Big data-based prefabricated bridge deck load safety monitoring system and method

Abstract

The application discloses a large-data-based assembled bridge bridge deck load safety monitoring system and method, and belongs to the technical field of bridge safety. In order to solve the problem that the overall image collection and monitoring of the bridge deck are difficult, the image processing unit performs perspective adjustment on the gray scale processed image of the bridge deck and fuses to generate a bridge deck combined image, so that the subsequent image splicing module can splice and fuse the image more conveniently, the driving vehicle condition of the entire bridge deck of the bridge and the bridge deck condition are captured and generated as a whole, it is not necessary to separately monitor and analyze the monitoring images of different angles, regions or ranges, the bridge deck simulation unit simulates and generates a bridge deck model based on the bridge deck combined image and divides the monitoring region, so that the monitoring of the bridge deck is more intuitive, the monitoring of each region of the bridge deck and the bridge body of the assembled bridge is realized, the safety influence coefficient of the bridge is rated, the safety condition problem of the bridge is found in time, and early warning and maintenance treatment are performed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bridge safety, in particular to an assembled bridge deck load safety monitoring system and method based on big data. BACKGROUND

[0002] The assembled bridge (prefabricated and assembled bridge) is different from the traditional on-site construction of steel bar binding and concrete pouring bridge construction method. For the assembled bridge, part or all of the components of the bridge substructure (pier column, pile cap, capping beam) and superstructure (box girder, plate girder, T girder) are transported to the construction site after being processed and formed in the prefabricated component factory, and then hoisted and spliced into the bridge main body. The components of the bridge are mechanically connected through the embedded hole position, embedded steel bar and connecting device processed in the prefabricated production process, and the grouting sleeve in the component is used for grouting to make the concrete fully fill the pores between the components and achieve the overall strengthening effect.

[0003] The existing assembled bridge still has the following problems when it is put into use and maintained.

[0004] When monitoring the bridge deck of the assembled bridge under the prior art, multiple different cameras are often used to collect images in sections for regional monitoring. However, the positions and angles of different cameras are not the same, and it is difficult to monitor the overall situation of the bridge deck as a whole through the collected video images. It is often necessary to combine multiple regions, which is not intuitive and convenient, and it is difficult to detect and alarm the overall operation of the assembled bridge deck and the load. SUMMARY

[0005] The purpose of the present application is to provide an assembled bridge deck load safety monitoring system and method based on big data to solve the problems raised in the background.

[0006] To achieve the above purpose, the present application provides the following technical scheme: an assembled bridge deck load safety monitoring system based on big data, comprising:

[0007] The big data grabbing unit is used for:

[0008] The information data is transmitted between the monitoring terminal and the data acquisition equipment through the network, the bridge deck image data collected by the data acquisition equipment is acquired, the grabbed bridge deck image data is preprocessed, and the data acquisition time and the point number of the data acquisition equipment are marked and sorted and packaged and transmitted to the image processing unit;

[0009] The image processing unit is used for:

[0010] The bridge deck image data is normalized to obtain a bridge deck gray scale processing image, the bridge deck gray scale processing image is perspective adjusted, the image after perspective adjustment is arranged and combined and fused to generate a bridge deck combined image;

[0011] The bridge deck simulation unit is configured to:

[0012] The bridge deck combined image is simulated to generate a bridge deck model and divide a monitoring area;

[0013] The safety monitoring unit is configured to:

[0014] The safety monitoring unit is configured to:

[0015] The monitoring terminal is configured to:

[0016] The monitoring terminal is configured to:

[0017] The data acquisition device is configured to:

[0018] The data acquisition device is configured to:

[0019] Further, the big data grabbing unit comprises:

[0020] The network communication module is configured to:

[0021] The network communication module is configured to:

[0022] The data grabbing module is configured to:

[0023] The data grabbing module is configured to:

[0024] The data transmission module is configured to:

[0025] The bridge deck image data sorted and labeled is packaged and transmitted to an image processing unit.

[0026] Further, the image processing unit comprises:

[0027] An image processing module, configured to:

[0028] normalize the bridge deck image data into a fixed standard form of grayscale image, and strengthen the high frequency components of each grayscale image after transformation, to obtain a bridge deck grayscale processing image;

[0029] A perspective adjustment module, configured to:

[0030] adjust the perspective of the bridge deck grayscale processing image, and output a bridge deck adjustment image after perspective adjustment;

[0031] An image stitching module, configured to:

[0032] arrange and combine the bridge deck adjustment images generated by the bridge deck image data collected at the same time, sort based on the point number of the data collection device corresponding to each bridge deck image data during arrangement, and stitch and fuse the arranged and combined bridge deck adjustment images to generate a bridge deck combination image.

[0033] Further, the perspective adjustment module adjusts the perspective of the bridge deck grayscale processing image, and specifically comprises the following steps:

[0034] extract and identify the quadrilateral of the fabricated bridge deck part in each bridge deck grayscale processing image through edge detection and corner detection;

[0035] label each vertex of the quadrilateral, generate a plane coordinate system based on the bridge deck grayscale processing image, and obtain the coordinates of each vertex of the quadrilateral of the fabricated bridge deck part;

[0036] determine the correction target plane rectangular data of the fabricated bridge deck;

[0037] select the coordinates of each vertex of the quadrilateral, and transform the coordinates of each vertex of the quadrilateral to match the correction target plane rectangular data;

[0038] perform rectangular transformation on the quadrilateral of the fabricated bridge deck part based on the coordinates of each vertex of the matched quadrilateral;

[0039] complete the perspective adjustment and output the bridge deck adjustment image.

[0040] Further, the bridge deck simulation unit comprises:

[0041] A bridge deck generation module, configured to:

[0042] The bridge deck model is generated based on the combined bridge deck images, and the bridge deck model is updated in time based on the combined bridge deck images at different collection times.

[0043] The area division module is configured to:

[0044] The bridge deck model is divided into rectangular monitoring areas of the same shape and size, and different monitoring areas are labeled.

[0045] Further, the safety monitoring unit includes:

[0046] The bridge deck identification module is configured to:

[0047] The internal area of each monitoring area of the bridge deck model is identified, the vehicles in each monitoring area at the same collection time are identified, and the bridge deck conditions are identified, including cracks, potholes, and foreign objects.

[0048] The safety rating module is configured to:

[0049] Based on the identification results of the bridge deck identification module, the internal area of each monitoring area of the bridge deck model is analyzed, all vehicles at the same collection time on the prefabricated bridge are counted and the load is predicted, and an alarm is given when the predicted load of the prefabricated bridge exceeds the load safety threshold.

[0050] The area alarm module is configured to:

[0051] When cracks, potholes, or foreign objects are identified in the internal area of each monitoring area, an area alarm is given.

[0052] Further, the data collection device is an image collection camera, which is arranged above the prefabricated bridge deck on both sides at a high altitude, and each data collection device is arranged equidistantly apart. Based on the positions and sequences of each data collection device, the data collection devices are numbered, and the bridge deck image data collected by each data collection device is labeled according to the corresponding data.

[0053] Further, in the monitoring terminal, information is exchanged with the data collection device through a network, including:

[0054] The node construction unit is configured to construct a first network node, a second network node, and a third network node in the network.

[0055] The address acquisition unit is configured to acquire a first node address corresponding to the first network node, a second node address corresponding to the second network node, and a third node address corresponding to the third network node.

[0056] The communication connection construction unit is configured to construct a first communication connection based on the first node address and the second node address, construct a second communication connection based on the second node address and the third node address, construct a third communication connection based on the first node address and the third node address, and construct a fourth communication connection based on the first node address and the device address of the data acquisition device;

[0057] The first network node reading unit is configured to:

[0058] The data acquisition device is configured to obtain the to-be-interacted information, and based on the fourth communication connection, input the to-be-interacted information to the first network node of the network for reading, determine an information keyword of the to-be-interacted information, and determine an information identifier of the to-be-interacted information according to the information keyword of the to-be-interacted information, identify the information identifier in a preset template library, and output an information format template according to an identification result.

[0059] The information format template is configured to perform first layout on the to-be-interacted information to obtain standard to-be-interacted information.

[0060] The second network node reading unit is configured to:

[0061] The second network node reading unit is configured to:

[0062] The third network node reading unit is configured to, when the credibility of the standard to-be-interacted information reaches the credibility threshold, transmit the standard to-be-interacted information to the third network node based on the second communication connection, and based on the third network node, analyze the standard to-be-interacted information to determine an interaction demand of the standard to-be-interacted information, and determine interaction feedback information according to the interaction demand of the standard to-be-interacted information.

[0063] The first network node reading unit is further configured to transmit the interaction feedback information to the first network node based on the third communication connection, and according to an initial format of the to-be-interacted information obtained by the first network node, perform second layout on the interaction feedback information based on the initial format of the to-be-interacted information, and output standard interaction feedback information based on a format conversion result.

[0064] The information feedback unit is configured to transmit the standard interaction feedback information to the data acquisition device based on the fourth communication connection, and complete information interaction.

[0065] Further, the second network reading unit is configured to determine the credibility of the standard to-be-interacted information, including:

[0066] The matching subunit is used for:

[0067] The interaction information management library is acquired, and the standard to-be-interacted information is input into the interaction information management library for matching;

[0068] Based on the matching result, the first sub to-be-interacted information in the standard to-be-interacted information which matches the corresponding historical interaction information in the interaction information management library and the second sub to-be-interacted information in the standard to-be-interacted information which does not match the corresponding standard interaction information in the interaction information management library are determined;

[0069] The calculation subunit is used for:

[0070] The first data amount of the first sub to-be-interacted information is acquired, and simultaneously, the second data amount of the second sub to-be-interacted information is acquired;

[0071] The credibility of the standard to-be-interacted information is calculated based on the first data amount and the second data amount;

[0072]

[0073] Wherein, φ represents the credibility value of the standard to-be-interacted information; M represents the total data amount of the standard to-be-interacted information; m1 represents the first data amount; and m2 represents the second data amount.

[0074] Another technical problem to be solved by the present application is to provide a monitoring method of a prefabricated bridge deck load safety monitoring system based on big data, comprising the following steps:

[0075] Step one: the data acquisition equipment acquires the bridge deck image data of the prefabricated bridge;

[0076] Step two: the big data grabbing unit grabs the bridge deck image data and pre-processes, marks and sorts based on the data acquisition time and the point number of the data acquisition equipment;

[0077] Step three: the image processing unit processes the bridge deck image data to obtain a bridge deck grayscale processing image, adjusts the perspective of the bridge deck grayscale processing image and fuses and combines to generate a bridge deck combined image;

[0078] Step four: the bridge deck simulation unit generates a bridge deck model and divides the monitoring area, and the safety monitoring unit identifies, monitors and alarms inside each monitoring area of the bridge deck model.

[0079] Compared with the prior art, the present application has the following advantages:

[0080] 1. The image processing unit of the present application normalizes the bridge deck image data to obtain a bridge deck grayscale processed image, adjusts the perspective of the bridge deck grayscale processed image, arranges and combines the image after perspective adjustment and fuses to generate a bridge deck combined image, so that the subsequent image splicing module can be more convenient when splicing and fusing the image, and the entire bridge deck driving vehicle condition and bridge deck condition are captured and generated as a whole, without the need to monitor and analyze each different angle, region or range of monitoring image separately.

[0081] 2. The bridge deck simulation unit of the present application simulates and generates a bridge deck model based on the bridge deck combined image and divides the monitoring area, so that the bridge deck monitoring is more intuitive, the safety monitoring unit identifies each monitoring area inside the bridge deck model, based on the identification result of the bridge deck identification module, and when the bearing load exceeds the load safety threshold, an alarm is given, and when an abnormality occurs in the monitoring area, a regional alarm is given, realizing monitoring of each area of the assembled bridge deck and bridge body, rating the safety influence coefficient of the bridge, discovering the safety condition problem of the bridge in time, and giving early warning and maintenance treatment.

[0082] 3. By constructing the first network node, the second network node and the third network node, and then realizing the transmission of information data through the first communication connection, the second communication connection, the third communication connection and the fourth communication connection, the format conversion and the credibility determination of the to-be-interacted information are realized through the first network node, the second network node and the third network node, so as to effectively guarantee the efficiency and accuracy of reading when interacting with the to-be-interacted information, and also guarantee the credibility of the to-be-interacted information, thereby being beneficial to guarantee the effectiveness, accuracy and reliability of information interaction with the data acquisition device through the network. BRIEF DESCRIPTION OF DRAWINGS

[0083] Figure 1 The figure is a schematic diagram of the system module of the present application. DETAILED DESCRIPTION

[0084] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0085] In order to solve the technical problems in the prior art that when monitoring the bridge deck during assembly, images are often collected by multiple different cameras in different sections for regional monitoring, the positions and angles of different cameras are different, and the overall situation of the bridge deck cannot be monitored through the collected video images, often needing to combine multiple regions, which is not intuitive and convenient, and it is difficult to detect and alarm the overall operation and load of the assembled bridge deck, please refer to Figure 1 The application provides the following technical scheme:

[0086] The assembled bridge deck load safety monitoring system based on big data comprises:

[0087] The big data acquisition unit is used for:

[0088] Information data transmission is performed between the monitoring terminal and the data acquisition equipment through the network, the bridge deck image data collected by the data acquisition equipment is acquired, the acquired bridge deck image data is preprocessed, the bridge deck image data is marked and sorted based on the data acquisition time and the point position number of the data acquisition equipment and is packaged and transmitted to the image processing unit, the bridge deck image data under the same acquisition time is marked through the big data acquisition unit, so that the bridge deck situation at the same time can be summarized and analyzed subsequently, the bridge deck image data under the same acquisition time is processed and spliced when subsequent processing is performed, and the overall bridge deck situation acquisition image under the same time can be obtained, and the bridge deck image data is sorted and spliced according to the positioning number of the corresponding data acquisition equipment of each bridge deck image data when splicing.

[0089] The image processing unit is used for:

[0090] The bridge deck image data is subjected to normalization processing to obtain a bridge deck grayscale processing image, the bridge deck grayscale processing image is subjected to perspective adjustment, the image subjected to perspective adjustment is arranged and combined and fused to generate a bridge deck combined image, so that the image can be spliced and fused more conveniently by the subsequent image splicing module, the driving vehicle situation of the entire bridge deck and the bridge deck situation are captured and generated as a whole, and it is not necessary to monitor and analyze the monitoring images of different angles, regions or ranges respectively.

[0091] The bridge deck simulation unit is used for:

[0092] The bridge deck combined image is used to simulate and generate a bridge deck model and divide a monitoring region, the bridge deck simulation unit can integrate and simulate the entire bridge deck situation, the monitoring of the bridge deck is more intuitive, the problem location on the bridge deck can be directly displayed, and it is more convenient for the staff to divide and identify the hidden danger location region.

[0093] The safety monitoring unit is used for:

[0094] The inside of each monitoring area of the bridge deck model is identified, and based on the identification result of the bridge deck identification module, an alarm is given when the load exceeds the load safety threshold, and a regional alarm is given when an anomaly occurs in the monitoring area. The number and type of vehicles on the bridge deck model can be counted by the safety monitoring unit, so as to predict the overall load on the bridge, thereby realizing monitoring of each area of the assembled bridge deck and bridge body, rating the safety influence coefficient of the bridge, discovering the safety problem of the bridge in time, and giving early warning and maintenance treatment.

[0095] The monitoring terminal is used to:

[0096] The big data grabbing unit, the image processing unit, the bridge deck simulation unit and the safety monitoring unit are carried and control the big data-based assembled bridge deck load safety monitoring system. The monitoring terminal sends and receives the transmitted data, and realizes signal interaction connection with the big data grabbing unit, the image processing unit, the bridge deck simulation unit and the safety monitoring unit through the network, and simultaneously realizes information interaction with the data acquisition device through the network;

[0097] The data acquisition device is used to:

[0098] The bridge deck image data of the assembled bridge is collected. Each data acquisition device is provided with different point numbers according to the set position. The data acquisition device is provided above the assembled bridge. The data acquisition device is an image acquisition camera. The image acquisition camera is provided above the high altitude on both sides of the assembled bridge deck. Each data acquisition device is provided at equal intervals. The data acquisition device is numbered based on the position and sequence of each data acquisition device. The bridge deck image data collected by each data acquisition device is marked with corresponding data according to the point number.

[0099] Specifically, when the load safety of the assembled bridge deck is monitored, the bridge deck image data of the assembled bridge is collected by the installed data acquisition device, then the big data grabbing unit grabs the bridge deck image data and pre-processes it, and the data is marked and sorted based on the collection time and the point number of the data acquisition device. The image processing unit processes the bridge deck image data to obtain a bridge deck grayscale processing image, adjusts the perspective of the bridge deck grayscale processing image and fuses and combines to generate a bridge deck combined image. Finally, the bridge deck simulation unit generates a bridge deck model and divides the monitoring area. The safety monitoring unit identifies, monitors and alarms the inside of each monitoring area of the bridge deck model.

[0100] By setting up image acquisition camera and data collection, the bridge deck and the bridge body of the assembled bridge are divided into regions, the collected images are processed and the data are analyzed, the various regions of the bridge deck and the bridge body of the assembled bridge are monitored, the safety influence coefficient of the bridge is rated, the safety problems of the bridge are found in time, and early warning and maintenance treatment are carried out.

[0101] The big data grabbing unit comprises:

[0102] The network communication module is used for:

[0103] network signal interaction communication with the Internet of Things and the Internet, and information data transmission between the monitoring terminal and the data acquisition equipment through the network;

[0104] The data grabbing module is used for:

[0105] connecting the data acquisition equipment through the Internet of Things, acquiring the bridge deck image data collected by the data acquisition equipment, pre-processing the grabbed bridge deck image data, marking and sorting the bridge deck image data according to the collection time and the point position number of the data acquisition equipment based on each bridge deck image data collected by each data acquisition equipment;

[0106] The data transmission module is used for:

[0107] packaging and transmitting the grabbed and marked and sorted bridge deck image data to the image processing unit.

[0108] Specifically, the bridge deck image data under the same collection time is marked by the big data grabbing unit, which is convenient for subsequent summarization and analysis of the bridge deck condition at the same time, and the bridge deck image data under the same collection time is processed and spliced to obtain the overall condition collection image of the bridge at the moment when the bridge deck image data under the same collection time is processed and spliced during subsequent processing. When splicing, the positioning number of the corresponding data acquisition equipment of each bridge deck image data is sorted and spliced.

[0109] The image processing unit comprises:

[0110] The image processing module is used for:

[0111] normalizing the bridge deck image data, transforming it into a fixed standard form of gray image, and strengthening the high frequency components of each gray image after transformation to obtain a bridge deck gray processing image;

[0112] The perspective adjustment module is used for:

[0113] The perspective adjustment is performed on the bridge gray processing image, the quadrilateral of the bridge deck part of the assembled bridge in each bridge gray processing image is extracted and recognized through edge detection and corner detection, each vertex of the quadrilateral is marked, a plane coordinate system is generated based on the bridge gray processing image, the coordinates of each vertex of the quadrilateral of the bridge deck part of the assembled bridge are acquired, the correction target plane rectangular data of the bridge deck of the assembled bridge is determined, the coordinates of each vertex of the quadrilateral are selected, the coordinates of each vertex of the quadrilateral are transformed to match the correction target plane rectangular data, the rectangular transformation is performed on the quadrilateral of the bridge deck part of the assembled bridge based on the coordinates of each vertex of the matched quadrilateral, and the bridge adjustment image is output after the perspective adjustment.

[0114] The image stitching module is configured to:

[0115] The bridge adjustment images generated based on the bridge image data collected at the same collection time are arranged and combined, the bridge adjustment images after the arrangement and combination are stitched and fused to generate a bridge combination image.

[0116] Specifically, the perspective adjustment module can correct the perspective angle of the bridge gray processing image, so that the collected images can be arranged, the problem that the images are difficult to directly splice due to the shooting angle and position is solved, the image stitching module can splice and fuse the images more conveniently, the driving vehicle condition and the bridge deck condition of the entire bridge deck are captured and generated as a whole, and it is not necessary to separately monitor and analyze the monitoring images of different angles, regions or ranges.

[0117] The bridge deck simulation unit includes:

[0118] The bridge deck generation module is configured to:

[0119] The bridge deck generation module is configured to:

[0120] The region division module is configured to:

[0121] The region division module is configured to:

[0122] Specifically, the bridge deck simulation unit can integrate and simulate the entire bridge deck condition, the monitoring of the bridge deck is more intuitive, the problem location on the bridge deck can be directly displayed, and it is more convenient for the staff to divide and identify the problem location region.

[0123] The safety monitoring unit includes:

[0124] The bridge deck recognition module is configured to:

[0125] The bridge deck recognition module is configured to recognize the inside of each monitoring area of the bridge deck model, recognize vehicles in each monitoring area at the same collection time, and recognize the bridge deck condition, including cracks, potholes, and foreign objects.

[0126] The safety rating module is configured to:

[0127] The safety rating module is configured to perform safety rating analysis on the inside of each monitoring area of the bridge deck model based on the recognition result of the bridge deck recognition module, count all vehicles on the prefabricated bridge at the same collection time based on the recognition result, and predict the load bearing, and issue an alarm when the predicted load bearing of the prefabricated bridge exceeds the load safety threshold.

[0128] The area alarm module is configured to:

[0129] The area alarm module is configured to issue an area alarm when cracks, potholes, or foreign objects are identified in each monitoring area.

[0130] Specifically, the safety monitoring unit can count the number and types of vehicles on the bridge deck model, thereby predicting the overall load on the bridge, monitoring each area of the prefabricated bridge deck and bridge body, rating the safety influence coefficient of the bridge, and timely discovering safety problems of the bridge and issuing warnings and maintenance treatments.

[0131] The embodiment also provides a prefabricated bridge deck load safety monitoring system based on big data, and the monitoring terminal is configured to interact with a data collection device through a network, including:

[0132] The node construction unit is configured to construct a first network node, a second network node, and a third network node in the network.

[0133] The address acquisition unit is configured to acquire a first node address corresponding to the first network node, a second node address corresponding to the second network node, and a third node address corresponding to the third network node.

[0134] The communication connection construction unit is configured to construct a first communication connection based on the first node address and the second node address, construct a second communication connection based on the second node address and the third node address, construct a third communication connection based on the first node address and the third address, and construct a fourth communication connection based on the first node address and a device address of the data collection device.

[0135] The first network node reading unit is configured to:

[0136] The data acquisition device obtains the information to be interacted, and simultaneously, the data acquisition device inputs the information to be interacted to the first network node of the network based on the fourth communication connection to read the information to be interacted, determines the information keyword of the information to be interacted, and determines the information identifier of the information to be interacted according to the information keyword of the information to be interacted, simultaneously, identifies the information identifier of the information to be interacted in the preset template library, and outputs the information format template according to the identification result;

[0137] The information to be interacted is first laid out based on the information format template to obtain standard information to be interacted;

[0138] The second network node reading unit is used for:

[0139] The standard information to be interacted is transmitted to the second network node based on the first communication connection, and the standard information to be interacted is read based on the second network node to determine the credibility of the standard information to be interacted, and simultaneously, when the credibility of the standard information to be interacted does not reach the credibility threshold, the interaction request for interacting the information to be interacted is interrupted;

[0140] The third network node reading unit is used for: when the credibility of the standard information to be interacted reaches the credibility threshold, the standard information to be interacted is transmitted to the third network node based on the second communication connection, and the standard information to be interacted is analyzed based on the third network node to determine the interaction demand of the standard information to be interacted, and simultaneously, the interaction feedback information is determined according to the interaction demand of the standard information to be interacted;

[0141] The first network node reading unit is also used for transmitting the interaction feedback information to the first network node based on the third communication connection, and the initial format of the information to be interacted is obtained according to the first network node, simultaneously, the interaction feedback information is second laid out based on the initial format of the information to be interacted, and the standard interaction feedback information is output based on the format conversion result;

[0142] The information feedback unit is used for transmitting the standard interaction feedback information to the data acquisition device based on the fourth communication connection, and completing information interaction.

[0143] In this embodiment, the first network node can be used to identify and read the information to be interacted, and lay out the information to be interacted to obtain the standard information to be interacted (wherein the standard information to be interacted can be determined after the information to be interacted is laid out, and the purpose of the layout is to enable the second network node to accurately read.

[0144] In this embodiment, the second network node can be used to read the standard information to be interacted to determine the credibility of the standard information to be interacted, thereby guaranteeing the effective and accurate interaction of the standard information to be interacted.

[0145] In this embodiment, the third network node can be used to parse the standard to-be-interacted information, so as to determine the interaction demand of the standard to-be-interacted information, and then realize the generation of the interaction feedback information (the interaction feedback information is the execution information corresponding to the standard to-be-interacted information).

[0146] In this embodiment, the first node address (the address of the first network node) and the second node address (the address of the second network node) construct the first communication connection, realizing the communication between the first network node and the second network node; the second node address and the third node address (the address of the third network node) construct the second communication connection, realizing the data communication between the second network node and the third network node; the first node address and the third node address construct the third communication connection, realizing the data communication between the third network node and the first network node; and the first node address and the device address of the data acquisition device construct the fourth communication connection, realizing the data communication between the first node address and the data acquisition device.

[0147] In this embodiment, the information keyword of the to-be-interacted information can include the information header data, the tail data of the to-be-interacted information, and the key data of the interaction execution in the to-be-interacted information.

[0148] In this embodiment, the information identifier of the to-be-interacted information can be a representation label of the to-be-interacted information determined based on the keyword of the to-be-interacted information.

[0149] In this embodiment, the preset template library can be set in advance, and stores the format templates corresponding to different identifiers, wherein the format templates of different identifiers are provided for the second network node to read data conveniently.

[0150] In this embodiment, the trust threshold can be set in advance, and used as a standard for measuring whether to continue the interaction.

[0151] In the second network reading unit, the trust degree of the standard to-be-interacted information includes:

[0152] The matching subunit is configured to: acquire an interaction information management library (set in advance, containing all trusted historical interaction information), and input the standard to-be-interacted information into the interaction information management library for matching; and determine, based on the matching result, the first sub to-be-interacted information in the standard to-be-interacted information that matches the corresponding historical interaction information in the interaction information management library, and the second sub to-be-interacted information in the standard to-be-interacted information that does not match the corresponding standard interaction information in the interaction information management library.

[0153] The calculation subunit is configured to: acquire a first data amount of the first sub to-be-interacted information, and simultaneously acquire a second data amount of the second sub to-be-interacted information; and calculate the trust degree of the standard to-be-interacted information based on the first data amount and the second data amount.

[0154]

[0155] Wherein, φ represents the standard degree of trust value of information to be interacted; M represents the total data quantity of the standard information to be interacted; m1 represents the first data quantity; m2 represents the second data quantity.

[0156] The working principle and beneficial effects of the above technical solution are: by constructing the first network node, the second network node and the third network node, and then realizing the transmission of information data through the first communication connection, the second communication connection, the third communication connection and the fourth communication connection, the format conversion of the information to be interacted is realized through the first network node, the second network node and the third network node, and the degree of trust is determined, thereby effectively guaranteeing the efficiency and accuracy of reading when the information to be interacted is interacted, and at the same time, the degree of trust of the information to be interacted is guaranteed, thereby being conducive to guaranteeing the effectiveness, accuracy and reliability of information interaction through the network and the data acquisition device.

[0157] In order to better show the assembly type bridge deck load safety monitoring process based on big data, the present embodiment proposes a monitoring method of the assembly type bridge deck load safety monitoring system based on big data, which comprises the following steps:

[0158] Step one: the data acquisition device collects the bridge deck image data of the assembly type bridge;

[0159] Step two: the big data grabbing unit grabs the bridge deck image data and pre-processes it, and marks and sorts it based on the data collection time and the point number of the data acquisition device;

[0160] Step three: the image processing unit processes the bridge deck image data to obtain a bridge deck grayscale processing image, adjusts the perspective of the bridge deck grayscale processing image and fuses and combines it to generate a bridge deck combined image;

[0161] Step four: the bridge deck simulation unit generates a bridge deck model and divides the monitoring area, and the safety monitoring unit identifies, monitors and alarms inside each monitoring area of the bridge deck model.

[0162] The above is only the preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can make equivalent replacement or change according to the technical solution and the inventive concept of the present application within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A prefabricated bridge deck load safety monitoring system based on big data, characterized in that, The application relates to a big data acquisition unit, an image processing unit, a bridge surface simulation unit, a safety monitoring unit and a monitoring terminal. The big data acquisition unit is used for transmitting information data between a monitoring terminal and a data acquisition device through a network, acquiring bridge surface image data collected by the data acquisition device, pre-processing the acquired bridge surface image data, marking and sorting the pre-processed bridge surface image data based on the collection time of the data and the point number of the data acquisition device, and transmitting the marked and sorted bridge surface image data to the image processing unit. The image processing unit is used for normalizing the bridge surface image data to obtain a bridge surface grayscale processing image, adjusting the perspective of the bridge surface grayscale processing image, arranging and combining the image after the perspective adjustment, and fusing the arranged and combined image to generate a bridge surface combined image. The bridge surface simulation unit is used for simulating a bridge surface model based on the bridge surface combined image and dividing a monitoring area. The safety monitoring unit is used for identifying the inside of each monitoring area of the bridge surface model, alarming when the load exceeds a load safety threshold based on the identification result of the bridge surface identification module, and regionally alarming when an abnormality occurs in the monitoring area. The monitoring terminal is used for carrying the big data acquisition unit, the image processing unit, the bridge surface simulation unit and the safety monitoring unit, controlling the big data-based assembled bridge surface load safety monitoring system, sending and receiving transmitted data, and realizing signal interaction connection with the big data acquisition unit, the image processing unit, the bridge surface simulation unit and the safety monitoring unit through a network, and realizing information interaction with the data acquisition device through the network. In the monitoring terminal, the information interaction with the data acquisition device through the network comprises: A node construction unit is used for constructing a first network node, a second network node and a third network node in the network. An address acquisition unit is used for acquiring a first node address corresponding to the first network node, a second node address corresponding to the second network node and a third node address corresponding to the third network node. A communication connection construction unit is used for constructing a first communication connection based on the first node address and the second node address, constructing a second communication connection based on the second node address and the third node address, constructing a third communication connection based on the first node address and the third node address, and constructing a fourth communication connection based on the first node address and a device address of the data acquisition device. The first network node reading unit is used for acquiring to-be-interacted information based on the data acquisition device, reading the to-be-interacted information based on the data acquisition device and inputting the to-be-interacted information into the first network node of the network according to the fourth communication connection, determining an information keyword of the to-be-interacted information, determining an information identifier of the to-be-interacted information according to the information keyword of the to-be-interacted information, identifying the information identifier of the to-be-interacted information in a preset template library, and outputting an information format template according to the identification result. The first network node reading unit is used for acquiring to-be-interacted information based on the data acquisition device, reading the to-be-interacted information based on the data acquisition device and inputting the to-be-interacted information into the first network node of the network according to the fourth communication connection, determining an information keyword of the to-be-interacted information, determining an information identifier of the to-be-interacted information according to the information keyword of the to-be-interacted information, identifying the information identifier of the to-be-interacted information in a preset template library, and outputting an information format template according to the identification result. The second network node reading unit is used for ​ ​ ​ ​ ​ ​ The standard to-be-interacted information is transmitted to the second network node based on the first communication connection, and the credibility of the standard to-be-interacted information is determined based on reading of the standard to-be-interacted information by the second network node, and meanwhile, when the credibility of the standard to-be-interacted information does not reach a credibility threshold, the interaction request for interacting with the to-be-interacted information is interrupted; The third network node reading unit is configured to: when the credibility of the standard to-be-interacted information reaches the credibility threshold, transmit the standard to-be-interacted information to the third network node based on the second communication connection, and determine the interaction demand of the standard to-be-interacted information based on analysis of the standard to-be-interacted information by the third network node, and meanwhile, determine the interaction feedback information according to the interaction demand of the standard to-be-interacted information; The first network node reading unit is further configured to: transmit the interaction feedback information to the first network node based on the third communication connection, and determine an initial format of the to-be-interacted information according to the first network node, and meanwhile, perform second layout on the interaction feedback information based on the initial format of the to-be-interacted information, and output the standard interaction feedback information based on the format conversion result; The information feedback unit is configured to: transmit the standard interaction feedback information to the data acquisition device based on the fourth communication connection, and complete information interaction; The data acquisition device is configured to: Collect bridge deck image data of the prefabricated bridge, and each data acquisition device is provided with a different point number according to a set position, and the data acquisition device is arranged at a high position above the prefabricated bridge.

2. The big data based fabricated bridge deck load safety monitoring system according to claim 1, wherein: The big data grabbing unit comprises: The network communication module is configured to: Interact with the Internet of Things and the Internet through network signal communication, and transmit information data between the monitoring terminal and the data acquisition device through the network; The data grabbing module is configured to: Connect the data acquisition device through the Internet of Things, acquire the bridge deck image data collected by the data acquisition device, and pre-process the grabbed bridge deck image data, mark and sort the bridge deck image data in time sequence based on the collection time of each bridge deck image data collected by each data acquisition device and the point number of the data acquisition device; The data transmission module is configured to: Package and transmit the grabbed and marked and sorted bridge deck image data to the image processing unit.

3. The big data based fabricated bridge deck load safety monitoring system according to claim 1, wherein: The image processing unit comprises: The image processing module is configured to: Normalize the bridge deck image data, transform it into a fixed standard form of a gray-scale image, and strengthen the high-frequency components of each gray-scale image after transformation to obtain a bridge deck gray-scale processing image; The perspective adjustment module is configured to: Adjust the perspective of the bridge deck gray-scale processing image, and output a bridge deck adjustment image after perspective adjustment; The image splicing module is configured to: Arrange and combine the bridge deck adjustment images generated by the bridge deck image data collected at the same collection time, sort the bridge deck adjustment images based on the point number of the data acquisition device corresponding to each bridge deck image data during arrangement, and splice and fuse the arranged and combined bridge deck adjustment images to generate a bridge deck combination image.

4. The big data based fabricated bridge deck load safety monitoring system of claim 3, wherein: The perspective adjustment module adjusts the perspective of the bridge deck gray-scale processing image, and specifically comprises the following steps: Extract and identify quadrilaterals in the bridge deck part of each bridge deck gray-scale processing image through edge detection and corner point detection; Marking each vertex of the quadrilateral, generating a planar coordinate system based on the bridge deck gray scale processing image, obtaining the coordinates of each vertex of the quadrilateral of the bridge deck part of the assembled bridge; Determine the correction target planar rectangular data of the bridge deck of the assembled bridge; Select the coordinates of each vertex of the quadrilateral, and transform the coordinates of each vertex of the quadrilateral to match the correction target planar rectangular data; Rectangular transformation is performed on the quadrilateral of the bridge deck part of the assembled bridge based on the coordinates of each vertex of the matched quadrilateral; Complete perspective adjustment and output bridge deck adjustment image.

5. The big data based prefabricated bridge deck load safety monitoring system according to claim 1, wherein: The bridge deck simulation unit comprises: A bridge deck generation module, configured to: generate a bridge deck model based on the bridge deck combined image, and perform timing update on the bridge deck model based on the bridge deck combined image at different collection times; A region division module, configured to: divide the bridge deck model into monitoring regions, the monitoring regions being rectangular monitoring regions of the same shape and size, and label different monitoring regions.

6. The big data based prefabricated bridge deck load safety monitoring system according to claim 1, wherein: The safety monitoring unit comprises: A bridge deck identification module, configured to: identify each monitoring region of the bridge deck model, identify vehicles in each monitoring region at the same collection time, and identify the bridge deck condition, the bridge deck condition including cracks, pits and foreign objects; A safety rating module, configured to: perform safety rating analysis on each monitoring region of the bridge deck model based on the identification result of the bridge deck identification module, count all vehicles on the assembled bridge at the same collection time based on the identification result, and predict the load bearing, and issue an alarm when the predicted load bearing of the assembled bridge exceeds the load safety threshold; A region alarm module, configured to: issue a region alarm when cracks, pits or foreign objects are identified in each monitoring region.

7. The big data based prefabricated bridge deck load safety monitoring system according to claim 1, wherein: The data collection device is an image collection camera, which is arranged above the high altitude on both sides of the bridge deck of the assembled bridge, and is arranged equidistantly between each data collection device. The data collection device is numbered based on the position and sequence of each data collection device, and the bridge deck image data collected by each data collection device is marked with corresponding data according to the point number.

8. The big data based prefabricated bridge deck load safety monitoring system according to claim 1, wherein, In the second network reading unit, the credibility of the standard to-be-interacted information is determined, including: A matching subunit, configured to: obtain an interaction information management library, and input the standard to-be-interacted information into the interaction information management library for matching; determine, based on the matching result, first sub to-be-interacted information in the standard to-be-interacted information that matches the corresponding historical interaction information in the interaction information management library, and second sub to-be-interacted information in the standard to-be-interacted information that does not match the corresponding standard interaction information in the interaction information management library; A calculation subunit, configured to: obtain a first data amount of the first sub to-be-interacted information, and simultaneously, obtain a second data amount of the second sub to-be-interacted information; calculate the credibility of the standard to-be-interacted information based on the first data amount and the second data amount; wherein φ represents the credibility value of the standard to-be-interacted information; M represents the total data amount of the standard to-be-interacted information; m1 represents the first data amount; and m2 represents the second data amount.

9. A monitoring method of the big data-based fabricated bridge deck load safety monitoring system according to any one of claims 1-8, characterized in that: The method comprises the following steps: Step 1: The data collection device collects the bridge deck image data of the assembled bridge; Step two: the big data grabbing unit grabs the bridge deck image data and carries out pretreatment, and marks and sorts based on the data collection time and the point number of the data collection equipment; Step three: the image processing unit processes the bridge deck image data to obtain a bridge deck grayscale processing image, adjusts the perspective of the bridge deck grayscale processing image, and fuses and combines to generate a bridge deck combined image; Step four: the bridge deck simulation unit generates a bridge deck model and divides the monitoring area, and the safety monitoring unit identifies, monitors and alarms inside each monitoring area of the bridge deck model.

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