[0040]Next, the technical solutions in the embodiments of the present invention will be apparent from the embodiment of the present invention, and it is clearly described, and it is understood that the described embodiments are merely embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, there are all other embodiments obtained without making creative labor without making creative labor premises.
[0041]Referfigure 1 As shown, the security real-time monitoring method of the assembly bridge over the cloud computing and image analysis, including the following steps:
[0042]S1: Detect environmental parameters in each detection sub-region in real time, and compare with standard environment parameters;
[0043]S2: Real-time detection of telescopic sewing variables in each detection sub-region and compares the standard telescopic sewing variables;
[0044]S3: Get the noise decibel in each detection sub-region in real time, and determine the corresponding noise decibel level and noise decibel influence coefficient;
[0045]S4: The data obtained according to S1, S2 and S3 is statistically divisored seam quality safety coefficient, and determine the mass safety level of the telescopic seam to be displayed;
[0046]SeeFigure IIAs shown, the security real-time monitoring method of the assembled bridge-based bridge-based bridge-based assembly bridge-based installation bridge-based bridge-based security real-time monitoring system based on cloud computing and image analysis, including regional division modules, environmental parameter detection modules , Environmental parameter pretreatment module, image acquisition module, image pre-processing module, telescopic sewing variable acquisition module, noise decision statistics module, database, modeling analysis server, management server, and display terminal;
[0047]The image acquisition module is connected to the area dividing module and the image pre-processing module, and the telescopic sewing variable acquisition module is connected to the image pre-processing module and the modeling analysis server, respectively, and the noise decision statistics module is connected to the modeling analysis server and database, respectively. Environmental parameter pre-processing modules are connected to the environmental parameter detection module and modeling analysis server, and the management server is connected to the database, modeling analytics, and display terminals, database and modeling analysis server;
[0048]The region division module is used to divide each of the extension seams of the assembled bridge surface. According to the order from the bridgehead to the end of the bridge, each of the extension seams of the assembled bridge bridge surface is the same detection sub-region as each area, each The detection sub-region corresponds to each of the extended sections, and the divided detection sub-regions are numbered in the proximity of the bridges in each detection sub-region, and mark 1, 2, ..., i , ... g;
[0049]The environmental parameter detecting module is configured to detect real-time environmental parameters in each detection sub-region, including a temperature detecting unit and a humidity detecting unit, a temperature detecting unit is a temperature sensor, mounted in each detection sub-region for detecting a telescopic seam. The temperature, the humidity detecting unit is a humidity sensor, mounted in the respective detection sub-regions, used to detect humidity in the telescopic seam, and transmit temperature and humidity in the environmental parameters in the detected subregions to environmental parameters Processing module;
[0050]The environment parameter pre-processing module receives temperature and humidity in the environmental parameters in each detection sub-region transmitted by the environment parameter detecting module, and divides the temperature and humidity in the environmental parameters in the respective detection sub-regions of the received individual segment According to the set time interval value, the divided multiple detection time period parameters are numbered in the order of the detection time, and it is marked as 1, 2, ..., t, ..., u, constitutes daily time. Segment environment parameter set AIW (aIW 1, AIW 2, ..., aIW T, ..., AIW u), AIW T is represented as the value corresponding to the first environment parameters within the T 's Issuus in the first detection period, T is represented as the detection period, W is indicated as environmental parameters, W = P1, P2, P1, P2 respectively For the temperature and humidity in each detection sub-region, the environmental parameter pre-processing module sends a set of time periods in the daily time to the modeling analysis server;
[0051]The image acquisition module includes a high-definition camera for image acquisition of the extension seam in the respective detect sub-regions, and transmits the telescopic seam image in the acquired individual detection sub-regions to the image pre-processing module;
[0052]The image pre-processing module receives the telescopic seam image in the respective detecting sub-regions transmitted by the image acquisition module, and the telescopic seam image segmentation in each of the received respective detection sub-regions, the stretching segment feature area obtained by splicing the image, and removes the Background images outside the region, the retained telescopic seam feature area image varies by geometry and does not have a degree of expiration of the seam image, and performs grayscale transform and image enhancement processing, resulting in a processed telescopic. Target image, and send the telescopic seam target image of each of the various detection sub-regions to the telescopic seam variable acquisition module;
[0053]The telescopic slit variable acquisition module receives the telescopic seam target image of the respective detection sub-regions after the processing transmitted by the image pretreatment module, and the telescopic variable acquisition of the telescopic seam target image of the respective detection sub-regions after the received process. And according to the detection time period, correspond to the detection time period of the environmental parameters in the detection sub-region, constitute a set of time period telescopic variables in the daily period Bt(Bt1, bt2 ..., bti, ..., btg), Bti is expressed as the debris variable variable seam in the tetrated seam in the twenserate period in the i-I detect sub-region, and sends a set of time period telescopic sewing variables to the modeling analysis server;
[0054]The noise division statistics module includes a forage apparatus for detecting noise decibels in each detection sub-region in real time, and divided according to the detection time period, corresponding to the detection time period of the environmental parameters in each detection sub-region, will detect The noise decibel in each detection period in each detection sub-region is compared to the noise decibel range corresponding to the noise decibels stored in the database, extracts noise decibel corresponding to the noise decibel of the noise decibels of each detection period in each detection sub-region. The noise decibel grade of each test time period in each test subregion is sent to the modeling analysis server;
[0055]This embodiment is compared with the standard environmental parameters, telescopic sewing variables in real time, and provides a reliable pre-stage pre-statistical stretch seam. Data preparation and reference basis, with high authenticity and high data accuracy and accuracy;
[0056]The database is used to store the standard temperature and humidity corresponding to each of the detection time periods set in each season, store each noise decision level corresponding to the noise decibel, the upper limit value of the noise decibel range corresponding to the first-order noise decibel level is less than The lower limit value of the noise decibel range corresponding to the secondary noise decibel, the upper limit value of the noise decibel range corresponding to the secondary noise decibel level is smaller than the lower limit value of the noise decibration range corresponding to the three-level noise decibel, and the noise decibel for each noise decision Impact factor, the size of the noise decibel in which the different noise decibels corresponding to the different noise decibels Store standard telescopic sewing variables, storing the range of telescopic seam quality safety coefficients corresponding to each extended seam mass safety level, the upper limit value of the telescopic seam quality safety coefficient of the primary telescopic seam quality is less than the secondary telescopic seam quality safety The lower limit value of the level corresponding to the scale of the telescopic seam quality, the upper limit value of the secondary telescopic seam quality safety coefficient is less than the upper limit value of the three-stage telescopic seam quality safety level corresponding to the lower limit value ;
[0057]The model analyzer server receives the set of time period environment parameters sent by the environment parameter pre-processing module, and the environmental parameters corresponding to each detection time period each detection subregion and the detection time period set in the current season Compared with the standard temperature and humidity, constitute a time period environmental parameter comparison collection A 'IW (a 'IW 1, a 'IW 2, ..., a 'IW T, ..., A 'IW u), a 'IW TI represents the difference between the standard values corresponding to the first environment parameters corresponding to the first detection time period within the first detection period of the first detection subregion. value;
[0058]Modeling Analysis Server Receives the set of time period telescopic sewing variables transmitted by the telescopic sewing variable to acquire the module, and the standard telescopic variables corresponding to each detection time period in each detection sub-region and the standard telescopic seam stored in the database Comparison of variables, constituting time period telescopic slit variables Comparative set B 't(b 't1, b 't2 ..., b 'tI, ..., b 'tg), b 'ti is a difference between the degradation of the stretchable seam and the standard telescopic slit variable in the first detection period of the I detection sub-region;
[0059]The Model Analysis Server receives the noise decibel level within the respective detection periods transmitted by the noise decision statistics module, and obtains the noise decibel impact coefficient corresponding to each noise decision level stored in the database, and then obtains each detection sub- The noise decibel influence coefficient corresponding to each test time period in the region, constitutes the time period noise decibel influence coefficient collection Ct(ct1, ct2, ..., cti, ..., ctg), cti is expressed as the noise decibel influence coefficient of the tip detection time period in the i-I detection subregion;
[0060]Modeling Analysis Server According to the comparison of time period environmental parameters, the time period telescopic variable contrast the set and time period noise decibel influence coefficient, with statistical telescopic seam quality safety factor, the calculation formula of the stretchable seam quality safety factor is λIT Represents the telescopic seam quality safety factor in the Tem Try Temperature during the i-thicon area, Ai'wTI represents the difference between the standard values corresponding to the first environment parameters corresponding to the first detection time period within the first detection period of the first detection subregion. Value, AIW T is expressed as the value corresponding to the first environment parameters within the tip of the I detection period, B.t'1 is a difference between the degradation of the telescopic seam and the standard telescopic sewing variable in the twenserate dimension variable, B.ti is expressed as the degradation of the telescopic seam in the tetra detection time period in the i-I detection sub-region, cti is expressed as the noise decibel influence coefficient of the tip detection time period in the i-I detection sub-region, and E is represented as natural number, and transmits the telescopic seam quality safety factor to the management server;
[0061]The management server receives the telescopic seam quality safety factor sent by the modeling analysis server, and compares the statistical telescopic seam quality safety coefficient to the scope of the telescopic seam quality safety coefficient corresponding to each telescopic seam quality safety level stored in the database. The mass safety coefficient of the telescopic seams corresponds to the mass safety coefficient of the telescopic seam mass safety level, and the quality and safety level of the telescopic seam is primary. If the telescopic seam quality safety coefficient is in the secondary telescopic seam quality safety level Within the scope of the stretchable seam quality, the mass safety level of the telescopic seam is second. If the telescopic seam quality safety coefficient is within the scope of the telescopic seam mass safety coefficient, the telescopic The quality safety level of the seam is three, manage the server and sends the telescopic seam quality safety factor of each detection sub-region and the corresponding quality and safety level to the display terminal;
[0062]The display terminal receives the telescopic seam mass safety factor of each detection sub-region transmitted by the management server, and the corresponding quality security level is displayed, and it is displayed by displaying the quality safety coefficients of different time segments in each detection sub-region. Provides the expansion of the bridge to real-time data, which is convenient for technical staff to take different measures according to the bridge expansion, and greatly improve the safety of the bridge.
[0063]A monitoring management cloud platform, the monitoring management cloud platform including a processor, a machine readable storage medium, and a network interface, the machine readable storage medium, the network interface, and the processor connected between the bus system. The network interface is used to monitor the terminal communication connection with at least one cloud computing and image analysis, and the machine readable storage medium is used to store programs, instructions, or code, the processor for execution. The program, instructions, or code in the machine readable storage medium is performed to perform a safe real-time monitoring method of the assembled bridge-based bridge over the present invention.
[0064]The present invention compares the environmental parameters, telescopic sewing variables, and noise decibels in each detection sub-region, and compares the standard environment parameters, and the telescopic sewing variable, and the noise decibels corresponding to each detection sub-region and the noise decibel are affected. The coefficients, with statistical seam quality safety factor of different time periods of each detection sub-region and corresponding quality and safety level, and have the characteristics of high real-time and high reliability, and greatly reduce labor costs, avoiding because of human factors The problem of large detection data errors, providing powerful technical support for bridge security applications.
[0065]The above is merely examples and descriptions of the structure of the present invention, and those skilled in the art will do a wide variety of modifications or supplements or use in a similar manner as long as they do not deviate from the structure of the invention or Beyond the scope defined by the claims, it should belong to the scope of the present invention.
