CN-121977697-A - Bridge temperature inversion method and system based on unmanned aerial vehicle thermal infrared remote sensing

CN121977697ACN 121977697 ACN121977697 ACN 121977697ACN-121977697-A

Abstract

The invention relates to the technical field of remote sensing monitoring, in particular to a bridge building temperature inversion method and system based on unmanned aerial vehicle thermal infrared remote sensing. The method comprises the steps of determining an adaptive unmanned aerial vehicle platform according to structural parameters of a bridge under construction, geographical conditions of a monitoring area and operation endurance requirements, carrying a color CCD camera and a common digital camera to form a double-camera load, and completing synchronous calibration of an unmanned aerial vehicle inertia measurement unit, a global positioning system module and a double-camera, wherein through complementation of functions and characteristics of the double-camera, system errors of radiation brightness detection are reduced from a data source, the color CCD camera provides stable basic radiation data, the common digital camera supplements effective signals under extreme conditions, space-time coordinates are consistent through synchronous calibration, radiation brightness acquisition deviation caused by self performance limitation of a single camera is avoided, the stability of radiation brightness detection is improved by more than 30%, and more reliable basic data is provided for subsequent temperature inversion.

Inventors

ZHANG CHUANYI
ZHANG JINLONG
JING YONGJUN
LI HONG
WANG XINDE
WANG YINGHAO
ZHANG CHI
ZHANG YUE
HUANG QINGHUA
Liu Jiangsen
XU PENG

Assignees

中铁十局集团第一工程有限公司
内蒙古科技大学
中铁十局集团有限公司

Dates

Publication Date: 20260505
Application Date: 20260203

Claims (10)

1. The temperature inversion method for the bridge under construction based on the unmanned aerial vehicle thermal infrared remote sensing is characterized by comprising the steps of determining an adaptive unmanned aerial vehicle platform according to structural parameters of the bridge under construction, geographical conditions of a monitored area and operation endurance requirements, carrying a color CCD camera and a common digital camera to form a double-camera load, and completing synchronous calibration of an unmanned aerial vehicle inertial measurement unit, a global positioning system module and the double-camera; planning and monitoring a route according to a route design principle of the whole structure of the coverage bridge, acquiring remote sensing data under meteorological and illumination conditions meeting the data acquisition quality requirements, and synchronously recording atmospheric environment parameters, unmanned aerial vehicle running states and camera working parameters; sequentially carrying out radiation correction, geometric correction and atmospheric scattering correction on the acquired dual-camera original data to obtain preprocessed standardized image data; Based on the Planckian radiation law and the dual-camera response characteristic, a temperature-radiation brightness conversion model is constructed, and the initial inversion temperature is subjected to multi-parameter joint correction by combining the atmospheric parameters and bridge material emissivity parameters calculated in real time; and acquiring temperature data of the verification point through actually measured temperature acquisition equipment, and verifying the corrected inversion temperature to generate a bridge construction ground surface temperature product containing temperature identification information, a coordinate system and an error range.
2. The bridge temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing according to claim 1 is characterized in that an adaptive unmanned aerial vehicle platform is determined according to structural parameters of a bridge, geographical conditions of a monitoring area and operation endurance requirements, a color CCD camera and a common digital camera are carried to form a double-camera load, synchronous calibration of an unmanned aerial vehicle inertial measurement unit, a global positioning system module and a double-camera is completed, specifically, the unmanned aerial vehicle platform with corresponding load capacity, hovering precision and wind resistance is selected according to bridge span size and monitoring area topography complexity, the unmanned aerial vehicle platform comprises a multi-rotor unmanned aerial vehicle or a vertical take-off and landing fixed-wing unmanned aerial vehicle, the color CCD camera meeting requirements of image resolution, spectrum response range and data output format and the common digital camera with original image format output, sensitivity adjustment range and shutter speed adjustment capacity are selected to form a double-camera load, and the unmanned aerial vehicle flight control system is used for carrying out time synchronous calibration on attitude data of the inertial measurement unit, position data of the global positioning system and image acquisition triggering signals of the double-camera, and corresponding coordinate images are guaranteed to be carried and controlled within a preset time-space-time synchronization error.
3. The bridge temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing is characterized in that a monitoring route is planned according to a route design principle of a full structure of a coverage bridge, remote sensing data are collected under meteorological and illumination conditions meeting data collection quality requirements, atmospheric environment parameters and unmanned aerial vehicle operation states and camera working parameters are synchronously recorded, specifically, the method comprises the steps of determining a route height according to the bridge height and a double-camera field angle to meet ground resolution requirements, planning a main monitoring route, setting reasonable route overlapping degree, planning an auxiliary checking route for subsequent data consistency verification, selecting a period with stable illumination conditions and small airflow interference to start data collection, recording atmospheric environment parameters such as atmospheric temperature, relative humidity and air pressure through meteorological monitoring equipment before collection, periodically acquiring and storing attitude data of an unmanned aerial vehicle and working parameters of a camera in the collection process, controlling the auxiliary checking route to keep consistent with the collection conditions of the main monitoring route, guaranteeing comparability of auxiliary data and the main data, and providing a foundation for subsequent data verification.
4. The bridge temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing is characterized by sequentially carrying out radiation correction, geometric correction and atmospheric scattering correction on collected double-camera original data to obtain preprocessed standardized image data, and concretely comprises the steps of carrying out radiation correction on the double-camera original data by adopting a dark field correction algorithm, eliminating the influence of sensor dark current noise on an image gray value, establishing an association relation between the image gray value and actual reflectivity through a standard reference, solving a correction coefficient to complete response consistency correction, carrying out geometric correction on an image by adopting a polynomial transformation model by taking high-precision position data acquired by an unmanned aerial vehicle global positioning system as a control point, eliminating spatial position deviation, carrying out atmospheric scattering correction on the corrected image by adopting an atmospheric scattering correction model, wherein atmospheric path radiation is acquired through image feature region statistics, and atmospheric transmittance is calculated through an atmospheric radiation transmission model.
5. The bridge construction temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing is characterized by further comprising a multi-source image registration step after geometrically correcting images by using high-precision position data acquired by an unmanned aerial vehicle global positioning system as control points and using a polynomial transformation model, and specifically comprises the steps of extracting image feature points from a common digital camera image by using a feature point extraction algorithm and calculating feature vectors of the feature points by using a geometrically corrected color CCD image as a reference image, screening the extracted feature points by using a feature point matching screening algorithm, removing mismatching points to reserve feature point pairs with high reliability, and performing coordinate adjustment on the common digital camera image by using a coordinate transformation model based on the screened feature point pairs, so that registration errors of the dual-camera image are controlled within a preset pixel range, and aligned dual-camera standardized image data are obtained.
6. The bridge construction temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing is characterized by comprising the steps of building a temperature-radiation brightness conversion model based on Planckian radiation law and double camera response characteristics, building a bridge surface radiation brightness and temperature association formula according to Planckian radiation law, wherein the formula comprises surface emissivity and radiation constant parameters, building a linear association relation between a camera response value and surface radiation brightness by combining spectral response characteristics of a double camera, wherein the relation comprises camera response coefficient, a spectral response function and dark current response value parameters, selecting typical areas of a plurality of known materials on a bridge, obtaining actual measurement temperatures of the areas through high-precision temperature measurement equipment, synchronously reading average response values of the corresponding areas of the double cameras, building the temperature-radiation brightness conversion model by adopting a regression analysis algorithm, and ensuring that the fitting goodness of the model meets preset requirements.
7. The bridge temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing is characterized by combining real-time calculated atmospheric parameters with bridge material emissivity parameters, and specifically comprises the steps of calculating the atmospheric equivalent temperature by adopting an empirical formula based on real-time acquired atmospheric environment parameters, constructing the empirical formula according to the association relation between the atmospheric temperature and relative humidity, inputting geographic information and atmospheric mode parameters of a monitoring area into an atmospheric radiation transmission model, calculating the atmospheric transmittance of a thermal infrared band, dividing the bridge area into different material types including bridge main structure materials and background area materials by adopting a clustering analysis algorithm through color characteristics of a color CCD image, and assigning corresponding emissivity values for the different material types by referring to standard spectral library data and combining laboratory measurement results, wherein the assignment error of the emissivity is controlled within a preset range.
8. The bridge temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing is characterized by comprising the steps of substituting a preprocessed dual-camera response value into a temperature-radiation brightness conversion model, calculating to obtain an initial inversion temperature, introducing an atmospheric equivalent temperature and an atmospheric transmittance parameter, carrying out atmospheric parameter correction on the initial inversion temperature by adopting an atmospheric correction formula, wherein the correction formula comprises a correlation term of atmospheric temperature difference and transmittance, carrying out further correction on the temperature after the atmospheric parameter correction by adopting an emissivity correction formula according to emissivity values of different material types, and obtaining a final inversion temperature by adopting an emissivity correction formula.
9. The bridge construction temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing is characterized in that verification point temperature data are obtained through actual measurement temperature acquisition equipment, accuracy verification is conducted on corrected inversion temperatures, bridge construction surface temperature products comprising temperature identification information, a coordinate system and an error range are generated, the bridge construction surface temperature products comprise a plurality of evenly distributed temperature verification points which cover different material areas and key structure parts of a bridge, actual measurement temperatures of the verification points are obtained through the actual measurement temperature acquisition equipment, error indexes of final inversion temperatures and actual measurement temperatures are calculated, the error indexes comprise absolute errors and relative errors, emissivity assignment or formula parameter correction is optimized again if the error indexes exceed a preset threshold value, the final inversion temperature data and geometrically corrected images are subjected to superposition processing, a temperature field distribution map is generated, temperature identification information, a standard coordinate system, data acquisition time and an error range are marked, and image formats supporting geographic information analysis and data formats comprising a coordinate-temperature corresponding relation are derived, and bridge construction surface temperature products are formed.
10. Bridge temperature inversion system under construction based on unmanned aerial vehicle thermal infrared remote sensing, characterized by comprising: The platform load module is configured to determine an adaptive unmanned aerial vehicle platform according to structural parameters of a bridge under construction, geographical conditions of a monitoring area and operation endurance requirements, carry a color CCD camera and a common digital camera to form a double-camera load, and complete synchronous calibration of an unmanned aerial vehicle inertial measurement unit, a global positioning system module and a double-camera; The parameter recording module is configured to plan a monitoring route according to a route design principle of the whole structure of the coverage bridge, collect remote sensing data under meteorological and illumination conditions meeting the data collection quality requirements, and synchronously record atmospheric environment parameters, unmanned aerial vehicle running states and camera working parameters; the standard module is configured to sequentially perform radiation correction, geometric correction and atmospheric scattering correction on the acquired dual-camera original data to obtain preprocessed standardized image data; The correction module is configured to construct a temperature-radiation brightness conversion model based on the Planckian radiation law and the dual-camera response characteristic, and perform multi-parameter joint correction on the initial inversion temperature by combining the atmospheric parameter and the bridge material emissivity parameter calculated in real time; the inversion module is configured to acquire temperature data of the verification point through the actually measured temperature acquisition equipment, verify the corrected inversion temperature, and generate a bridge construction surface temperature product containing temperature identification information, a coordinate system and an error range.

Description

Bridge temperature inversion method and system based on unmanned aerial vehicle thermal infrared remote sensing Technical Field The invention relates to the technical field of remote sensing monitoring, in particular to a bridge building temperature inversion method and system based on unmanned aerial vehicle thermal infrared remote sensing. Background The current bridge temperature monitoring and inversion technology mainly comprises two types, namely a traditional discrete point type monitoring technology, a temperature inversion technology based on a remote sensing technology and a satellite thermal infrared remote sensing and unmanned aerial vehicle thermal infrared remote sensing inversion method, wherein the two types are the traditional discrete point type monitoring technology for acquiring local point position temperature data through arrangement of temperature sensors. The unmanned aerial vehicle thermal infrared remote sensing gradually becomes the main stream technical direction due to wide coverage range and high space-time resolution, and is often provided with WIRISProSc equal-width wave band thermal infrared imagers, and inversion is realized through conversion of radiation brightness and temperature by combining theory such as Planck's law, style-Boltzmann law and the like. Defects of the prior art The monitoring mode lacks space continuity, namely the traditional point type monitoring can only acquire isolated point position data, cannot capture the space distribution heterogeneity of the bridge full-structure temperature field, is difficult to reflect the temperature difference of different parts (such as concrete beam sections and steel structure nodes), and is easy to cause misjudgment of construction decisions. The suitability of the broadband sensor is insufficient, the logic of the existing inversion algorithm for multi-edge use of the broadband satellite sensor is not optimized for the broadband thermal imager. The full wave band is regarded as the whole calculated temperature by directly adopting the Style-Boltzmann law, the radiation difference in the wide wave band is ignored, and a significant system error is introduced. The key influencing factor correction is imperfect, interference of the characteristics of the atmosphere and the ground is not fully considered, the atmospheric temperature and humidity data are replaced by historical exploring data or near-surface data, space-time difference exists between the atmospheric temperature and humidity data and actual atmospheric conditions of the flight time and the observation height of the unmanned aerial vehicle, and meanwhile emissivity difference of different materials of the bridge is not corrected by the system, so that inversion errors are further aggravated. The model simplification introduces inherent errors, namely, a part of algorithm simplifies the Planckian function through the Taylor expansion, and the radiation and the temperature are in linear relation, but the radiation and the temperature are not in a strong linear relation in reality, and the inversion precision is directly reduced through the simplification treatment. The data processing and calibration has a short board, the processing of high-precision original data such as 14-bit RAW is high in requirement on hardware computing capacity, the gray-temperature mapping relation is complex, the existing calibration flow is complex, temperature deviation is easily caused by improper parameter setting, and meanwhile, the standardized data preprocessing flow is lacking, so that the influence of noise and space deviation on the result is large. The repeatability of the technical process is poor, the existing method does not form a complete standardized system from data acquisition, parameter correction to result verification, the operation is complicated, the influence of environmental conditions is large, and the business popularization and application are difficult to realize. Disclosure of Invention In order to solve the problems, the invention provides a bridge temperature inversion method and system based on unmanned aerial vehicle thermal infrared remote sensing. In a first aspect, the invention provides a bridge temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing, which adopts the following technical scheme: A bridge temperature inversion method based on unmanned aerial vehicle thermal infrared remote sensing comprises the following steps: Determining an adaptive unmanned aerial vehicle platform according to structural parameters of a bridge under construction, geographical conditions of a monitored area and operation endurance requirements, carrying a color CCD camera and a common digital camera to form a double-camera load, and completing synchronous calibration of an unmanned aerial vehicle inertia measurement unit, a global positioning system module and a double-camera; planning and monitoring a route according to