CN114993249B - Road surface roadbed settlement monitoring analysis early warning system based on internet of things technology - Google Patents
Road surface roadbed settlement monitoring analysis early warning system based on internet of things technology Download PDFInfo
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Abstract
The invention discloses a road subgrade settlement monitoring, analyzing and early warning system based on the internet of things technology, which comprises a monitoring area dividing module, a monitoring area structural layer dividing module, a monitoring terminal layout module, a monitoring area construction quality analyzing module, a monitoring area road bearing capacity analyzing module, a groundwater monitoring and analyzing module, an information storage library, a subgrade settlement risk analyzing module, a subgrade settlement early warning analyzing module and a settlement early warning prompt executing module. The parameters required by the road subgrade settlement analysis are automatically acquired and analyzed through the monitoring terminal, the weight sensor and the intelligent high-definition camera, so that not only is the waste of a large amount of manpower resources and material resources avoided, but also the accuracy of measured data is improved, the reliability and the scientific basis of the analysis result are greatly improved, the unilateral performance of the existing road subgrade analysis result is made up, not only is the effective data support provided for the analysis result, but also the rationality and the referenceability of the analysis result are improved.
Description
Technical Field
The invention relates to the technical field of road subgrade settlement monitoring, in particular to a road subgrade settlement monitoring, analyzing and early warning system based on the internet of things technology.
Background
Along with the rapid development of urban road construction, more and more roads are striven into the field of view of the masses like bamboo shoots after rain, the problem of road subgrade settlement of each road is followed, and the current road subgrade settlement analysis mainly relies on manual measurement analysis on the road subgrade, so the current road subgrade settlement analysis has the following defects:
for settlement parameter collection, the current road bed settlement analysis not only enables the settlement parameter collection to be carried out manually, but also enables the road bed settlement analysis to be carried out manually, so that a great amount of manpower resources and material resources are consumed, meanwhile, the settlement parameter collection is possibly inaccurate, and further errors are caused in the road bed settlement analysis, and the road bed settlement analysis result cannot be accurately, effectively and scientifically mastered.
For the monitoring mode and the monitoring dimension, on one hand, the monitoring mode in the current pavement subgrade settlement analysis only carries out integral analysis on the pavement subgrade, so that settlement analysis on the local structural layers is omitted, pavement subgrade settlement conditions corresponding to the local structural layers cannot be known, and the situation that the settlement of the local structural layers cannot be known possibly occurs; on the other hand, the monitoring dimension in the current road subgrade settlement analysis is single, the road subgrade settlement condition is not analyzed from multiple aspects, so that the singleness and one-sided performance of an analysis result are caused, and meanwhile, powerful data support cannot be provided for the subsequent road subgrade settlement analysis.
For early warning prompt, no early warning prompt terminal is arranged in the current road subgrade settlement analysis, so that the settlement condition of the road subgrade cannot be known in time, and the timeliness and effectiveness of the road subgrade settlement early warning are affected.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides a road subgrade settlement monitoring, analyzing and early warning system based on the technology of the Internet of things, which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme:
road surface road bed subsides monitoring analysis early warning system based on internet of things, include:
the monitoring area dividing module is used for dividing the road surface area to be monitored on the road in a grid mode to obtain each road surface subarea to be monitored, and numbering the road surface subareas to be monitored according to a preset sequence to be 1, 2.
The monitoring area structural layer dividing module is used for acquiring structural layers corresponding to the pavement subareas to be monitored through the X-ray detector, and numbering the structural layers into 1,2 according to a preset sequence;
the monitoring terminal layout module is used for carrying out monitoring terminal layout on each structural layer in each pavement subarea to be monitored, and meanwhile, weight sensors and intelligent high-definition cameras are arranged at the positions of each pavement subarea to be monitored;
the construction quality analysis module of the monitoring area is used for analyzing construction quality coefficients corresponding to each structural layer in each pavement subarea to be monitored;
the monitoring area pavement bearing capacity analysis module is used for analyzing dangerous bearing coefficients of all pavement subareas to be monitored by the weight sensor and the intelligent high-definition camera;
the underground water monitoring and analyzing module is used for analyzing the underground water danger proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored;
the information storage library is used for storing standard compactness, standard flatness and standard thickness corresponding to each structural layer, storing dangerous influence factors corresponding to the groundwater level distance in each structural layer, storing permitted subgrade settlement dangerous coefficients corresponding to each structural layer and storing permitted dangerous bearing coefficients;
the roadbed settlement risk analysis module is used for analyzing settlement risk coefficients corresponding to the structural layers in the pavement subareas to be monitored by integrating construction quality coefficients corresponding to the structural layers in the pavement subareas to be monitored and underground water risk proportion coefficients;
the roadbed settlement early warning analysis module is used for performing roadbed settlement early warning analysis on roadbed settlement dangerous coefficients corresponding to each structural layer in each to-be-monitored pavement subarea, and performing dangerous bearing early warning analysis on dangerous bearing coefficients of each to-be-monitored pavement subarea, thereby obtaining key parameters;
and the settlement early warning prompt execution module is used for carrying out corresponding settlement early warning voice prompt based on the numbers corresponding to the key road surface subregions and the key structure layers in the key parameters.
Specifically, the structure layer corresponding to each pavement subarea to be monitored is obtained through the X-ray detector, and the specific obtaining steps are as follows:
transmitting X-rays to each pavement subarea to be monitored through an X-ray detector, and enabling the transmitted rays to penetrate through each pavement subarea to be monitored and be subjected to imaging record through a ray film so as to obtain an internal structure film of each pavement subarea to be monitored;
the obtained radiographic film is placed into a darkroom for processing, and then the inner structure radiographic film of each pavement subarea to be monitored is obtained;
according to the difference of gray values displayed by the structural layers in the ray films of the internal structures of the sub-areas of the road surfaces to be monitored, obtaining the corresponding structural layers of the sub-areas of the road surfaces to be monitored;
and carrying out distribution area contour recognition on each structural layer according to the distribution area corresponding to each structural layer in each pavement subarea to be monitored, wherein the recognized distribution area contour of each structural layer in each pavement subarea to be monitored is used as a boundary between the structural layers, and the thickness corresponding to each structural layer in each pavement subarea to be monitored is obtained according to the distribution area contour of each structural layer in each pavement subarea to be monitored.
Specifically, the monitoring terminal comprises a nuclear densimeter and underground water monitoring equipment, wherein the underground water monitoring equipment comprises a water level automatic monitor, a water quality monitor and an osmometer.
Specifically, the construction quality coefficients corresponding to each structural layer in each pavement sub-area to be monitored are analyzed, and the specific analysis is as follows:
obtaining the compactness corresponding to each structural layer in each pavement subarea to be monitored through a nuclear densimeter;
uniformly distributing detection points in each structural layer in each pavement subarea to be monitored, further obtaining the corresponding vertical distance between each detection point in each structural layer in each pavement subarea to be monitored and the pavement area to be monitored, and screening out the maximum vertical distance and the minimum vertical distance from the vertical distances;
based on the maximum vertical distance and the minimum vertical distance corresponding to each structural layer in each pavement subarea to be monitored, calculating the flatness corresponding to each structural layer in each pavement subarea to be monitored, wherein a specific calculation formula is as follows Expressed as the flatness corresponding to the jth structural layer in the ith pavement subregion, +.>And->Expressed as maximum vertical distance and minimum vertical distance, respectively, corresponding to the jth structural layer in the ith pavement subregion,/->Representing the average vertical distance corresponding to the j structural layer in the i-th pavement subarea to be monitored;
comprehensively analyzing the compactness, flatness and thickness corresponding to each structural layer in each pavement subarea to be monitored to obtain each pavement subarea to be monitoredThe construction quality coefficient corresponding to each structural layer is specifically calculated as follows Expressed as the construction quality coefficient corresponding to the j-th structural layer in the i-th pavement area to be monitored,/and>respectively expressed as compactness and thickness ys 'corresponding to the jth structural layer in the ith pavement area to be monitored' j 、pz′ j 、hd j ' is respectively expressed as standard compactness, standard flatness and standard thickness corresponding to the jth structural layer, and a1, a2 and a3 are respectively expressed as influence factors corresponding to the compactness, flatness and thickness.
Specifically, the dangerous bearing coefficient of each pavement subarea to be monitored is analyzed, and the specific analysis is as follows:
the actual bearing weight of each pavement subarea to be monitored is monitored through a weight sensor and is marked as m i ，m i The actual bearing weight corresponding to the ith pavement subarea to be monitored is represented;
the actual bearing area of each pavement subarea to be monitored is obtained through an intelligent high-definition camera, and the actual bearing area is marked as s i ，s i The actual bearing area corresponding to the ith pavement subarea to be monitored is represented;
the actual bearing weight and the actual bearing area corresponding to each pavement subarea to be monitored are synthesized to obtain the dangerous bearing coefficient corresponding to each pavement subarea to be monitored, wherein the specific calculation formula is as follows Dangerous bearing system corresponding to ith pavement subarea to be monitoredThe number m' is expressed as the core load weight corresponding to the road surface area to be monitored on the highway, s i ' is expressed as the area corresponding to the ith pavement subarea to be monitored, and b1 and b2 are respectively expressed as the bearing weight and the influence factors corresponding to the bearing area.
Specifically, the analysis is performed on the corresponding groundwater danger ratio coefficient of each structural layer in each pavement subarea to be monitored, and the specific analysis is as follows:
the water quality parameters and the osmotic pressure of the underground water are respectively collected by a water quality monitor and an osmometer, wherein the water quality parameters comprise the temperature of the underground water and the pH value of the underground water;
the groundwater temperature, the groundwater pH value and the osmotic pressure are synthesized to obtain the groundwater water body influence proportionality coefficient, and the specific calculation formula is as followsKappa is expressed as an influence proportionality coefficient of groundwater water body, sw, sj and sy are respectively expressed as groundwater temperature, groundwater pH value and osmotic pressure, and sw ', sj ' and sy ' are respectively expressed as reference groundwater temperature, reference groundwater pH value and reference osmotic pressure;
the automatic water level monitor collects the groundwater level of each pavement subarea to be monitored, and simultaneously obtains the vertical distance between the groundwater level of each pavement subarea to be monitored and each structural layer, marks the vertical distance as the groundwater level distance, and further numbers the groundwater level distance as the groundwater level distance The water level distance of the groundwater corresponding to the j-th structural layer in the ith pavement area to be monitored is expressed;
the underground water level distance and the underground water body influence proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored are synthesized to obtain the underground water danger proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored, wherein the concrete calculation formula is as follows Expressed as the ratio coefficient of danger of groundwater corresponding to the jth structural layer in the ith pavement area to be monitored, sh j ' expressed as the reference water level distance corresponding to the j-th structural layer, f j 1 is a dangerous influence factor corresponding to the ground water level distance in the j-th structural layer, and f2 is a dangerous influence factor corresponding to the ground water body influence scaling factor.
Specifically, the settlement risk coefficient corresponding to each structural layer in each pavement subarea to be monitored is as follows The road bed settlement risk coefficient corresponding to the j-th structural layer in the i-th road surface subarea to be monitored is represented, and e1 and e2 are respectively represented as correction coefficients corresponding to the construction quality coefficient and the underground water risk proportion coefficient.
Specifically, the roadbed settlement early warning analysis is performed on roadbed settlement risk coefficients corresponding to each structural layer in each to-be-monitored pavement subarea, and the specific analysis is as follows:
and comparing the roadbed settlement risk coefficient corresponding to each structural layer in each pavement subarea to be monitored with the roadbed settlement risk coefficient corresponding to each structural layer stored in the information storage library, if the roadbed settlement risk coefficient corresponding to a structural layer in a pavement subarea to be monitored is larger than the roadbed settlement risk coefficient corresponding to the structural layer, marking the pavement subarea to be monitored as a dangerous settlement pavement subarea, marking the structural layer as a dangerous settlement structural layer, extracting the number corresponding to the dangerous settlement structural layer in the dangerous settlement pavement subarea, and sending the number to a settlement early warning prompt execution module.
Specifically, the dangerous bearing early warning analysis is performed on the dangerous bearing coefficient of each pavement subarea to be monitored, and the specific analysis is as follows:
and comparing the dangerous bearing coefficient of each road surface subarea to be monitored with the allowable dangerous bearing coefficient stored in the information storage library, if the dangerous bearing coefficient of a certain road surface subarea to be monitored is larger than the allowable dangerous bearing coefficient, marking the road surface subarea to be monitored as a dangerous bearing road surface subarea, and simultaneously acquiring the number corresponding to the dangerous bearing road surface subarea.
Specifically, the key parameters comprise key pavement sub-areas and key structure layers, wherein the key pavement sub-areas comprise dangerous settlement pavement sub-areas and dangerous bearing pavement sub-areas, and the key structure layers are dangerous settlement structure layers.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
according to the invention, the pavement area to be monitored is divided into a plurality of pavement subareas to be monitored and a plurality of structural layers, and meanwhile, each structural layer in each pavement subarea to be monitored automatically collects and analyzes parameters required by pavement subgrade settlement analysis through the monitoring terminal, the weight sensor and the intelligent high-definition camera automation equipment, so that on one hand, waste of a large amount of manpower resources and material resource is avoided, accuracy of measurement data is improved, reliability and scientific basis of analysis results are greatly improved, and further pavement subgrade settlement analysis results can be accurately, effectively and mastered, on the other hand, the analysis results are more targeted through the division of the pavement area to be monitored, and the situation that the internal structural layers are settled and the whole pavement subgrade is not influenced is avoided.
According to the settlement warning prompt execution module, settlement prompt is carried out on the road subgrade, so that the timeliness of settlement analysis of the road subgrade is greatly improved, and the whole road subgrade settlement analysis is scientific, timeliness and reliability.
In the process of monitoring the road construction quality, the compactness, the flatness and the thickness in each structural layer in each road sub-area to be monitored are comprehensively analyzed, the unilateral performance of the result obtained by single-aspect analysis is avoided, the road subgrade construction quality coefficient becomes more reliable and scientific, the construction quality coefficient is more convincing, the influence of the road subgrade construction quality coefficient on road subgrade settlement is effectively avoided, and the powerful data support is provided for the subsequent subgrade settlement analysis.
In the process of monitoring the danger of the underground water, the method synthesizes the influence proportion coefficient of the underground water body from three aspects of the temperature of the underground water, the pH value of the underground water and the osmotic pressure, so as to synthesize the influence proportion coefficient of the underground water body and the distance between the underground water level corresponding to each structural layer in each to-be-monitored pavement subarea, effectively solve the singleness and one-sided property of the existing pavement subgrade settlement analysis result, improve the comprehensiveness and scientific basis of the analysis result, provide powerful data support for the subsequent pavement subgrade settlement analysis, and improve the timeliness and effectiveness of the pavement subgrade settlement early warning to a certain extent.
In the dangerous bearing monitoring process of the road surface, the weight sensor and the intelligent high-definition camera are used for carrying out real-time monitoring analysis on each road surface subarea to be monitored, so that the corresponding dangerous bearing coefficient is obtained through the corresponding actual bearing weight and the corresponding actual bearing area of each road surface subarea to be monitored, the defect that the sedimentation early warning voice prompt cannot be carried out in time in the current road surface roadbed sedimentation analysis is effectively overcome, the extrusion to the road surface roadbed caused by long-time overload pre-pressing is avoided, the possibility of sedimentation of the road surface roadbed is effectively avoided, and the service life of the road surface roadbed is prolonged.
In the process of roadbed settlement analysis, the roadbed settlement early warning analysis is carried out from the two aspects of the construction quality coefficient of the roadbed and the danger proportion coefficient of the underground water, meanwhile, the roadbed settlement early warning analysis is carried out on the danger bearing coefficient of each sub-area of the road surface to be monitored, the one-sided performance of the existing roadbed analysis result of the road surface is made up, not only is effective data support provided for the analysis result, but also the rationality and the referenceability of the analysis result are improved, and the roadbed settlement problem caused by untimely discovery is effectively avoided.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a schematic diagram of the system module connection of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a road subgrade settlement monitoring, analyzing and early warning system based on the internet of things technology, which comprises a monitoring area dividing module, a monitoring area structural layer dividing module, a monitoring terminal layout module, a monitoring area construction quality analyzing module, a monitoring area road bearing capacity analyzing module, a groundwater monitoring and analyzing module, an information storage library, a subgrade settlement risk analyzing module, a subgrade settlement early warning analyzing module and a settlement early warning prompt executing module.
The system comprises a monitoring area dividing module, a monitoring terminal layout module, a monitoring area road surface bearing capacity analyzing module, a roadbed settlement early warning executing module and a roadbed settlement early warning prompt executing module, wherein the monitoring area dividing module is connected with the monitoring area structural layer dividing module, the monitoring terminal layout module is connected with the monitoring area dividing module, the monitoring area structural layer dividing module, the monitoring area construction quality analyzing module, the monitoring area road surface bearing capacity analyzing module and the groundwater monitoring analyzing module respectively, the monitoring area construction quality analyzing module is connected with an information storage library and the roadbed settlement dangerous analyzing module respectively, the monitoring area construction quality analyzing module is connected with the information storage library and the roadbed settlement early warning analyzing module, and the roadbed settlement early warning prompting executing module is connected with the information storage library and the roadbed settlement dangerous analyzing module respectively.
The monitoring area dividing module is used for dividing the road surface area to be monitored on the road in a grid mode to obtain each road surface subarea to be monitored, and numbering the road surface subareas to be monitored according to a preset sequence to be 1, 2.
The monitoring area structural layer dividing module is used for acquiring structural layers corresponding to all the pavement sub-areas to be monitored through the X-ray detector, and numbering the structural layers according to a preset sequence to be 1, 2.
According to the invention, the pavement area to be monitored is divided into a plurality of pavement subareas to be monitored and a plurality of structural layers, meanwhile, each structural layer in each pavement subarea to be monitored automatically collects and analyzes parameters required by pavement subgrade settlement analysis through the monitoring terminal, the weight sensor and the intelligent high-definition camera automation equipment, so that not only is the waste of a great amount of manpower resources and material resources avoided, the accuracy of measurement data improved, but also the reliability and the scientific basis of the analysis result are greatly improved, and the pavement subgrade settlement analysis result can be accurately, effectively and mastered, and on the other hand, the analysis result is more targeted through the division of the pavement area to be monitored, the occurrence of settlement of the internal structural layers is avoided, and the situation that the whole pavement subgrade cannot be influenced is avoided, and therefore, the settlement voice prompt of pertinence is carried out on each structural layer in each pavement subarea to be monitored.
Specifically, the structure layer corresponding to each pavement subarea to be monitored is obtained through the X-ray detector, and the specific obtaining steps are as follows:
x-rays are emitted to each pavement subarea to be monitored through the X-ray detector, the emitted rays penetrate through each pavement subarea to be monitored, and imaging and recording are carried out through the radiographic film, so that the internal structural film of each pavement subarea to be monitored is obtained.
And (3) putting the obtained radiographic film into a darkroom for processing to obtain the radiographic film of the internal structure of each pavement subarea to be monitored.
And according to the difference of gray values displayed by the structural layers in the ray films of the internal structures of the pavement subareas to be monitored, obtaining the structural layers corresponding to the pavement subareas to be monitored.
And carrying out distribution area contour recognition on each structural layer according to the distribution area corresponding to each structural layer in each pavement subarea to be monitored, wherein the recognized distribution area contour of each structural layer in each pavement subarea to be monitored is used as a boundary between the structural layers, and the thickness corresponding to each structural layer in each pavement subarea to be monitored is obtained according to the distribution area contour of each structural layer in each pavement subarea to be monitored.
Since the X-ray has a short wavelength and a large energy, only a part of the X-ray is absorbed by a substance when irradiated on the substance, and most of the X-ray is transmitted through an atomic gap, and the X-ray exhibits a strong transmission capability. The penetration of X-rays is related to the density of the substance, and substances with different densities can be distinguished by the property of differential absorption.
And the monitoring terminal layout module is used for carrying out monitoring terminal layout on each structural layer in each pavement subarea to be monitored, and simultaneously, weight sensors and intelligent high-definition cameras are arranged at each pavement subarea to be monitored.
Specifically, the monitoring terminal comprises a nuclear densimeter and underground water monitoring equipment, wherein the underground water monitoring equipment comprises a water level automatic monitor, a water quality monitor and an osmometer.
The nuclear densimeter or the nuclear instrument is short for a nuclear density and humidity detector, is an electronic instrument for detecting the density and humidity of the geotechnical building material in real time by using the isotope radiation principle, and can rapidly detect the wet density and the water content of the roadbed by using the nuclear densimeter.
And the construction quality analysis module of the monitoring area is used for analyzing construction quality coefficients corresponding to each structural layer in each pavement subarea to be monitored.
Specifically, the construction quality coefficients corresponding to each structural layer in each pavement sub-area to be monitored are analyzed, and the specific analysis is as follows:
and obtaining the compactness corresponding to each structural layer in each pavement subarea to be monitored through a nuclear densimeter.
The wet density and water content of the roadbed are measured by a nuclear densimeter, and the compactness corresponding to each structural layer in each pavement subarea to be monitored is obtained after comparison with a conventional method.
And uniformly distributing detection points in each structural layer in each pavement subarea to be monitored, further obtaining the corresponding vertical distance between each detection point in each structural layer in each pavement subarea to be monitored and the pavement area to be monitored, and screening out the maximum vertical distance and the minimum vertical distance from the vertical distances.
Based on the maximum vertical distance and the minimum vertical distance corresponding to each structural layer in each pavement subarea to be monitored, calculating the flatness corresponding to each structural layer in each pavement subarea to be monitored, wherein a specific calculation formula is as follows Expressed as the flatness corresponding to the jth structural layer in the ith pavement subregion, +.>And->Expressed as maximum vertical distance and minimum vertical distance, respectively, corresponding to the jth structural layer in the ith pavement subregion,/->Expressed as the average vertical distance corresponding to the jth structural layer in the ith pavement sub-area to be monitored.
It is to be noted that the impact force of the wheels on the road surface can be reduced by the flat road surface, the additional vibration generated by the running is small, the jolt of the vehicle is avoided, the running speed and the comfort can be improved, and the running cost is not increased. So in order to slow down the decay rate of the road surface, the flatness of the road surface structure should be emphasized.
Comprehensively analyzing the compactness, flatness and thickness corresponding to each structural layer in each pavement subarea to be monitored to obtain each pavement subarea to be monitoredThe construction quality coefficient corresponding to each structural layer is specifically calculated as follows Expressed as the construction quality coefficient corresponding to the j-th structural layer in the i-th pavement area to be monitored,/and>respectively expressed as compactness and thickness ys 'corresponding to the jth structural layer in the ith pavement area to be monitored' j 、pz′ j 、hd j ' is respectively expressed as standard compactness, standard flatness and standard thickness corresponding to the jth structural layer, and a1, a2 and a3 are respectively expressed as influence factors corresponding to the compactness, flatness and thickness.
In the process of monitoring the road construction quality, the compactness, the flatness and the thickness in each structural layer in each road sub-area to be monitored are comprehensively analyzed, the unilateral performance of the result obtained by single-aspect analysis is avoided, the road subgrade construction quality coefficient becomes more reliable and scientific, the construction quality coefficient is more convincing, the influence of the road subgrade construction quality coefficient on road subgrade settlement is effectively avoided, and the powerful data support is provided for the subsequent subgrade settlement analysis.
And the monitoring area pavement bearing capacity analysis module is used for analyzing dangerous bearing coefficients of all pavement subareas to be monitored by the weight sensor and the intelligent high-definition camera.
The dangerous bearing coefficients of all the pavement subareas to be monitored are analyzed, and the dangerous bearing coefficients are specifically analyzed as follows:
the actual bearing weight of each pavement subarea to be monitored is monitored through a weight sensor and is marked as m i ，m i Denoted as the actual load weight corresponding to the i-th sub-area of the road surface to be monitored.
Each road surface to be monitored is through intelligent high-definition cameraThe sub-area is obtained as the actual bearing area and marked as s i ，s i And the actual bearing area corresponding to the ith pavement subarea to be monitored is shown.
The actual bearing weight and the actual bearing area corresponding to each pavement subarea to be monitored are synthesized to obtain the dangerous bearing coefficient corresponding to each pavement subarea to be monitored, wherein the specific calculation formula is as follows Expressed as dangerous bearing coefficient corresponding to the ith pavement area to be monitored, m' expressed as nuclear bearing weight corresponding to the pavement area to be monitored on the highway, s i ' is expressed as the area corresponding to the ith pavement subarea to be monitored, and b1 and b2 are respectively expressed as the bearing weight and the influence factors corresponding to the bearing area.
In the dangerous bearing monitoring process of the road surface, the weight sensor and the intelligent high-definition camera are used for carrying out real-time monitoring analysis on each road surface subarea to be monitored, so that the corresponding dangerous bearing coefficient is obtained through the corresponding actual bearing weight and the corresponding actual bearing area of each road surface subarea to be monitored, the defect that the sedimentation early warning voice prompt cannot be carried out in time in the current road surface roadbed sedimentation analysis is effectively overcome, the extrusion to the road surface roadbed caused by long-time overload pre-pressing is avoided, the possibility of sedimentation of the road surface roadbed is effectively avoided, and the service life of the road surface roadbed is prolonged.
And the underground water monitoring and analyzing module is used for analyzing the underground water danger proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored.
Specifically, the analysis is performed on the corresponding groundwater danger ratio coefficient of each structural layer in each pavement subarea to be monitored, and the specific analysis is as follows:
the water quality parameters and the osmotic pressure of the underground water are respectively collected by a water quality monitor and an osmometer, wherein the water quality parameters comprise the temperature of the underground water and the pH value of the underground water;
the groundwater temperature, the groundwater pH value and the osmotic pressure are synthesized to obtain the groundwater water body influence proportionality coefficient, and the specific calculation formula is as followsKappa is expressed as an influence proportionality coefficient of groundwater water body, sw, sj and sy are respectively expressed as groundwater temperature, groundwater pH value and osmotic pressure, and sw ', sj ' and sy ' are respectively expressed as reference groundwater temperature, reference groundwater pH value and reference osmotic pressure;
the automatic water level monitor collects the groundwater level of each pavement subarea to be monitored, and simultaneously obtains the vertical distance between the groundwater level of each pavement subarea to be monitored and each structural layer, marks the vertical distance as the groundwater level distance, and further numbers the groundwater level distance as the groundwater level distance The water level distance of the groundwater corresponding to the j-th structural layer in the ith pavement area to be monitored is expressed;
the underground water level distance and the underground water body influence proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored are synthesized to obtain the underground water danger proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored, wherein the concrete calculation formula is as follows Expressed as the ratio coefficient of danger of groundwater corresponding to the jth structural layer in the ith pavement area to be monitored, sh j ' expressed as the reference water level distance corresponding to the j-th structural layer, f j 1 is a dangerous influence factor corresponding to the ground water level distance in the j-th structural layer, and f2 is a dangerous influence factor corresponding to the ground water body influence scaling factor.
It should be noted that, the influence of the water level distance, the groundwater water temperature, the groundwater ph value and the osmotic pressure on each structural layer is different, and the influence of the above four aspects on the structural layer at the bottom of the road bed is larger, so that the dangerous influence factors corresponding to the water level distance, the groundwater water temperature, the groundwater ph value and the osmotic pressure in each structural layer are different.
In the process of monitoring the danger of the underground water, the method synthesizes the influence proportion coefficient of the underground water body from three aspects of the temperature of the underground water, the pH value of the underground water and the osmotic pressure, so as to synthesize the influence proportion coefficient of the underground water body and the distance between the underground water level corresponding to each structural layer in each to-be-monitored pavement subarea, effectively solve the singleness and one-sided property of the existing pavement subgrade settlement analysis result, improve the comprehensiveness and scientific basis of the analysis result, provide powerful data support for the subsequent pavement subgrade settlement analysis, and improve the timeliness and effectiveness of the pavement subgrade settlement early warning to a certain extent.
The information storage library is used for storing the standard compactness, standard flatness and standard thickness corresponding to each structural layer, storing the dangerous influence factors corresponding to the groundwater level distance in each structural layer, storing the permitted subgrade settlement dangerous coefficient corresponding to each structural layer and storing the permitted dangerous bearing coefficient.
The roadbed settlement risk analysis module is used for analyzing settlement risk coefficients corresponding to the structural layers in the pavement subareas to be monitored by integrating construction quality coefficients corresponding to the structural layers in the pavement subareas to be monitored and underground water risk coefficients.
Specifically, the settlement risk coefficient corresponding to each structural layer in each pavement subarea to be monitored is as follows Represented as the jth in the ith road surface sub-area to be monitoredAnd the roadbed settlement risk coefficients corresponding to the structural layer, and e1 and e2 are respectively expressed as the construction quality coefficient and the correction coefficient corresponding to the groundwater risk proportion coefficient.
The roadbed settlement early warning analysis module is used for performing roadbed settlement early warning analysis on roadbed settlement dangerous coefficients corresponding to each structural layer in each to-be-monitored pavement subarea, and simultaneously performing dangerous bearing early warning analysis on dangerous bearing coefficients of each to-be-monitored pavement subarea, thereby obtaining key parameters.
Specifically, the dangerous bearing early warning analysis is performed on the dangerous bearing coefficient of each pavement subarea to be monitored, and the specific analysis is as follows:
and comparing the dangerous bearing coefficient of each road surface subarea to be monitored with the allowable dangerous bearing coefficient stored in the information storage library, if the dangerous bearing coefficient of a certain road surface subarea to be monitored is larger than the allowable dangerous bearing coefficient, marking the road surface subarea to be monitored as a dangerous bearing road surface subarea, and simultaneously acquiring the number corresponding to the dangerous bearing road surface subarea.
In the process of roadbed settlement analysis, the roadbed settlement early warning analysis is carried out from the two aspects of the construction quality coefficient of the roadbed and the danger proportion coefficient of the underground water, meanwhile, the roadbed settlement early warning analysis is carried out on the danger bearing coefficient of each sub-area of the road surface to be monitored, the one-sided performance of the existing roadbed analysis result of the road surface is made up, not only is effective data support provided for the analysis result, but also the rationality and the referenceability of the analysis result are improved, and the roadbed settlement problem caused by untimely discovery is effectively avoided.
And the settlement early warning prompt execution module is used for carrying out corresponding settlement early warning voice prompt based on the numbers corresponding to the key road surface subregions and the key structure layers in the key parameters.
Specifically, the key parameters comprise key pavement sub-areas and key structure layers, wherein the key pavement sub-areas comprise dangerous settlement pavement sub-areas and dangerous bearing pavement sub-areas, and the key structure layers are dangerous settlement structure layers.
According to the settlement warning prompt execution module, settlement prompt is carried out on the road subgrade, so that the timeliness of settlement analysis of the road subgrade is greatly improved, and the whole road subgrade settlement analysis is scientific, timeliness and reliability.
It should be noted that, the corresponding sedimentation early warning voice prompt includes but is not limited to: the roadbed settlement voice prompt is carried out on the dangerous settlement structural layers based on the numbers corresponding to the dangerous settlement structural layers in the dangerous settlement pavement subareas, the dangerous bearing voice prompt is carried out on the dangerous bearing pavement subareas based on the numbers corresponding to the dangerous bearing pavement subareas, and then bearing objects corresponding to the dangerous bearing pavement subareas are quickly dredged, and the roadbed settlement caused by long-time bearing extrusion is avoided.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (7)
1. Road surface road bed subsides monitoring analysis early warning system based on internet of things, characterized in that includes:
the monitoring area dividing module is used for dividing the road surface area to be monitored on the road in a grid mode to obtain each road surface subarea to be monitored, and numbering the road surface subareas to be monitored according to a preset sequence to be 1, 2.
The monitoring area structural layer dividing module is used for acquiring structural layers corresponding to the pavement subareas to be monitored through the X-ray detector, and numbering the structural layers into 1,2 according to a preset sequence;
the monitoring terminal layout module is used for carrying out monitoring terminal layout on each structural layer in each pavement subarea to be monitored, and meanwhile, weight sensors and intelligent high-definition cameras are arranged at the positions of each pavement subarea to be monitored;
the construction quality analysis module of the monitoring area is used for analyzing construction quality coefficients corresponding to each structural layer in each pavement subarea to be monitored;
the monitoring area pavement bearing capacity analysis module is used for analyzing dangerous bearing coefficients of all pavement subareas to be monitored by the weight sensor and the intelligent high-definition camera;
the underground water monitoring and analyzing module is used for analyzing the underground water danger proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored;
the information storage library is used for storing standard compactness, standard flatness and standard thickness corresponding to each structural layer, storing dangerous influence factors corresponding to the groundwater level distance in each structural layer, storing permitted subgrade settlement dangerous coefficients corresponding to each structural layer and storing permitted dangerous bearing coefficients;
the roadbed settlement risk analysis module is used for analyzing settlement risk coefficients corresponding to the structural layers in the pavement subareas to be monitored by integrating construction quality coefficients corresponding to the structural layers in the pavement subareas to be monitored and underground water risk proportion coefficients;
the roadbed settlement early warning analysis module is used for performing roadbed settlement early warning analysis on roadbed settlement dangerous coefficients corresponding to each structural layer in each to-be-monitored pavement subarea, and performing dangerous bearing early warning analysis on dangerous bearing coefficients of each to-be-monitored pavement subarea, thereby obtaining key parameters;
the settlement early warning prompt execution module is used for carrying out corresponding settlement early warning voice prompt based on numbers corresponding to key pavement subregions and key structure layers in key parameters;
the construction quality coefficients corresponding to each structural layer in each pavement subarea to be monitored are analyzed, and the concrete analysis is as follows:
obtaining the compactness corresponding to each structural layer in each pavement subarea to be monitored through a nuclear densimeter;
uniformly distributing detection points in each structural layer in each pavement subarea to be monitored, further obtaining the corresponding vertical distance between each detection point in each structural layer in each pavement subarea to be monitored and the pavement area to be monitored, and screening out the maximum vertical distance and the minimum vertical distance from the vertical distances;
based on the maximum vertical distance and the minimum vertical distance corresponding to each structural layer in each pavement subarea to be monitoredThe straight distance is calculated, the flatness corresponding to each structural layer in each pavement subarea to be monitored is calculated according to the specific calculation formula as follows Expressed as the flatness corresponding to the jth structural layer in the ith pavement subregion, +.>And->Expressed as maximum vertical distance and minimum vertical distance, respectively, corresponding to the jth structural layer in the ith pavement subregion,/->Representing the average vertical distance corresponding to the j structural layer in the i-th pavement subarea to be monitored;
comprehensively analyzing the compactness, flatness and thickness corresponding to each structural layer in each pavement subarea to be monitored to obtain construction quality coefficients corresponding to each structural layer in each pavement subarea to be monitored, wherein a specific calculation formula is as follows Expressed as the construction quality coefficient corresponding to the j-th structural layer in the i-th pavement area to be monitored,/and>respectively expressed as compactness and thickness ys 'corresponding to the jth structural layer in the ith pavement area to be monitored' j 、pz′ j 、hd′ j Respectively denoted asThe standard compactness, standard flatness and standard thickness corresponding to the jth structural layer are respectively expressed as influence factors corresponding to the compactness, flatness and thickness, and a1, a2 and a3 are respectively expressed as the influence factors corresponding to the compactness, flatness and thickness;
the dangerous bearing coefficients of all the pavement subareas to be monitored are analyzed, and the dangerous bearing coefficients are specifically analyzed as follows:
the actual bearing weight of each pavement subarea to be monitored is monitored through a weight sensor and is marked as m i ，m i The actual bearing weight corresponding to the ith pavement subarea to be monitored is represented;
the actual bearing area of each pavement subarea to be monitored is obtained through an intelligent high-definition camera, and the actual bearing area is marked as s i ，s i The actual bearing area corresponding to the ith pavement subarea to be monitored is represented;
the actual bearing weight and the actual bearing area corresponding to each pavement subarea to be monitored are synthesized to obtain the dangerous bearing coefficient corresponding to each pavement subarea to be monitored, wherein the specific calculation formula is as follows Expressed as dangerous bearing coefficient corresponding to the ith pavement area to be monitored, m' expressed as nuclear bearing weight corresponding to the pavement area to be monitored on the highway, s i′ The area corresponding to the i-th pavement subarea to be monitored is represented, and b1 and b2 are respectively represented as bearing weight and influence factors corresponding to the bearing area;
the analysis is carried out on the corresponding groundwater danger proportion coefficient of each structural layer in each pavement subarea to be monitored, and the concrete analysis is as follows:
the water quality parameters and the osmotic pressure of the underground water are respectively collected by a water quality monitor and an osmometer, wherein the water quality parameters comprise the temperature of the underground water and the pH value of the underground water;
the groundwater temperature, the groundwater pH value and the osmotic pressure are integrated to obtain the groundwater water body influence proportionality coefficientThe specific calculation formula is thatKappa is expressed as an influence proportionality coefficient of groundwater water body, sw, sj and sy are respectively expressed as groundwater temperature, groundwater pH value and osmotic pressure, and sw ', sj ' and sy ' are respectively expressed as reference groundwater temperature, reference groundwater pH value and reference osmotic pressure;
the automatic water level monitor collects the groundwater level of each pavement subarea to be monitored, and simultaneously obtains the vertical distance between the groundwater level of each pavement subarea to be monitored and each structural layer, marks the vertical distance as the groundwater level distance, and further numbers the groundwater level distance as the groundwater level distanceThe water level distance of the groundwater corresponding to the j-th structural layer in the ith pavement area to be monitored is expressed;
the underground water level distance and the underground water body influence proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored are synthesized to obtain the underground water danger proportion coefficient corresponding to each structural layer in each pavement subarea to be monitored, wherein the concrete calculation formula is as follows Expressed as the ratio coefficient of danger of groundwater corresponding to the jth structural layer in the ith pavement area to be monitored, sh' j Expressed as the reference water level distance, f, corresponding to the jth structural layer j 1 is a dangerous influence factor corresponding to the ground water level distance in the j-th structural layer, and f2 is a dangerous influence factor corresponding to the ground water body influence scaling factor.
2. The road surface roadbed settlement monitoring, analyzing and early warning system based on the technology of the Internet of things, which is characterized in that: the method comprises the following specific acquisition steps of acquiring a structural layer corresponding to each pavement subarea to be monitored through an X-ray detector:
transmitting X-rays to each pavement subarea to be monitored through an X-ray detector, and enabling the transmitted rays to penetrate through each pavement subarea to be monitored and be subjected to imaging record through a ray film so as to obtain an internal structure film of each pavement subarea to be monitored;
the obtained radiographic film is placed into a darkroom for processing, and then the inner structure radiographic film of each pavement subarea to be monitored is obtained;
according to the difference of gray values displayed by the structural layers in the ray films of the internal structures of the sub-areas of the road surfaces to be monitored, obtaining the corresponding structural layers of the sub-areas of the road surfaces to be monitored;
and carrying out distribution area contour recognition on each structural layer according to the distribution area corresponding to each structural layer in each pavement subarea to be monitored, wherein the recognized distribution area contour of each structural layer in each pavement subarea to be monitored is used as a boundary between the structural layers, and the thickness corresponding to each structural layer in each pavement subarea to be monitored is obtained according to the distribution area contour of each structural layer in each pavement subarea to be monitored.
3. The road surface roadbed settlement monitoring, analyzing and early warning system based on the technology of the Internet of things, which is characterized in that: the monitoring terminal comprises a nuclear densimeter and underground water monitoring equipment, wherein the underground water monitoring equipment comprises a water level automatic monitor, a water quality monitor and an osmometer.
4. The road surface roadbed settlement monitoring, analyzing and early warning system based on the technology of the Internet of things, which is characterized in that: the settlement risk coefficient corresponding to each structural layer in each pavement subarea to be monitored is specifically calculated as follows Denoted as the ith standbyAnd monitoring roadbed settlement risk coefficients corresponding to the jth structural layer in the pavement subarea, wherein e1 and e2 are respectively expressed as construction quality coefficients and correction coefficients corresponding to the underground water risk proportion coefficients.
5. The road surface roadbed settlement monitoring, analyzing and early warning system based on the technology of the Internet of things, which is characterized in that: roadbed settlement early warning analysis is carried out on roadbed settlement risk coefficients corresponding to each structural layer in each pavement subarea to be monitored, and the roadbed settlement early warning analysis is specifically carried out as follows:
and comparing the roadbed settlement risk coefficient corresponding to each structural layer in each pavement subarea to be monitored with the roadbed settlement risk coefficient corresponding to each structural layer stored in the information storage library, if the roadbed settlement risk coefficient corresponding to a structural layer in a pavement subarea to be monitored is larger than the roadbed settlement risk coefficient corresponding to the structural layer, marking the pavement subarea to be monitored as a dangerous settlement pavement subarea, marking the structural layer as a dangerous settlement structural layer, extracting the number corresponding to the dangerous settlement structural layer in the dangerous settlement pavement subarea, and sending the number to a settlement early warning prompt execution module.
6. The road surface roadbed settlement monitoring, analyzing and early warning system based on the technology of the Internet of things, which is characterized in that: dangerous bearing early warning analysis is carried out on dangerous bearing coefficients of all the pavement subareas to be monitored, and the dangerous bearing early warning analysis is specifically carried out as follows:
and comparing the dangerous bearing coefficient of each road surface subarea to be monitored with the allowable dangerous bearing coefficient stored in the information storage library, if the dangerous bearing coefficient of a certain road surface subarea to be monitored is larger than the allowable dangerous bearing coefficient, marking the road surface subarea to be monitored as a dangerous bearing road surface subarea, and simultaneously acquiring the number corresponding to the dangerous bearing road surface subarea.
7. The road surface roadbed settlement monitoring, analyzing and early warning system based on the technology of the Internet of things, which is characterized in that: the key parameters comprise key pavement sub-areas and key structure layers, wherein the key pavement sub-areas comprise dangerous settlement pavement sub-areas and dangerous bearing pavement sub-areas, and the key structure layers are dangerous settlement structure layers.
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