road surface is as follows: the complexity, auxiliary monitoring method, road surface monitoring data and actual road surface data corresponding to each road surface are obtained from the historical monitoring records, and the auxiliary monitoring method, road surface monitoring data and actual road surface data corresponding to each historical monitoring of each complexity are statistically calculated.

[0035] Among them, the road surface monitoring data includes the size and location of road surface damage monitored, and the actual road surface data includes the actual size and location of road surface damage.

[0036] According to the complexity of the monitored road surface, the auxiliary monitoring methods, road surface monitoring data and actual road surface data of each historical monitoring of the corresponding complexity of the monitored road surface are obtained as the auxiliary monitoring methods, road surface monitoring data and actual road surface data of each historical monitoring. The auxiliary monitoring times of each auxiliary monitoring method, the road surface monitoring data and actual road surface data of each monitoring of each auxiliary monitoring method are counted and recorded as , and , f represents the number of each auxiliary monitoring method, w represents the number of each monitoring, and both f and w are positive integers.

[0037] Using the prediction formula: , get the monitoring effect value of the fth auxiliary monitoring method in the monitored road surface , where v represents the total number of monitoring times, N represents the sum of the auxiliary monitoring times of each auxiliary monitoring method, and e represents a natural constant.

[0038] Preferably, the control data of the infrared device and the target auxiliary monitoring method when monitoring each partition is confirmed. The specific process is: obtain the control data and basic characteristic data of each historical partition when the infrared device monitors each historical road surface with the same complexity as the monitored road surface from the historical monitoring records, and based on the basic characteristic data of each partition in the monitored road surface, count the control data of each historical partition monitored by the infrared device with the same basic characteristic data as the partition in the monitored road surface, and select the majority as the control data of the infrared device when monitoring each partition.

[0039] The target-assisted monitoring method analyzes the control data when monitoring each partition in the same manner as the infrared device analyzes the control data when monitoring each partition.

[0040] Among them, auxiliary monitoring methods include laser ranging, ultrasonic detection and visual detection, and the control data are the parameters of the adjustment equipment. For example: the monitoring method is infrared equipment monitoring, and the control data include infrared wavelength, power and resolution, etc.; the monitoring method is visual detection, and the control data include focal length and resolution, etc.

[0041] When the monitored road surface is not complicated, the historical monitoring records are used to confirm the control data of the infrared equipment when monitoring each partition, and use it as the monitoring parameters of each partition.

[0042] It should be noted that when the monitored road surface is not complicated, the analysis process of the control data of the infrared device when monitoring each partition is the same as the analysis process of the control data of the infrared device when monitoring each partition when the monitored road surface is relatively complicated.

[0043] The road surface repair unit is used to analyze whether each zone needs to be repaired based on the road surface monitoring data of each zone, record each zone that needs to be repaired as a target zone, analyze the repair data of each target zone, and then repair the road surface.

[0044] In the above, whether each partition needs to be repaired is analyzed. The specific process is as follows: the road surface monitoring data threshold corresponding to each road surface area is obtained from the database, and the road surface monitoring data threshold corresponding to each partition is obtained according to the area of ​​each partition. When the road surface monitoring data of a partition is greater than its road surface monitoring data threshold, it indicates that the partition needs to be repaired, otherwise it indicates that it does not need to be repaired, so as to analyze whether each partition needs to be repaired.

[0045] Among them, the pavement monitoring data threshold corresponding to each pavement area is a reference value for judging whether the pavement damage in each pavement area is serious. The area and pavement monitoring data corresponding to each pavement in the historical repair are obtained from the historical repair records, and the pavement monitoring data corresponding to each pavement area are counted. The minimum pavement monitoring data in the pavement area is selected as the pavement monitoring data threshold corresponding to each pavement area.

[0046] In a specific embodiment, the specific process of analyzing the repair data of each target partition is as follows: obtaining the basic characteristic data corresponding to each target partition and the basic characteristic data of each adjacent partition corresponding to each target partition, and at the same time obtaining the characteristic data, suitable infrared spectrum data and vulnerable characteristic values ​​corresponding to each repair material type from the database, and obtaining the infrared spectrum data interval corresponding to the operation of the infrared equipment in the monitored road surface.

[0047] In the above, the infrared spectrum data includes infrared wavelength and resolution, etc.

[0048] It should be noted that the vulnerable characteristic value corresponding to each repair material type is: the starting time point, first damage time point and material replacement time point of each repair material type are obtained from the database, the time from the starting time point to the first damage time point is taken as the damage time, and the time from the starting time point to the material replacement time point is taken as the life cycle, so as to count the damage time and life cycle of each repair material type during each repair use, and then the average damage time and average life cycle of each repair material type are obtained by mean calculation, which are recorded as and , k represents the number of each type of repair material, k is a positive integer; then use the analytical formula: , get the vulnerable characteristic value of the kth repair material type , where T1 and T2 represent the maximum value of the average damage time and the maximum value of the average life cycle of each repair material type, respectively.

[0049] The material matching coefficient calculation formula is used to calculate the adaptation coefficient between each target partition and each type of repair material. The type of repair material with the largest adaptation coefficient in each target partition is selected as the type of repair material for each target partition. At the same time, the size to be repaired in each target partition and the unit consumables of each type of repair material during repair are obtained. The demand for the type of repair material in each target partition is obtained, and the type and demand for the repair material in each target partition are used as repair data.

[0050] Among them, the size to be repaired is obtained from the pavement monitoring data of each target partition, the unit consumables of each repair material type during repair means the amount of consumables required for the unit repair size when each repair material is used for repair, the consumables and sizes corresponding to each repair material type during each historical repair are obtained from the historical repair records, and then the consumables and sizes are divided to obtain the unit consumables corresponding to each repair material type during each historical repair, and then the average is calculated to obtain the unit consumables of each repair material type during repair.

[0051] Historical repair records are stored in the pavement monitoring system.

[0052] The required quantity of the repair material type in each target partition is obtained by multiplying the size to be repaired in each target partition and the unit consumable quantity of the repair material type in the target partition.

[0053] In a specific embodiment, the calculation formula of the material matching coefficient is: , where represents the adaptation coefficient between the cth target partition and the kth type of restoration material, represents the basic characteristic data of the cth target partition, represents the characteristic data of the kth type of restorative material, Indicates the basic characteristic data of the cth target partition corresponding to the dth adjacent partition, represents the basic characteristic data difference threshold, c represents the number of each target partition, k represents the number of each repair material type, d represents the number of each adjacent partition, c, k and d are all positive integers, n represents the number of adjacent partitions, represents the difference value of infrared spectrum data of the kth type of restoration material, is the preset infrared spectrum data difference value threshold, represents the vulnerable characteristic value of the k-th repair material type, YS is the preset vulnerable characteristic value threshold, , They respectively represent the weight coefficient of the characteristic data within the area and the weight coefficient of the characteristic data outside the area.

[0054] It should be noted that when the suitable infrared spectrum data of a certain type of repair material is within the infrared spectrum data interval corresponding to the operation of the infrared device on the monitored road surface, the infrared spectrum data difference value of the repair material type is 0; if the suitable infrared spectrum data of a certain type of repair material is greater than the upper limit value of the infrared spectrum data interval corresponding to the operation of the infrared device on the monitored road surface, then the infrared spectrum data difference value of the repair material type is the difference between the suitable infrared spectrum data of the repair material type and the upper limit value of the infrared spectrum data interval corresponding to the operation of the infrared device on the monitored road surface; if the suitable infrared spectrum data of a certain type of repair material is less than the lower limit value of the infrared spectrum data interval corresponding to the operation of the infrared device on the monitored road surface, then the infrared spectrum data difference value of the repair material type is the difference between the lower limit value of the infrared spectrum data interval corresponding to the operation of the infrared device on the monitored road surface and the suitable infrared spectrum data of the repair material type, thereby obtaining the infrared spectrum data difference values ​​of each type of repair material.

[0055] The setting process of YS is the same as that of the complexity threshold, which will not be repeated here.

[0056] In the above, , Setting process: Subtract the basic characteristic data of each target partition from the basic characteristic data of each adjacent partition, then divide it by the basic characteristic data of each target partition, and then calculate the average value to obtain the basic characteristic data difference rate between the target partition and the adjacent partition, which is recorded as the marked basic characteristic data difference rate, marked as a1, and calculate the basic characteristic data difference rate between the partition and the adjacent partition of the monitored road surface in the same way, select the maximum basic characteristic data difference rate as the reference basic characteristic data difference rate, marked as a2, if a1<a2, then , , if a1≥a2, then =0.9, =0.1.

[0057] When selecting the type of repair material, the embodiment of the present invention compares the basic characteristic data in the target partition and its adjacent partitions, and sets the weight coefficient of the characteristic data outside the zone. When the basic characteristic data in the target partition and its adjacent partitions are not much different, the type of repair material whose characteristic data is less different from the basic characteristic data of the adjacent partitions is selected. This can reduce the control range of the monitoring equipment during subsequent road surface monitoring. At the same time, small-scale control can reduce damage to the monitoring equipment and increase the use time of the equipment.

[0058] In addition, selecting the type of restoration material whose characteristic data differs less from the basic characteristic data of the target partition can ensure the uniformity of the characteristics in the target partition, reduce the differences within the partition, and improve the accuracy and reliability of subsequent monitoring results.

[0059] The pavement feedback unit is used to obtain the historical repair records of the monitored pavement, analyze the damage of the monitored pavement, and provide corresponding feedback and prompts.

[0060] The historical repair records of the monitored road surface are stored in the road surface monitoring system.

[0061] In a specific embodiment, the damage condition of the monitored road surface is analyzed, and the specific process is as follows: the number of repairs of each target partition in the monitored road surface within a specified period, the position and size of each repair area are obtained from the historical repair records of the monitored road surface, and the spacing between each repair area in each target partition is obtained according to the position of each repair area in each target partition, and then the average spacing of the repair areas in each target partition is obtained by mean calculation, and the total size of the repair area and the size of the repeated repair area in each target partition are obtained according to the position and size of each repair area in each target partition, and then the damage assessment model is used to output the damage level of the monitored road surface.

[0062] It should be noted that the total size of the repair area is the sum of the sizes of each repair area, and the size of the repeated repair area is the total size of the overlapping area between the repair areas. When there are at least two repair areas with overlapping areas, the overlapping area of ​​the two repair areas is the overlapping area.

[0063] The expression of the damage assessment model is: , where represents the damage level of the monitored road surface, m represents the number of target partitions, represents the number of partitions, X represents the total number of repairs of each target partition, , , , They represent the number of repairs of the cth target partition, the total size of the repaired area, the size of the repeated repaired area, and the average spacing of the repaired areas. Indicates the size of the cth target partition, is the maximum length of the cth target partition, , They are the weight coefficient of the total size of the repair area and the weight coefficient of the size of the repeated repair area. , They are the lower limit and upper limit of damage assessment respectively.

[0064] In the above, the size and maximum length of each target partition can be obtained by performing image recognition on the image of the monitored road surface.

[0065] It should be noted that , These are two reference values ​​for judging whether the road surface is seriously damaged. They are jointly discussed and formulated by multiple professionals. When the calculated value is less than the lower limit of the damage assessment, it indicates that the road surface is not seriously damaged. When the calculated value is greater than or equal to the lower limit of the damage assessment and less than or equal to the upper limit of the damage assessment, it indicates that the road surface is seriously damaged. When the calculated value is greater than the upper limit of the damage assessment, it indicates that the road surface is very seriously damaged. For example: , 5 and 15 respectively. The calculated value is 6, 6>5 but 6<15, indicating that the road surface is seriously damaged.

[0066] Preferably, the corresponding feedback and prompts are specifically performed as follows: when the damage level of the monitored road surface is level 1, a prompt indicating that the damage to the monitored road surface is not serious is displayed on the terminal display.

[0067] When the damage level of the monitored road surface is level 2, a prompt indicating that the monitored road surface is seriously damaged will be displayed on the terminal display, and at the same time, a prompt for vehicles to drive in a standardized manner will be given on the monitored road surface.

[0068] When the damage level of the monitored road surface is level 2, a prompt indicating that the monitored road surface is severely damaged will be displayed on the terminal display. At the same time, vehicles will be prompted to drive in a standardized manner on the monitored road surface, and supervision of illegal driving on the monitored road surface will be strengthened.

[0069] The database is used to store the characteristic data, suitable infrared spectrum data and vulnerable characteristic values ​​corresponding to each type of repair material, store the pavement monitoring data thresholds corresponding to each pavement area, and also store the start time point, first damage time point and material replacement time point of each repair use of each type of repair material.

[0070] See also Figure 2 As shown, the infrared-based road surface monitoring method includes: Step 1, road surface monitoring: dividing the monitored road surface into regions to obtain each partition, obtaining basic characteristic data of each partition, setting monitoring parameters of each partition, and obtaining road surface monitoring data of each partition.

[0071] Step 2: Road surface repair: Based on the road surface monitoring data of each zone, analyze whether each zone needs to be repaired, record each zone that needs to be repaired as a target zone, analyze the repair data of each target zone, and then repair the road surface.

[0072] Step 3: Road surface feedback: Obtain the historical repair records of the monitored road surface, analyze the damage of the monitored road surface, and provide corresponding feedback and prompts.

[0073] The embodiment of the present invention first divides the monitored road surface into regions according to the characteristic data of each point in the road surface, then sets the monitoring parameters of each partition, monitors each partition, and then analyzes whether each partition needs to be repaired. When necessary, the repair data of each target partition is analyzed, and then the road surface is repaired. Finally, the repair status of the monitored road surface within a specified period is used to analyze the damage status of the monitored road surface, and corresponding feedback and prompts are given. The present invention can effectively improve the accuracy and reliability of monitoring, select suitable auxiliary monitoring means for complex road surfaces, complement the detection advantages of different detection methods, reduce the limitations of single infrared detection, ensure the high accuracy of complex road surface results, analyze the selection of road maintenance material types, ensure the similarity of road surface material properties, reduce the difficulty of subsequent infrared technology monitoring of the road surface, reduce the cost of road surface monitoring, and give corresponding feedback and operations for the repair status of the road surface to reduce road surface damage.

[0074] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they shall all fall within the protection scope of the present invention.

Claims

1. The infrared-based road surface monitoring system is characterized by: include: The road surface monitoring unit is used to divide the monitored road surface into regions, obtain each zone, obtain basic characteristic data of each zone, set monitoring parameters of each zone, and obtain road surface monitoring data of each zone; A road surface repair unit is used to analyze whether each zone needs to be repaired according to the road surface monitoring data of each zone, record each zone that needs to be repaired as a target zone, analyze the repair data of each target zone, and then repair the road surface; The pavement feedback unit is used to obtain the historical repair records of the monitored pavement, analyze the damage of the monitored pavement, and provide corresponding feedback and prompts.

2. The infrared-based road surface monitoring system according to claim 1, characterized in that: The monitored road surface is divided into regions, and the specific process is as follows: Several points are set on the monitored road surface, and the characteristic data corresponding to each point is obtained from the construction record. The characteristic data corresponding to each point is compared with the characteristic data interval corresponding to the material type to obtain the material type corresponding to each point. Then, the points corresponding to each material type are clustered to obtain each partition, thereby completing the regional division of the monitored road surface. At the same time, the mode of the characteristic data of each point in each partition is used as the basic characteristic data of each partition.

3. The infrared-based road surface monitoring system according to claim 1, characterized in that: The specific process of setting the monitoring parameters of each partition is as follows: The basic characteristic data corresponding to each partition is used to analyze the complexity of the monitored road surface. When the complexity of the monitored road surface is greater than the preset complexity threshold, it indicates that the monitored road surface is relatively complex, otherwise it indicates that the monitored road surface is not complex. When the monitored road surface is relatively complex, obtain historical monitoring records, predict the monitoring effect values ​​of each auxiliary monitoring method in the monitored road surface, select the auxiliary monitoring method corresponding to the maximum monitoring effect value as the target auxiliary monitoring method, and confirm the control data of the infrared equipment and the target auxiliary monitoring method when monitoring each partition based on the historical monitoring records, and use the control data of the infrared equipment and the target auxiliary monitoring method when monitoring each partition as the monitoring parameters of each partition; When the monitored road surface is not complicated, the historical monitoring records are used to confirm the control data of the infrared equipment when monitoring each partition, and use it as the monitoring parameters of each partition.

4. The infrared-based road surface monitoring system according to claim 3 is characterized in that: The analysis process of analyzing the complexity of the monitored road surface is as follows: Set the basic characteristic data difference threshold, denoted as ; Subtract the basic characteristic data between each partition to obtain the difference of each basic characteristic data, recorded as , y represents the number of the basic characteristic data difference, and y is a positive integer; Using the analytical formula: , and obtain the complexity of the monitored road surface , where z represents the number of basic characteristic data differences, x represents the number corresponding to each partition, x is a positive integer, and q represents the number of partitions. represents the area corresponding to the xth partition, S represents the area of ​​the monitored road surface, Indicates the preset partition quantity threshold.

5. The infrared-based road surface monitoring system according to claim 3 is characterized in that: The prediction process of the monitoring effect value of each auxiliary monitoring mode in the monitored road surface is as follows: Obtain the complexity, auxiliary monitoring method, road surface monitoring data and actual road surface data corresponding to each road surface from historical monitoring records, and thereby count the auxiliary monitoring method, road surface monitoring data and actual road surface data corresponding to each complexity in each historical monitoring; According to the complexity of the monitored road surface, the auxiliary monitoring methods, road surface monitoring data and actual road surface data of each historical monitoring of the corresponding complexity of the monitored road surface are obtained as the auxiliary monitoring methods, road surface monitoring data and actual road surface data of each historical monitoring. The auxiliary monitoring times of each auxiliary monitoring method, the road surface monitoring data and actual road surface data of each monitoring of each auxiliary monitoring method are counted and recorded as , and , f represents the number of each auxiliary monitoring method, w represents the number of each monitoring, and both f and w are positive integers; Using the prediction formula: , get the monitoring effect value of the fth auxiliary monitoring method in the monitored road surface , where v represents the total number of monitoring times, N represents the sum of the auxiliary monitoring times of each auxiliary monitoring method, and e represents a natural constant.

6. The infrared-based road surface monitoring system according to claim 1, characterized in that: The specific process of analyzing the repair data of each target partition is as follows: Obtain the basic characteristic data corresponding to each target partition and the basic characteristic data of each adjacent partition corresponding to each target partition, and at the same time obtain the characteristic data, suitable infrared spectrum data and vulnerable characteristic value corresponding to each type of repair material from the database, and obtain the infrared spectrum data interval corresponding to the operation of the infrared equipment in the monitored road surface; The material matching coefficient calculation formula is used to calculate the adaptation coefficient between each target partition and each type of repair material. The type of repair material with the largest adaptation coefficient in each target partition is selected as the type of repair material for each target partition. At the same time, the size to be repaired in each target partition and the unit consumables of each type of repair material during repair are obtained. The demand for the type of repair material in each target partition is obtained, and the type and demand for the repair material in each target partition are used as repair data.

7. The infrared-based road surface monitoring system according to claim 6, characterized in that: The calculation formula of the material matching coefficient is: , where represents the adaptation coefficient between the cth target partition and the kth type of restoration material, represents the basic characteristic data of the cth target partition, represents the characteristic data of the kth type of restorative material, Indicates the basic characteristic data of the cth target partition corresponding to the dth adjacent partition, represents the basic characteristic data difference threshold, c represents the number of each target partition, k represents the number of each repair material type, d represents the number of each adjacent partition, c, k and d are all positive integers, n represents the number of adjacent partitions, represents the difference value of infrared spectrum data of the kth type of restoration material, is the preset infrared spectrum data difference value threshold, represents the vulnerable characteristic value of the k-th repair material type, YS is the preset vulnerable characteristic value threshold, , They respectively represent the weight coefficient of the characteristic data within the area and the weight coefficient of the characteristic data outside the area.

8. The infrared-based road surface monitoring system according to claim 1, characterized in that: The specific process of analyzing the damage of the monitored road surface is as follows: The number of repairs of each target partition in the monitored road surface within a specified period, the position and size of each repair area are obtained from the historical repair records of the monitored road surface. According to the position of each repair area in each target partition, the spacing between each repair area in each target partition is obtained. Then, the average spacing of the repair areas in each target partition is obtained by mean calculation. According to the position and size of each repair area in each target partition, the total size of the repair area and the size of the repeated repair area in each target partition are obtained. Then, the damage assessment model is used to output the damage level of the monitored road surface. The expression of the damage assessment model is: , where represents the damage level of the monitored road surface, m represents the number of target partitions, represents the number of partitions, X represents the total number of repairs of each target partition, , , , They represent the number of repairs of the cth target partition, the total size of the repaired area, the size of the repeated repaired area, and the average spacing of the repaired areas. Indicates the size of the cth target partition, is the maximum length of the cth target partition, , They are the weight coefficient of the total size of the repair area and the weight coefficient of the size of the repeated repair area. , are the lower limit and upper limit of damage assessment respectively, c represents the number of each target partition, and c is a positive integer.

9. The infrared-based road surface monitoring system according to claim 8, characterized in that: The corresponding feedback and prompts are given as follows: When the damage level of the monitored road surface is level 1, the terminal display will show that the damage to the monitored road surface is not serious; When the damage level of the monitored road surface is level 2, a prompt indicating that the monitored road surface is seriously damaged will be displayed on the terminal display, and a prompt for vehicles to drive in accordance with regulations will be given on the monitored road surface; When the damage level of the monitored road surface is level 2, a prompt indicating that the monitored road surface is severely damaged will be displayed on the terminal display. At the same time, vehicles will be prompted to drive in a standardized manner on the monitored road surface, and supervision of illegal driving on the monitored road surface will be strengthened.

10. A road surface monitoring method for implementing an infrared-based road surface monitoring system according to any one of claims 1 to 9, characterized in that: include: Step 1, road surface monitoring: divide the monitored road surface into regions, obtain each zone, obtain basic characteristic data of each zone, set monitoring parameters of each zone, and obtain road surface monitoring data of each zone; Step 2: Road surface repair: Analyze whether each zone needs to be repaired based on the road surface monitoring data of each zone, record each zone that needs to be repaired as a target zone, analyze the repair data of each target zone, and then repair the road surface; Step 3: Road surface feedback: Obtain the historical repair records of the monitored road surface, analyze the damage of the monitored road surface, and provide corresponding feedback and prompts.

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