Highway bridge disease identification method and system

Abstract

The invention relates to the technical field of highway bridge disease recognition, and discloses a highway bridge disease recognition method and system, and the method comprises the steps: obtaining a highway bridge disease picture, carrying out the analysis, and determining the disease type and degree of the highway bridge disease; acquiring use data after the highway bridge is built, and acquiring historical environment data of the position where the highway bridge is located and influence building data within a specified range of the highway bridge; determining the self influence weight of the highway bridge according to the use data, determining the environment influence weight of the environment on the highway bridge according to the historical environment data, and determining the building influence weight of the highway bridge according to the building influence data; determining the comprehensive influence weight of the highway bridge based on the self influence weight, the environment influence weight and the building influence weight, and adjusting the disease degree according to the comprehensive influence weight to obtain the final disease degree of the highway bridge disease. According to the invention, the accuracy and timeliness of disease identification are improved, and the safe operation of the highway bridge is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of highway bridge defect recognition, and in particular to a highway bridge defect recognition method and system. Background Art

[0002] As a key component of the transportation network, highway bridges undertake important transportation tasks. The health of bridge structures is directly related to traffic safety and economic operation. However, due to the influence of various factors such as environmental erosion, material aging, design defects, overload use, and insufficient maintenance, various diseases may occur in bridges during operation. If these diseases are not discovered and treated in time, they may lead to bridge performance degradation or even accidents.

[0003] Traditional bridge defect identification methods mainly rely on manual inspections, which are completed by regular on-site inspections by bridge engineers or inspectors, based on experience and simple tools. This method is time-consuming, inefficient, highly subjective, and difficult to fully cover. Therefore, there is an urgent need for a highway bridge defect identification method and system to achieve efficient and accurate identification of bridge defects. Summary of the invention

[0004] The purpose of the present invention is to provide a highway bridge defect identification method and system to solve the problem that the traditional bridge defect identification method mainly relies on manual inspection, based on experience judgment and the assistance of simple tools. This method is time-consuming and labor-intensive, inefficient, highly subjective, and difficult to fully cover.

[0005] The present invention provides a method for identifying highway bridge defects, the method comprising:

[0006] Obtaining highway bridge disease pictures, analyzing the highway bridge disease pictures, and determining the disease type and disease degree of the highway bridge disease;

[0007] Obtain the data on the use of highway bridges after they are built, as well as the historical environmental data on the locations of highway bridges and the data on the buildings that affect the scope of the highway bridges;

[0008] Determine the self-impact weight of the highway bridge according to the commissioning data, determine the environmental impact weight of the environment on the highway bridge according to the historical environmental data, and determine the construction impact weight of the highway bridge according to the construction impact data;

[0009] The comprehensive impact weight of the highway bridge is determined based on the self-impact weight, the environmental impact weight and the building impact weight, and the degree of damage is adjusted according to the comprehensive impact weight to obtain the final degree of damage of the highway bridge.

[0010] In some embodiments of the present application, the highway bridge damage picture is analyzed to determine the damage type and damage degree of the highway bridge damage, including:

[0011] Obtaining original pictures of highway bridges, wherein the original pictures of highway bridges are pictures of highway bridges that have passed acceptance but have not been put into use;

[0012] De-noising the highway bridge disease image using Gaussian filtering to obtain a de-noised highway bridge disease image;

[0013] Compare the noise reduction highway bridge disease pictures with the original highway bridge pictures to determine the difference areas;

[0014] Segment the difference area to obtain the difference picture of highway bridge;

[0015] Compare the highway bridge difference pictures with the highway bridge disease standard pictures, and determine the type of highway bridge disease according to the comparison results;

[0016] and determining the degree of the corresponding defect type in the highway bridge difference image according to the defect type, and encoding the defect type and the degree of the defect;

[0017] Among them, the types of diseases include crack disease, peeling disease, weathering disease and rust disease;

[0018] Disease severity includes mild disease, moderate disease, severe disease, and serious disease;

[0019] The types of damage, such as cracks, spalling, weathering, exposed steel bars and corrosion, are coded as A, B, C and D respectively;

[0020] The mild disease, moderate disease, severe disease and serious disease in the disease degree are coded as L1, L2, L3, L4 respectively.

[0021] In some embodiments of the present application, determining the degree of damage of the corresponding damage type in the highway bridge difference image according to the damage type includes:

[0022] Set disease evaluation standards corresponding to disease types according to disease types;

[0023] Among them, the severity of crack damage is determined according to the crack width;

[0024] Determine the severity of the spalling disease based on the spalling area;

[0025] Determine the severity of weathering diseases based on weathering time and weathering area;

[0026] Determine the severity of the rust disease based on the rust time and rust area.

[0027] In some embodiments of the present application, determining the degree of crack damage according to the crack width includes:

[0028] Presetting a first crack width, a second crack width and a third crack width, wherein the first crack width, the second crack width and the third crack width increase in sequence;

[0029] Acquire the crack width in the highway bridge difference picture, and set the degree of the crack disease according to the relationship between the crack width and the first crack width, the second crack width and the third crack width;

[0030] If the crack width is smaller than the first crack width, the damage degree of the crack damage is set to be a mild damage A-L1;

[0031] If the crack width is greater than or equal to the first crack width, and the crack width is less than the second crack width, the damage degree of the crack disease is set to be moderate damage A-L2;

[0032] If the crack width is greater than or equal to the second crack width, and the crack width is less than the third crack width, the degree of the crack disease is set to be severe disease A-L3;

[0033] If the crack width is greater than or equal to the third crack width, the severity of the crack disease is set to severe disease A-L4;

[0034] The severity of the spalling disease is determined based on the spalling area, including:

[0035] Presetting a first peeling area, a second peeling area and a third peeling area, wherein the first peeling area, the second peeling area and the third peeling area increase in sequence;

[0036] Acquire the spalling area in the highway bridge difference picture, and set the degree of the spalling disease according to the relationship between the spalling area and the first spalling area, the second spalling area and the third spalling area;

[0037] If the spalling area is smaller than the first spalling area, the spalling disease severity is set to be a mild disease B-L1;

[0038] If the spalling area is greater than or equal to the first spalling area, and the spalling area is less than the second spalling area, the spalling disease severity is set to moderate disease B-L2;

[0039] If the spalling area is greater than or equal to the second spalling area, and the spalling area is less than the third spalling area, the spalling disease severity is set to severe disease B-L3;

[0040] If the spalling area is greater than or equal to the third spalling area, the spalling disease severity is set to severe disease B-L4;

[0041] The severity of weathering diseases is determined based on the weathering time and weathering area, including:

[0042] Presetting a first weathering ratio, a second weathering ratio and a third weathering ratio, wherein the first weathering ratio, the second weathering ratio and the third weathering ratio increase in sequence;

[0043] Obtaining the weathering time and weathering area corresponding to the weathering damage in the highway bridge difference image, determining the weathering ratio between the weathering area and the weathering time, and setting the damage degree of the weathering damage according to the relationship between the weathering ratio and the first weathering ratio, the second weathering ratio, and the third weathering ratio;

[0044] If the weathering ratio is less than the first weathering ratio, the disease degree of the weathering disease is set to be a mild disease C-L1;

[0045] If the weathering ratio is greater than or equal to the first weathering ratio, and the weathering ratio is less than the second weathering ratio, the disease degree of the weathering disease is set to be moderate disease C-L2;

[0046] If the weathering ratio is greater than or equal to the second weathering ratio, and the weathering ratio is less than the third weathering ratio, the disease degree of the weathering disease is set to severe disease C-L3;

[0047] If the weathering ratio is greater than or equal to the third weathering ratio, the disease degree of the weathering disease is set to severe disease C-L4;

[0048] The severity of the rust disease is determined based on the rust time and rust area, including:

[0049] Presetting a first corrosion ratio, a second corrosion ratio and a third corrosion ratio, wherein the first corrosion ratio, the second corrosion ratio and the third corrosion ratio increase in sequence;

[0050] Obtaining the corrosion time and corrosion area corresponding to the corrosion disease in the highway bridge difference picture, determining the corrosion ratio between the corrosion area and the corrosion time, and setting the degree of the corrosion disease according to the relationship between the corrosion ratio and the first corrosion ratio, the second corrosion ratio and the third corrosion ratio;

[0051] If the rust ratio is less than the first rust ratio, the rust disease severity is set to be a mild disease D-L1;

[0052] If the corrosion ratio is greater than or equal to the first corrosion ratio, and the corrosion ratio is less than the second corrosion ratio, the degree of the corrosion disease is set to be moderate disease D-L2;

[0053] If the corrosion ratio is greater than or equal to the second corrosion ratio, and the corrosion ratio is less than the third corrosion ratio, the degree of the corrosion disease is set to severe disease D-L3;

[0054] If the rust ratio is greater than or equal to the third rust ratio, the disease degree of the rust disease is set to severe disease D-L4.

[0055] In some embodiments of the present application, determining the self-influence weight of the highway bridge according to the commissioning data includes:

[0056] The said data of putting into use include the number of days of use and the daily load-bearing weight;

[0057] Determine the self-influencing factor of the highway bridge according to the daily load-bearing weight;

[0058] Determine the self-influence weight of the highway bridge according to the usage days and the self-influence factor;

[0059] The self-influence weight is calculated according to the following formula:

[0060]

[0061] Among them, Qz represents the self-influence weight, T represents the number of days of use, qi represents the self-influence factor, Lq represents the design load of the highway bridge, Wq represents the daily bearing capacity, q1 represents the first self-influence factor, q2 represents the second self-influence factor, and q3 represents the third self-influence factor.

[0062] In some embodiments of the present application, determining the environmental impact weight of the environment on the highway bridge according to the historical environmental data includes:

[0063] The historical environmental data include daily rainfall, daily humidity value and daily wind speed value;

[0064] Pre-set rainfall threshold, humidity threshold and wind speed threshold;

[0065] Comparing the daily rainfall with the rainfall threshold, and filtering rainfall data whose daily rainfall is higher than the rainfall threshold;

[0066] Comparing the daily humidity value with the humidity threshold, and filtering humidity data whose daily humidity value is higher than the humidity threshold;

[0067] Comparing the daily wind speed value with the wind speed threshold, and screening the wind speed data whose daily wind speed value is higher than the wind speed threshold;

[0068] Determine the environmental impact weight of the environment on the highway bridge according to the rainfall data, humidity data and wind speed data;

[0069] The environmental impact weight is calculated according to the following formula:

[0070]

[0071] Among them, Qh represents the environmental impact weight, a represents the rainfall impact factor, m represents the number of rainy days with daily rainfall higher than the rainfall threshold, Rx represents the daily rainfall on the xth day among m days, b represents the humidity impact factor, n represents the number of humidity days with daily humidity values ​​higher than the humidity threshold, Sy represents the daily humidity value on the yth day among n days, c represents the wind speed impact factor, k represents the number of wind speed days with daily wind speed values ​​higher than the wind speed threshold, and Wz represents the daily wind speed value on the zth day among k days.

[0072] In some embodiments of the present application, determining the building impact weight of the highway bridge according to the impact building data includes:

[0073] The affected building data include the distance between the affected building and the highway bridge and the construction area of ​​the affected building;

[0074] Determine a ratio between the construction area and the distance, and determine a construction impact weight of the highway bridge according to the ratio;

[0075] The building impact weight is calculated according to the following formula:

[0076]

[0077] Among them, Qj represents the building impact weight, d represents the impact building factor, p represents the number of impacted buildings, Sji represents the construction area of ​​the i-th impacted building, and Sdi represents the distance between the i-th impacted building and the highway bridge.

[0078] In some embodiments of the present application, the comprehensive impact weight is calculated according to the following formula:

[0079] Q=Qz+Qh+Qj.

[0080] In some embodiments of the present application, the damage degree is adjusted according to the comprehensive impact weight to obtain the final damage degree of the highway bridge damage, including:

[0081] Presetting a first comprehensive influence weight, a second comprehensive influence weight, and a third comprehensive influence weight, wherein the first comprehensive influence weight, the second comprehensive influence weight, and the third comprehensive influence weight increase in sequence;

[0082] The damage degree is adjusted according to the relationship between the comprehensive impact weight and the first comprehensive impact weight, the second comprehensive impact weight and the third comprehensive impact weight to obtain a final damage degree of the highway bridge damage;

[0083] If the comprehensive impact weight is less than the first comprehensive impact weight, the disease degree is not adjusted;

[0084] If the comprehensive impact weight is greater than or equal to the first comprehensive impact weight, and the comprehensive impact weight is less than the second comprehensive impact weight, the disease degree is increased by one level; if the disease degree is a serious disease, the disease degree is not adjusted;

[0085] If the comprehensive impact weight is greater than or equal to the second comprehensive impact weight, and the comprehensive impact weight is less than the third comprehensive impact weight, the disease degree is increased by two levels; if the disease degree is a serious disease, the disease degree is not adjusted;

[0086] If the comprehensive impact weight is greater than or equal to the third comprehensive impact weight, the disease level is increased by three levels; if the disease level is a serious disease, the disease level is not adjusted.

[0087] The present invention also discloses a highway bridge defect identification system, which is used to apply the above-mentioned highway bridge defect identification method, and the system comprises:

[0088] An acquisition module is used to acquire images of road bridge damage. The acquisition module is also used to acquire data on the road bridge being put into use after completion, and to acquire historical environmental data on the location of the road bridge and data on buildings that affect the road bridge within the specified range;

[0089] An image analysis module is used to analyze the highway bridge damage image to determine the damage type and damage degree of the highway bridge damage;

[0090] A weight determination module is used to determine the self-impact weight of the highway bridge according to the commissioning data, determine the environmental impact weight of the environment on the highway bridge according to the historical environmental data, and determine the building impact weight of the highway bridge according to the building impact data; the weight determination module is also used to determine the comprehensive impact weight of the highway bridge based on the self-impact weight, environmental impact weight and building impact weight;

[0091] The damage determination module is used to adjust the damage degree according to the comprehensive impact weight to obtain the final damage degree of the highway bridge damage.

[0092] Compared with the prior art, the beneficial effect of the present invention is that the present invention adjusts the degree of damage by comprehensively considering the self-influence weight, environmental influence weight and building influence weight of the highway bridge, and can more comprehensively and accurately evaluate the real damage condition of the bridge. It no longer relies solely on a single damage picture analysis, but combines various influencing factors after the bridge is put into use, such as vehicle traffic, environmental temperature and humidity changes, construction impact of surrounding buildings, etc., so that the damage assessment result is closer to the actual situation, greatly improving the efficiency of damage identification, and being able to find problems in time. In addition, the present invention obtains an accurate final degree of damage, which is helpful to formulate a more targeted, scientific and reasonable maintenance and repair plan. It can predict the development trend of the disease in advance, reasonably arrange maintenance resources, avoid aggravation of damage to the bridge structure due to untimely maintenance, and extend the service life of the bridge. The present invention uses advanced technical means to realize an automated and intelligent highway bridge disease identification method, which has become an urgent need to improve the accuracy and timeliness of disease identification and ensure the safe operation of highway bridges. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] 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 in the following description are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0094] Figure 1 It is a schematic flow chart of a highway bridge disease identification method of the present invention;

[0095] Figure 2 It is a functional block diagram of a highway bridge disease identification system of the present invention. DETAILED DESCRIPTION

[0096] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0097] like Figure 1 As shown, the present invention provides a method for identifying highway bridge defects, the method comprising:

[0098] S1, obtaining a highway bridge disease picture, analyzing the highway bridge disease picture, and determining the disease type and disease degree of the highway bridge disease.

[0099] S2, obtain the data of the highway bridge put into use after completion, and obtain the historical environmental data of the location of the highway bridge and the data of the buildings affecting the highway bridge within the prescribed scope.

[0100] S3, determining the self-impact weight of the highway bridge according to the commissioning data, determining the environmental impact weight of the environment on the highway bridge according to the historical environmental data, and determining the construction impact weight of the highway bridge according to the construction impact data.

[0101] S4, determining the comprehensive impact weight of the highway bridge based on the self-impact weight, the environmental impact weight and the building impact weight, adjusting the damage degree according to the comprehensive impact weight, and obtaining the final damage degree of the highway bridge damage.

[0102] In some embodiments of the present application, the highway bridge disease picture is analyzed to determine the disease type and degree of the highway bridge disease, including: obtaining an original picture of the highway bridge, wherein the original picture of the highway bridge is a picture of the highway bridge when it has passed acceptance but has not been put into use; using Gaussian filtering to denoise the highway bridge disease picture to obtain a denoised highway bridge disease picture; comparing the denoised highway bridge disease picture with the original picture of the highway bridge to determine the difference area; segmenting the difference area to obtain a highway bridge difference picture; comparing the highway bridge difference picture with the standard picture of the highway bridge disease, and determining the disease type of the highway bridge disease according to the comparison result; and determining the disease degree of the corresponding disease type in the highway bridge difference picture according to the disease type; wherein the disease types include crack disease, spalling disease, weathering disease and rust disease; and the disease degrees include mild disease, moderate disease, severe disease and serious disease.

[0103] In this embodiment, original pictures of highway bridges are collected. These original pictures are taken when the bridges are accepted and have not yet been put into use; in this way, these pictures can ensure that the corresponding highway bridges are not subjected to any external force and are in a standard state. Subsequently, in order to eliminate the noise interference that may exist in the image, Gaussian filtering technology is used to denoise these diseased pictures, thereby obtaining a set of noise-reduced highway bridge diseased pictures. Gaussian filtering technology is an effective linear smoothing filtering method, which is widely used for noise elimination in image processing and computer vision. This technology is based on the Gaussian function and achieves a smoothing effect by weighted averaging the neighborhood of image pixels. Next, these denoised images were compared in detail with the original bridge images to identify the difference areas between the two; these difference areas were then segmented independently to form highway bridge difference images; these highway bridge difference images were compared and analyzed with known highway bridge disease standard images, and through this comparison, the specific type of bridge disease can be accurately determined; after determining the disease type, the specific degree of the corresponding disease type in the highway bridge difference images was further analyzed; in this process, the corresponding disease types include crack disease, spalling disease, weathering disease and rust disease; and the degree of disease is subdivided into mild disease, moderate disease, severe disease and serious disease. Through such a detailed analysis, a comprehensive and accurate assessment of the health status of highway bridges can be made, providing a scientific basis for subsequent maintenance and repair work.

[0104] In some embodiments of the present application, the highway bridge disease images are analyzed to determine the disease type and disease degree of the highway bridge disease, which also includes: encoding the disease type and disease degree; cracks, spalling, weathering, exposed steel bars and rust in the disease types are coded as A, B, C, D respectively; mild diseases, moderate diseases, severe diseases and serious diseases in the disease degrees are coded as L1, L2, L3, L4 respectively.

[0105] Specifically, different types of damage are coded as follows: cracks, spalling, weathering, exposed steel bars and rust are marked as A, B, C, D, and E respectively. The degree of damage, mild damage, moderate damage, severe damage and serious damage are marked as L1, L2, L3, and L4 respectively. Such a coding system can better understand and deal with various damage problems, so as to take effective measures for repair and protection. It is also easy to record and consult.

[0106] In some embodiments of the present application, the degree of damage of the corresponding damage type in the highway bridge difference image is determined according to the damage type, including: setting a damage evaluation standard for the corresponding damage type according to the damage type; wherein, the degree of damage of crack damage is determined according to the crack width; the degree of damage of spalling damage is determined according to the spalling area; the degree of damage of weathering damage is determined according to the weathering time and weathering area; and the degree of damage of rust disease is determined according to the rust time and rust area.

[0107] In this embodiment, a set of scientific evaluation criteria is set for each type of disease, which can reflect the severity of the disease and can quantitatively evaluate the damage of the bridge. For crack diseases, the degree of impact on the bridge structure is determined according to the width of the crack. The larger the crack width, the more serious the damage to the bridge may be, and timely repair and reinforcement are required. Similarly, the severity of spalling diseases is also evaluated by its area. The larger the spalling area, the more serious the damage to the bridge surface, which may affect the service life of the bridge. For weathering diseases, the degree is evaluated according to the time and affected area of ​​weathering. The longer the weathering time, the larger the affected area, and the more serious the damage to the bridge caused by weathering diseases. The evaluation of rust diseases is similar, and the degree of damage to the bridge structure is determined according to the length of time and area range of rust. Rust not only destroys the beauty of the bridge, but more importantly, it weakens the bearing capacity of the bridge, posing a great safety hazard. In summary, this method can be used to accurately identify and evaluate various types of defects in highway bridges, so that scientific and reasonable maintenance and protection measures can be formulated to ensure the safe operation of bridges and extend their service life.

[0108] In some embodiments of the present application, determining the degree of crack disease according to the crack width includes: presetting a first crack width, a second crack width and a third crack width, wherein the first crack width, the second crack width and the third crack width increase in sequence; obtaining the crack width in the highway bridge difference picture, and setting the degree of the crack disease according to the relationship between the crack width and the first crack width, the second crack width and the third crack width; if the crack width is less than the first crack width, setting the degree of the crack disease to a mild disease A-L1; if the crack width is greater than or equal to the first crack width, and the crack width is less than the second crack width, setting the degree of the crack disease to a moderate disease A-L2; if the crack width is greater than or equal to the second crack width, and the crack width is less than the third crack width, setting the degree of the crack disease to a severe disease A-L3; if the crack width is greater than or equal to the third crack width, setting the degree of the crack disease to a serious disease A-L4.

[0109] Determining the degree of the spalling disease according to the spalling area includes: presetting a first spalling area, a second spalling area and a third spalling area, wherein the first spalling area, the second spalling area and the third spalling area increase in sequence; obtaining the spalling area in the highway bridge difference picture, and setting the degree of the spalling disease according to the relationship between the spalling area and the first spalling area, the second spalling area and the third spalling area; if the spalling area is smaller than the first spalling area, setting the degree of the spalling disease to a mild disease B-L1; if the spalling area is greater than or equal to the first spalling area, and the spalling area is smaller than the second spalling area, setting the degree of the spalling disease to a moderate disease B-L2; if the spalling area is greater than or equal to the second spalling area, and the spalling area is smaller than the third spalling area, setting the degree of the spalling disease to a severe disease B-L3; if the spalling area is greater than or equal to the third spalling area, setting the degree of the spalling disease to a serious disease B-L4.

[0110] Determining the degree of weathering damage according to weathering time and weathering area includes: presetting a first weathering ratio, a second weathering ratio and a third weathering ratio, wherein the first weathering ratio, the second weathering ratio and the third weathering ratio are increased in sequence; obtaining the weathering time and the weathering area corresponding to the weathering damage in the highway bridge difference picture, determining the weathering ratio between the weathering area and the weathering time, and setting the degree of weathering damage according to the relationship between the weathering ratio and the first weathering ratio, the second weathering ratio and the third weathering ratio; if the weathering ratio is less than the first weathering ratio, the second weathering ratio and the third weathering ratio are set; If the weathering ratio is greater than or equal to the first weathering ratio, and the weathering ratio is less than the second weathering ratio, the disease degree of the weathering disease is set to be a mild disease C-L1; if the weathering ratio is greater than or equal to the first weathering ratio, and the weathering ratio is less than the third weathering ratio, the disease degree of the weathering disease is set to be a moderate disease C-L2; if the weathering ratio is greater than or equal to the second weathering ratio, and the weathering ratio is less than the third weathering ratio, the disease degree of the weathering disease is set to be a severe disease C-L3; if the weathering ratio is greater than or equal to the third weathering ratio, the disease degree of the weathering disease is set to be a serious disease C-L4.

[0111] Determining the degree of corrosion damage according to the corrosion time and the corrosion area includes: presetting a first corrosion ratio, a second corrosion ratio and a third corrosion ratio, wherein the first corrosion ratio, the second corrosion ratio and the third corrosion ratio increase in sequence; obtaining the corrosion time and the corrosion area corresponding to the corrosion damage in the highway bridge difference picture, determining the corrosion ratio between the corrosion area and the corrosion time, and setting the degree of corrosion damage according to the relationship between the corrosion ratio and the first corrosion ratio, the second corrosion ratio and the third corrosion ratio; if the corrosion ratio is less than the first corrosion ratio, the second corrosion ratio and the third corrosion ratio are used as the reference; If the rust ratio is greater than or equal to the first rust ratio, and the rust ratio is less than the second rust ratio, the rust disease severity is set to be moderate disease D-L2; if the rust ratio is greater than or equal to the second rust ratio, and the rust ratio is less than the third rust ratio, the rust disease severity is set to be severe disease D-L3; if the rust ratio is greater than or equal to the third rust ratio, the rust disease severity is set to be serious disease D-L4.

[0112] In some embodiments of the present application, determining the self-influence weight of the highway bridge according to the commissioning data includes: the commissioning data includes the number of days of use and the daily bearing weight; determining the self-influence factor of the highway bridge according to the daily bearing weight; determining the self-influence weight of the highway bridge according to the number of days of use and the self-influence factor;

[0113] The self-influence weight is calculated according to the following formula:

[0114]

[0115] Among them, Qz represents the self-influence weight, T represents the number of days of use, qi represents the self-influence factor, Lq represents the design load of the highway bridge, Wq represents the daily bearing capacity, q1 represents the first self-influence factor, q2 represents the second self-influence factor, and q3 represents the third self-influence factor.

[0116] In this embodiment, in order to make a more accurate assessment of the use status of the highway bridge, this method introduces a comprehensive self-influence weight mechanism. This mechanism is mainly based on two key parameters: the number of days in use and the daily load-bearing weight. First, the number of days in use refers to the cumulative number of operating days since the bridge was put into use, which can reflect the utilization rate and operation time of the bridge. Secondly, the daily load-bearing weight refers to the sum of the traffic loads borne by the bridge within one day. This parameter is directly related to the structural safety and durability of the bridge. Within this framework, the self-influence factor of the highway bridge is determined by the daily load-bearing weight. Specifically, by statistically analyzing the daily load-bearing weight of the bridge every day, a quantitative indicator reflecting its bearing capacity can be obtained. Further, the self-influence weight of the highway bridge can be calculated by combining the number of days in use and the self-influence factor determined above.

[0117] In some embodiments of the present application, determining the environmental impact weight of the environment on the highway bridge according to the historical environmental data includes: the historical environmental data includes daily rainfall, daily humidity value and daily wind speed value; presetting a rainfall threshold, a humidity threshold and a wind speed threshold; comparing the daily rainfall with the rainfall threshold, and screening rainfall data with a daily rainfall higher than the rainfall threshold; comparing the daily humidity value with the humidity threshold, and screening humidity data with a daily humidity value higher than the humidity threshold; comparing the daily wind speed value with the wind speed threshold, and screening wind speed data with a daily wind speed value higher than the wind speed threshold; determining the environmental impact weight of the environment on the highway bridge according to the rainfall data, humidity data and wind speed data;

[0118] The environmental impact weight is calculated according to the following formula:

[0119]

[0120] Among them, Qh represents the environmental impact weight, a represents the rainfall impact factor, m represents the number of rainy days with daily rainfall higher than the rainfall threshold, Rx represents the daily rainfall on the xth day among m days, b represents the humidity impact factor, n represents the number of humidity days with daily humidity values ​​higher than the humidity threshold, Sy represents the daily humidity value on the yth day among n days, c represents the wind speed impact factor, k represents the number of wind speed days with daily wind speed values ​​higher than the wind speed threshold, and Wz represents the daily wind speed value on the zth day among k days.

[0121] In this embodiment, in order to deeply understand and quantify the extent of the impact of environmental factors on the long-term operation of highway bridges, this study adopted an analytical method based on historical environmental data. This method first requires the collection of a series of detailed historical environmental data, including but not limited to daily rainfall, relative humidity, and wind speed. These environmental parameters are essential for assessing the health of bridges and predicting their future maintenance needs. After collecting this data, specific thresholds are set to distinguish which weather conditions may have a significant impact on bridges. These thresholds are set based on past weather records and the response history of bridges. Specifically, rainfall thresholds are set to ensure that only those rainfall events that exceed normal levels are taken into account. Similarly, similar thresholds are set for relative humidity and wind speed to screen out those days that may have a significant impact on the structure and function of the bridge. Next, the collected data is carefully screened and analyzed. The rainfall, humidity, and wind speed values ​​of each day are compared with the corresponding thresholds to select data under extreme weather conditions. Specifically, the rainfall of each day is evaluated and those days with rainfall exceeding the pre-set thresholds are screened. Similar processing was performed for relative humidity and wind speed to ensure that only those data with humidity and wind speed values ​​exceeding the threshold were included in the analysis. Finally, the filtered rainfall data, humidity data, and wind speed data were used to calculate and determine the environmental impact weight of the environment on the highway bridge. This weight is a quantitative indicator that can reflect the relative importance of different environmental factors on the bridge. In this way, we can not only better understand how environmental factors affect the health of the bridge, but also provide valuable reference information for future bridge design and maintenance.

[0122] It is understandable that the dimensions of the rainfall impact factor a, humidity impact factor b, and wind speed impact factor c can be set according to the actual situation. If the unit of rainfall is "mm", the unit of rainfall impact factor a is "day / mm"; if the humidity value is expressed as relative humidity and is dimensionless, the unit of humidity impact factor b is "day"; if the unit of wind speed value is "m / s", the unit of wind speed impact factor c is "day·second / m". No matter how the units of rainfall impact factor a, humidity impact factor b, and wind speed impact factor c are set, the environmental impact weight must be dimensionless.

[0123] In some embodiments of the present application, determining the building influence weight of the highway bridge according to the influencing building data includes: the influencing building data includes the distance between the influencing building and the highway bridge and the construction area of ​​the influencing building; determining the ratio between the construction area and the distance, and determining the building influence weight of the highway bridge according to the ratio;

[0124] The building impact weight is calculated according to the following formula:

[0125]

[0126] Among them, Qj represents the building impact weight, d represents the impact building factor, p represents the number of impacted buildings, Sji represents the construction area of ​​the i-th impacted building, and Sdi represents the distance between the i-th impacted building and the highway bridge.

[0127] In this embodiment, the construction of surrounding buildings may cause ground vibration or partial collapse. The larger the construction scope and the closer the distance to the highway bridge, the greater the impact on the highway bridge. This application proposes a method for determining the building impact weight based on the building data. The method mainly considers two key factors: one is the distance between the building and the highway bridge, and the other is the construction area of ​​the building. First, a large amount of relevant building data is collected, including the distance information between various buildings and highway bridges and the construction area of ​​these buildings. These data can be obtained through field surveys, satellite remote sensing image analysis and other means. Then, these data are sorted and analyzed in detail for subsequent calculations and evaluations. Next, the ratio between the construction area and the distance is determined. This ratio reflects the relative relationship between the construction scale of the building and its distance from the highway bridge. By calculating this ratio, the degree of impact of different buildings on the highway bridge can be more intuitively understood. Finally, according to this ratio, the building impact weight of the highway bridge is determined. Specifically, if a building is close to the highway bridge and has a large construction area, its building impact weight will be higher. On the contrary, if a building is far away from a highway bridge or has a smaller construction area, its building impact weight will be lower.

[0128] Through this method, we can better understand and evaluate the impact of highway bridges on surrounding buildings and provide a scientific basis for relevant decision-making. For example, in urban planning, architectural design, traffic management, etc., this building impact weight can be used to make more reasonable layout and design to achieve harmonious development of transportation and architecture.

[0129] It can be understood that the dimension of the influencing building factor d is set according to the actual situation. If the unit of the construction area Sji is "square meters", the unit of the distance Sdi between the influencing building and the highway bridge is "meters", and the unit of the number of influencing buildings p is "buildings", then the unit of the influencing building factor d is "buildings / meter". No matter how the unit of the influencing building factor d is set, the building impact weight must be dimensionless.

[0130] In some embodiments of the present application, the comprehensive impact weight is calculated according to the following formula:

[0131] Q=Qz+Qh+Qj.

[0132] In some embodiments of the present application, the degree of damage is adjusted according to the comprehensive impact weight to obtain the final degree of damage to the highway bridge, including: presetting a first comprehensive impact weight, a second comprehensive impact weight and a third comprehensive impact weight, wherein the first comprehensive impact weight, the second comprehensive impact weight and the third comprehensive impact weight increase in sequence; adjusting the degree of damage according to the relationship between the comprehensive impact weight and the first comprehensive impact weight, the second comprehensive impact weight and the third comprehensive impact weight to obtain the final degree of damage to the highway bridge; if the comprehensive impact weight is less than the first comprehensive impact weight, then the degree of damage is not adjusted; if the comprehensive impact weight is less than the first comprehensive impact weight, then the degree of damage is not adjusted; if the comprehensive impact weight is less than the first comprehensive impact weight, then the degree of damage is not adjusted. If the comprehensive impact weight is greater than or equal to the first comprehensive impact weight, and the comprehensive impact weight is less than the second comprehensive impact weight, the disease degree will be increased by one level. If the disease degree is a serious disease, the disease degree will not be adjusted; if the comprehensive impact weight is greater than or equal to the second comprehensive impact weight, and the comprehensive impact weight is less than the third comprehensive impact weight, the disease degree will be increased by two levels. If the disease degree is a serious disease, the disease degree will not be adjusted; if the comprehensive impact weight is greater than or equal to the third comprehensive impact weight, the disease degree will be increased by three levels. If the disease degree is a serious disease, the disease degree will not be adjusted.

[0133] In this embodiment, the adjustment method of the degree of the disease is determined by determining the range of the comprehensive impact weight. First, three different levels of comprehensive impact weights are set, which are the first comprehensive impact weight, the second comprehensive impact weight and the third comprehensive impact weight. These three weights are successively increased, that is, the second comprehensive impact weight is higher than the first comprehensive impact weight, and the third comprehensive impact weight is higher than the second comprehensive impact weight. In the specific operation process, these comprehensive impact weights will be evaluated according to the specific situation of each disease. If the comprehensive impact weight of a disease is lower than the first comprehensive impact weight, then the degree of the disease is not adjusted and its original level is maintained. If the comprehensive impact weight is between the first comprehensive impact weight and the second comprehensive impact weight, then the level of the disease is raised by one level. However, if the original degree of the disease is already a serious disease, then it will not be adjusted. When the comprehensive impact weight is between the second comprehensive impact weight and the third comprehensive impact weight, the level of the disease is raised by two levels. However, if the degree of the disease after the increase reaches a serious disease, it will still not be adjusted. Finally, if the comprehensive impact weight is equal to or higher than the third comprehensive impact weight, the level of the disease will be increased by three levels. In this process, if the upgraded disease level is still a serious disease, its original level will be maintained without adjustment. Through such meticulous weight setting and degree adjustment, the scientificity and rationality of highway bridge disease assessment can be ensured, thus providing an important basis for bridge maintenance management and decision-making. This method not only considers the severity of the disease itself, but also takes into account the importance of various factors such as geographical location, traffic flow, bridge importance, etc. on the impact of the disease, making the assessment results more comprehensive and practical.

[0134] In some embodiments of the present application, after the highway bridge disease is identified according to the actual data of the highway bridge, it includes: issuing an early warning based on the identification result of the highway bridge disease, setting an early warning level according to the degree of the disease, and recording the identification result of the highway bridge disease and the early warning level: wherein, if the degree of the disease is a mild disease, a low-level early warning is issued; if the degree of the disease is a moderate disease, an intermediate early warning is issued; if the degree of the disease is a severe disease or a serious disease, a high-level early warning is issued.

[0135] In this embodiment, in the process of early warning and recording of highway bridge diseases, it is necessary not only to pay attention to the immediate status of the disease, but also to predict its development trend. For the identified diseases, it is necessary to formulate corresponding early warning levels according to the severity of the disease and the potential risks. For example, if the disease is a mild disease, a low-level early warning is carried out; if the disease is a moderate disease, a medium-level early warning is carried out; if the disease is a severe disease or a serious disease, a high-level early warning is carried out. At the same time, some suggestions can also be attached, such as routine maintenance and emergency repair or reinforcement measures.

[0136] It is understandable that the release of early warning information should ensure timely, accurate and comprehensive. Through modern information communication means, such as the Internet, mobile phone APP or SMS service, early warning information can be quickly conveyed to relevant responsible units, managers and maintenance personnel. At the same time, the early warning information should also include the specific location, type, severity and recommended response measures of the disease, so that relevant personnel can take prompt action. In terms of records, a complete highway bridge disease identification and early warning information recording system should be established. The system should be able to record in detail the results of each disease identification, the release of early warning information, the implementation effect of response measures and the subsequent development of the disease. Through data analysis, the trend of highway bridge diseases can be predicted, providing strong data support for future maintenance and repair work. Through scientific methods, advanced technology and perfect systems, the safety and smoothness of highway bridges can be effectively guaranteed.

[0137] like Figure 2 As shown, the present invention also discloses a highway bridge defect identification system, which is used to apply the above-mentioned highway bridge defect identification method, and the system includes:

[0138] The acquisition module is used to obtain pictures of highway bridge damage. The acquisition module is also used to obtain data on the use of highway bridges after they are built, and to obtain historical environmental data on the location of the highway bridges and data on buildings that affect the highway bridges within the specified range.

[0139] The image analysis module is used to analyze the highway bridge damage image to determine the damage type and damage degree of the highway bridge damage.

[0140] A weight determination module is used to determine the self-impact weight of the highway bridge according to the commissioning data, determine the environmental impact weight of the environment on the highway bridge according to the historical environmental data, and determine the construction impact weight of the highway bridge according to the influencing building data; the weight determination module is also used to determine the comprehensive impact weight of the highway bridge based on the self-impact weight, environmental impact weight and construction impact weight.

[0141] The damage determination module is used to adjust the damage degree according to the comprehensive impact weight to obtain the final damage degree of the highway bridge damage.

[0142] In this embodiment, the present invention adjusts the degree of damage by comprehensively considering the self-impact weight, environmental impact weight and building impact weight of the highway bridge, and can more comprehensively and accurately evaluate the actual damage condition of the bridge. It no longer relies solely on a single damage picture analysis, but combines various influencing factors after the bridge is put into use, such as vehicle traffic, environmental temperature and humidity changes, construction impact of surrounding buildings, etc., so that the damage assessment results are closer to the actual situation, greatly improving the efficiency of damage identification, and being able to detect problems in a timely manner. In addition, the present invention obtains an accurate final degree of damage, which is helpful to formulate a more targeted, scientific and reasonable maintenance and repair plan. It can predict the development trend of the disease in advance, reasonably arrange maintenance resources, avoid aggravated damage to the bridge structure due to untimely maintenance, and extend the service life of the bridge.

[0143] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

[0144] The system provided in the above embodiment is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be decomposed or combined. For example, the modules in the above embodiment can be combined into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not regarded as improper limitations of the present invention.

[0145] Those skilled in the art should be able to appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two, and the programs corresponding to the software modules and method steps can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the technical field. In order to clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

Claims

1. A highway bridge disease identification method, characterized in that: The method comprises: Obtaining highway bridge disease pictures, analyzing the highway bridge disease pictures, and determining the disease type and disease degree of the highway bridge disease; Obtain the data on the use of highway bridges after they are built, as well as the historical environmental data on the locations of highway bridges and the data on the buildings that affect the scope of the highway bridges; Determine the self-impact weight of the highway bridge according to the commissioning data, determine the environmental impact weight of the environment on the highway bridge according to the historical environmental data, and determine the construction impact weight of the highway bridge according to the construction impact data; The comprehensive impact weight of the highway bridge is determined based on the self-impact weight, the environmental impact weight and the building impact weight, and the degree of damage is adjusted according to the comprehensive impact weight to obtain the final degree of damage of the highway bridge.

2. The highway bridge disease identification method according to claim 1 is characterized in that: Analyze the highway bridge damage pictures to determine the damage type and damage degree of the highway bridge damage, including: Obtaining original pictures of highway bridges, wherein the original pictures of highway bridges are pictures of highway bridges that have passed acceptance but have not been put into use; De-noising the highway bridge disease image using Gaussian filtering to obtain a de-noised highway bridge disease image; Compare the noise reduction highway bridge disease pictures with the original highway bridge pictures to determine the difference areas; Segment the difference area to obtain the difference picture of highway bridge; Compare the highway bridge difference pictures with the highway bridge disease standard pictures, and determine the type of highway bridge disease according to the comparison results; and determining the degree of the corresponding defect type in the highway bridge difference image according to the defect type, and encoding the defect type and the degree of the defect; Among them, the types of diseases include crack disease, peeling disease, weathering disease and rust disease; Disease severity includes mild disease, moderate disease, severe disease, and serious disease; The types of damage, such as cracks, spalling, weathering, exposed steel bars and corrosion, are coded as A, B, C and D respectively; The mild disease, moderate disease, severe disease and serious disease in the disease degree are coded as L1, L2, L3, L4 respectively.

3. The highway bridge disease identification method according to claim 2 is characterized in that: Determine the degree of the corresponding damage type in the highway bridge difference image according to the damage type, including: Set disease evaluation standards corresponding to disease types according to disease types; Among them, the severity of crack damage is determined according to the crack width; Determine the severity of the spalling disease based on the spalling area; Determine the severity of weathering diseases based on weathering time and weathering area; Determine the severity of the rust disease based on the rust time and rust area.

4. The highway bridge disease identification method according to claim 3 is characterized in that: The severity of crack damage is determined based on the crack width, including: Presetting a first crack width, a second crack width and a third crack width, wherein the first crack width, the second crack width and the third crack width increase in sequence; Acquire the crack width in the highway bridge difference picture, and set the degree of the crack disease according to the relationship between the crack width and the first crack width, the second crack width and the third crack width; If the crack width is smaller than the first crack width, the damage degree of the crack damage is set to be a mild damage A-L1; If the crack width is greater than or equal to the first crack width, and the crack width is less than the second crack width, the damage degree of the crack disease is set to be moderate damage A-L2; If the crack width is greater than or equal to the second crack width, and the crack width is less than the third crack width, the degree of the crack disease is set to be severe disease A-L3; If the crack width is greater than or equal to the third crack width, the severity of the crack disease is set to severe disease A-L4; The severity of the spalling disease is determined based on the spalling area, including: Presetting a first peeling area, a second peeling area and a third peeling area, wherein the first peeling area, the second peeling area and the third peeling area increase in sequence; Acquire the spalling area in the highway bridge difference picture, and set the degree of the spalling disease according to the relationship between the spalling area and the first spalling area, the second spalling area and the third spalling area; If the spalling area is smaller than the first spalling area, the spalling disease severity is set to be a mild disease B-L1; If the spalling area is greater than or equal to the first spalling area, and the spalling area is less than the second spalling area, the spalling disease severity is set to moderate disease B-L2; If the spalling area is greater than or equal to the second spalling area, and the spalling area is less than the third spalling area, the spalling disease severity is set to severe disease B-L3; If the spalling area is greater than or equal to the third spalling area, the spalling disease severity is set to severe disease B-L4; The severity of weathering diseases is determined based on the weathering time and weathering area, including: Presetting a first weathering ratio, a second weathering ratio and a third weathering ratio, wherein the first weathering ratio, the second weathering ratio and the third weathering ratio increase in sequence; Obtaining the weathering time and weathering area corresponding to the weathering damage in the highway bridge difference image, determining the weathering ratio between the weathering area and the weathering time, and setting the damage degree of the weathering damage according to the relationship between the weathering ratio and the first weathering ratio, the second weathering ratio, and the third weathering ratio; If the weathering ratio is less than the first weathering ratio, the disease degree of the weathering disease is set to be a mild disease C-L1; If the weathering ratio is greater than or equal to the first weathering ratio, and the weathering ratio is less than the second weathering ratio, the disease degree of the weathering disease is set to be moderate disease C-L2; If the weathering ratio is greater than or equal to the second weathering ratio, and the weathering ratio is less than the third weathering ratio, the disease degree of the weathering disease is set to severe disease C-L3; If the weathering ratio is greater than or equal to the third weathering ratio, the disease degree of the weathering disease is set to severe disease C-L4; The severity of the rust disease is determined based on the rust time and rust area, including: Presetting a first corrosion ratio, a second corrosion ratio and a third corrosion ratio, wherein the first corrosion ratio, the second corrosion ratio and the third corrosion ratio increase in sequence; Obtaining the corrosion time and corrosion area corresponding to the corrosion disease in the highway bridge difference picture, determining the corrosion ratio between the corrosion area and the corrosion time, and setting the degree of the corrosion disease according to the relationship between the corrosion ratio and the first corrosion ratio, the second corrosion ratio and the third corrosion ratio; If the rust ratio is less than the first rust ratio, the rust disease severity is set to be a mild disease D-L1; If the corrosion ratio is greater than or equal to the first corrosion ratio, and the corrosion ratio is less than the second corrosion ratio, the degree of the corrosion disease is set to be moderate disease D-L2; If the corrosion ratio is greater than or equal to the second corrosion ratio, and the corrosion ratio is less than the third corrosion ratio, the degree of the corrosion disease is set to severe disease D-L3; If the rust ratio is greater than or equal to the third rust ratio, the disease degree of the rust disease is set to severe disease D-L4.

5. The highway bridge disease identification method according to claim 1 is characterized in that: The impact weight of the highway bridge itself is determined based on the commissioning data, including: The said data of putting into use include the number of days of use and the daily load-bearing weight; Determine the self-influencing factor of the highway bridge according to the daily load-bearing weight; Determine the self-influence weight of the highway bridge according to the usage days and the self-influence factor; The self-influence weight is calculated according to the following formula: Among them, Qz represents the self-influence weight, T represents the number of days of use, qi represents the self-influence factor, Lq represents the design load of the highway bridge, Wq represents the daily bearing capacity, q1 represents the first self-influence factor, q2 represents the second self-influence factor, and q3 represents the third self-influence factor.

6. The highway bridge disease identification method according to claim 5 is characterized in that: The weight of the environmental impact on the highway bridge is determined based on the historical environmental data, including: The historical environmental data include daily rainfall, daily humidity value and daily wind speed value; Pre-set rainfall threshold, humidity threshold and wind speed threshold; Comparing the daily rainfall with the rainfall threshold, and filtering rainfall data whose daily rainfall is higher than the rainfall threshold; Comparing the daily humidity value with the humidity threshold, and filtering humidity data whose daily humidity value is higher than the humidity threshold; Comparing the daily wind speed value with the wind speed threshold, and screening the wind speed data whose daily wind speed value is higher than the wind speed threshold; Determine the environmental impact weight of the environment on the highway bridge according to the rainfall data, humidity data and wind speed data; The environmental impact weight is calculated according to the following formula: Among them, Qh represents the environmental impact weight, a represents the rainfall impact factor, m represents the number of rainy days with daily rainfall higher than the rainfall threshold, Rx represents the daily rainfall on the xth day among m days, b represents the humidity impact factor, n represents the number of humidity days with daily humidity values ​​higher than the humidity threshold, Sy represents the daily humidity value on the yth day among n days, c represents the wind speed impact factor, k represents the number of wind speed days with daily wind speed values ​​higher than the wind speed threshold, and Wz represents the daily wind speed value on the zth day among k days.

7. The highway bridge disease identification method according to claim 6 is characterized in that: The construction impact weight of the highway bridge is determined based on the influencing building data, including: The affected building data include the distance between the affected building and the highway bridge and the construction area of ​​the affected building; Determine a ratio between the construction area and the distance, and determine a construction impact weight of the highway bridge according to the ratio; The building impact weight is calculated according to the following formula: Among them, Qj represents the building impact weight, d represents the impact building factor, p represents the number of impacted buildings, Sji represents the construction area of ​​the i-th impacted building, and Sdi represents the distance between the i-th impacted building and the highway bridge.

8. The highway bridge disease identification method according to claim 7 is characterized in that: The comprehensive impact weight is calculated according to the following formula: Q=Qz+Qh+Qj.

9. The highway bridge disease identification method according to claim 8, characterized in that: The damage degree is adjusted according to the comprehensive impact weight to obtain the final damage degree of the highway bridge damage, including: Presetting a first comprehensive influence weight, a second comprehensive influence weight, and a third comprehensive influence weight, wherein the first comprehensive influence weight, the second comprehensive influence weight, and the third comprehensive influence weight increase in sequence; The damage degree is adjusted according to the relationship between the comprehensive impact weight and the first comprehensive impact weight, the second comprehensive impact weight and the third comprehensive impact weight to obtain a final damage degree of the highway bridge damage; If the comprehensive impact weight is less than the first comprehensive impact weight, the disease degree is not adjusted; If the comprehensive impact weight is greater than or equal to the first comprehensive impact weight, and the comprehensive impact weight is less than the second comprehensive impact weight, the disease degree is increased by one level; if the disease degree is a serious disease, the disease degree is not adjusted; If the comprehensive impact weight is greater than or equal to the second comprehensive impact weight, and the comprehensive impact weight is less than the third comprehensive impact weight, the disease degree is increased by two levels; if the disease degree is a serious disease, the disease degree is not adjusted; If the comprehensive impact weight is greater than or equal to the third comprehensive impact weight, the disease level will be increased by three levels; if the disease level is a serious disease, the disease level will not be adjusted.

10. A highway bridge defect identification system, used for applying the highway bridge defect identification method according to any one of claims 1 to 9, characterized in that: The system comprises: An acquisition module is used to acquire images of road bridge damage. The acquisition module is also used to acquire data on the road bridge being put into use after completion, and to acquire historical environmental data on the location of the road bridge and data on buildings that affect the road bridge within the specified range; An image analysis module is used to analyze the highway bridge damage image to determine the type and degree of the highway bridge damage; A weight determination module is used to determine the self-impact weight of the highway bridge according to the commissioning data, determine the environmental impact weight of the environment on the highway bridge according to the historical environmental data, and determine the building impact weight of the highway bridge according to the building impact data; the weight determination module is also used to determine the comprehensive impact weight of the highway bridge based on the self-impact weight, environmental impact weight and building impact weight; The damage determination module is used to adjust the damage degree according to the comprehensive impact weight to obtain the final damage degree of the highway bridge damage.

Images