CN116564067B - Highway state early warning system based on wisdom gathers materials technique - Google Patents
Highway state early warning system based on wisdom gathers materials technique Download PDFInfo
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- 230000002159 abnormal effect Effects 0.000 claims abstract description 18
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Abstract
The invention relates to the technical field of highway state monitoring, and particularly discloses a highway state early warning system based on an intelligent aggregate technology, which comprises the following steps: the aggregate sensing sensors are provided with a plurality of groups and are uniformly buried under the pavement and used for sensing the deformation state of the pavement; the weather monitoring sensor is used for monitoring the weather state of the current area in real time; the ponding amount monitoring sensor is provided with a plurality of groups and is used for monitoring ponding states of corresponding areas; the road monitoring module is used for monitoring the real-time vehicle state on the road; the analysis module is used for judging whether the highway state is abnormal or not according to the deformation state, carrying out potential risk analysis on the deformation state according to the climate state, the ponding state and the real-time vehicle state, and carrying out early warning when the abnormality or the potential risk is judged to exist; the invention can improve the timeliness of the judging result by comparing the deformation quantity actually monitored with the predicted deformation quantity.
Description
Technical Field
The invention relates to the technical field of highway state monitoring and early warning, in particular to a highway state early warning system based on an intelligent aggregate technology.
Background
In the process of highway construction, the construction complexity and the road quality problem after construction are different due to the difference of construction areas, and along with the rapid development of hardware technologies such as intelligent internet of things technology and sensors, the road state is monitored by utilizing an aggregate sensor, and the structural deformation state of the road can be timely monitored and early warned, so that the real-time supervision of the road state is ensured, and the timeliness of overhauling the road is improved.
In the prior art, the monitoring process of the highway state is mainly realized by arranging intelligent hardware such as a deformation sensor and the like inside a highway, real-time deformation data of a monitoring point position of the highway are monitored, the deformation data are compared with theoretical values, and then judgment of whether the highway state is early-warned or not is realized, and timely treatment is performed when an early-warning problem occurs, so that the driving safety is ensured.
When the existing aggregate sensor is directly buried underground, firstly, the electronic product is directly buried and is easily affected by natural disasters (factors such as water damage and the like), the reliability is low, and the electronic product is easily disabled; secondly, under the influence of road vehicle load, the sensor module needs to resist compression, high strength and corrosion, and a result obtained by detection also has larger error, so that the accuracy of the monitored result is poor; in addition, in the prior art, the deformation analysis process is mainly compared based on the early warning value, and the analysis process can only judge when obvious problems occur, so that certain hysteresis exists in the judgment process.
Disclosure of Invention
The invention aims to provide a highway state early warning system based on an intelligent aggregate technology, which solves the following technical problems:
how to realize the timeliness and the accuracy of the highway state early warning based on the intelligent aggregate technology.
The aim of the invention can be achieved by the following technical scheme:
a highway state early warning system based on a smart aggregate technology, the system comprising:
the aggregate sensing sensors are provided with a plurality of groups and are uniformly buried under the pavement and used for sensing the deformation state of the pavement;
the weather monitoring sensor is used for monitoring the weather state of the current area in real time;
the ponding amount monitoring sensor is provided with a plurality of groups and is used for monitoring ponding states of corresponding areas;
the road monitoring module is used for monitoring the real-time vehicle state on the road;
the analysis module is used for judging whether the highway state is abnormal or not according to the deformation state, carrying out potential risk analysis on the deformation state according to the climate state, the ponding state and the real-time vehicle state, and carrying out early warning when the abnormality or the potential risk is judged to exist.
In one embodiment, the aggregate perception sensor comprises:
3D aggregate is obtained through 3D printing according to a real aggregate 3D model, and a placing groove is formed;
the three-axis acceleration sensor is arranged in the 3D aggregate placing groove;
and the solar panel power supply module is electrically connected with the triaxial acceleration sensor and is used for supplying power to the triaxial acceleration sensor.
In one embodiment, the process of determining whether the road status is abnormal by the analysis module includes:
acquiring acceleration data a (t) and angular velocity data based on a triaxial acceleration sensor；
By the formulaRespectively calculating and obtaining the speed on X, Y, Z shaft、/>、/>；
By the formulaRespectively calculating and obtaining the displacement on X, Y, Z axis、/>、/>；
By the formulaCalculating to obtain rotation angle->；
Wherein t is the current time, t-1 is the last time, and the duration of t-1 is a preset fixed value;is the speed of the last moment; />The displacement is the displacement at the last moment; />The rotation angle is the rotation angle at the last moment;
will be、/>、/>Respectively with the early warning displacement threshold->And (3) performing comparison:
if it is、/>、/>Any one of which has a value of +.>Judging whether the road state is abnormal or not;
will beAnd the early warning angle threshold value->And (3) performing comparison:
if it isAnd judging whether the road state is abnormal or not.
In one embodiment, the process of the analysis module performing the risk potential analysis includes:
before t time is acquiredHistorical climate state information, ponding state information and real-time vehicle state information of a period;
fitting the allowable displacement of X, Y, Z axis in each direction according to the historical climate state information, the ponding state information and the real-time vehicle state information、/>、/>Angle allowance->；
Will be、/>、/>、/>Respectively and->、/>、/>、/>And comparing, and judging whether potential risks exist according to the comparison result.
In one embodiment, the process of obtaining the displacement allowance and the angle allowance is:
by the formulaCalculating to obtain the displacement allowance of X-axis +.>；
By the formulaCalculating to obtain the displacement allowance of Y-axis +.>；
By the formulaCalculating to obtain the displacement allowance of the Z axis>；
By the formulaCalculating the angle allowance +.>；
wherein ,is the basic displacement; />Is the basic angle variation; />、/>、/>X, Y, Z axis influence coefficients, respectively; n is the number of the existing ponding time intervals, i epsilon [1, N]；/>The ith water accumulation time interval;=/>-/>the method comprises the steps of carrying out a first treatment on the surface of the r (t) is a historical rainfall variation curve with time; />A natural absorption function for rainfall in the area; m is the number of rainfall time intervals, j is E [1, M]；/>The j-th rainfall time interval; />For the first judgment function, ++>Is a second judging function; g 1 、g 2 Is a displacement weight coefficient; h is a 1 、h 2 Is an angle weight coefficient; />The influence coefficient of the highway load on the displacement in the X-axis direction is obtained; />The influence coefficient of the road load on the Y-axis displacement is obtained; />The influence coefficient of the road load on the displacement in the Z axis direction is obtained; />The angle influence coefficient is used for highway load.
In one embodiment, the displacement influencing factor、/>、/>Angle influence coefficient->The acquisition process of (1) comprises:
acquisition based on road monitoring moduleThe image information in the time period is identified, and the road vehicle type and the corresponding running time point are obtained;
predicting vehicle weight data according to vehicle type, and acquiring displacement influence coefficients based on the vehicle weight data and corresponding driving time points、/>、/>Angle influence coefficient->。
In one embodiment, the displacement influencing factor、/>、/>Angle influence coefficient->The calculation process of (1) comprises:
by the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain angle influence coefficient->；
Wherein D isThe traffic in the time period, k is [1, D ]]；W k Predicted vehicle weight for the kth vehicle; q isThe number of driving in the interval, I E [1, Q]；/>Predicted vehicle weight for the first vehicle; o is->The number of driving in the interval e E [1,O ]]；W e Predicted vehicle weight for the e-th vehicle; />、/>、/>Is a preset adjustment coefficient;for load displacement influencing functions +.>As a load angle influence function; />、/>、/>The component coefficients of the X, Y, Z axes, respectively.
In one embodiment, the process of performing the risk potential analysis by the analysis module further comprises:
will be、/>、/>、/>Respectively and->、/>、/>、/>And (3) performing comparison:
if it is、/>、/>And->Judging that the potential risk analysis result is normal;
otherwise, judging that the potential risk analysis result is abnormal.
The invention has the beneficial effects that:
(1) According to the invention, the deformation quantity actually monitored is compared with the predicted deformation quantity, so that the potential risk can be timely judged before the deformation quantity is obviously abnormal, the timeliness of a judging result can be further improved, and the potential safety hazard problem of road running caused by the hysteresis of monitoring is avoided.
(2) According to the invention, the triaxial acceleration sensor is arranged in the 3D aggregate, the 3D aggregate is obtained through 3D printing according to the real aggregate 3D model, and the structure of the 3D aggregate can better realize the deformation state monitoring process, so that the accuracy of the monitoring result is improved.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a logic block diagram of a highway status warning system of the present invention;
FIG. 2 is a pictorial view of a 3D aggregate of the present invention;
FIG. 3 is a pictorial view of an aggregate sensing sensor in accordance with 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, in one embodiment, a highway status warning system based on smart aggregate technology is provided, the system comprising:
the aggregate sensing sensors are provided with a plurality of groups and are uniformly buried under the pavement and used for sensing the deformation state of the pavement;
the weather monitoring sensor is used for monitoring the weather state of the current area in real time;
the ponding amount monitoring sensor is provided with a plurality of groups and is used for monitoring ponding states of corresponding areas;
the road monitoring module is used for monitoring the real-time vehicle state on the road;
the analysis module is used for judging whether the highway state is abnormal or not according to the deformation state, carrying out potential risk analysis on the deformation state according to the climate state, the ponding state and the real-time vehicle state, and carrying out early warning when the abnormality or the potential risk is judged to exist.
Through above-mentioned technical scheme, this embodiment is at first buried in advance under the road surface through aggregate perception sensor, realize the testing process to road surface deformation state, simultaneously, based on the weather monitoring sensor, ponding volume monitoring sensor and the information deformation volume that road monitoring module obtained are predicted, compare through actual monitoring's deformation volume and the deformation volume of prediction, can produce obvious unusual before the deformation volume, in time judge potential risk, and then can improve the timeliness of judgement result, avoid the hysteresis quality of monitoring to cause the potential safety hazard problem that the road was driven.
The climate monitoring sensor, the ponding amount monitoring sensor and the road monitoring module in the technical scheme all realize the functions thereof through the internet of things equipment and the intelligent hardware equipment in the prior art, and are not further detailed herein.
As an embodiment of the present invention, referring to fig. 2 to 3, the aggregate sensing sensor includes:
3D aggregate is obtained through 3D printing according to a real aggregate 3D model, and a placing groove is formed;
the three-axis acceleration sensor is arranged in the 3D aggregate placing groove;
and the solar panel power supply module is electrically connected with the triaxial acceleration sensor and is used for supplying power to the triaxial acceleration sensor.
According to the technical scheme, the triaxial acceleration sensor is arranged in the 3D aggregate, 3D printing is performed through high-temperature-resistant, corrosion-resistant and high-strength materials, so that a structure similar to the shape of a real aggregate can be obtained, the triaxial acceleration sensor is arranged in a placing groove of the 3D aggregate, on one hand, the compressive strength of the triaxial acceleration sensor is enhanced, and more importantly, the structure of the 3D aggregate can better realize the monitoring process of deformation states, and further the accuracy of a monitoring result is improved; in addition, through solar panel power module and triaxial acceleration sensor electric connection, can supply power to triaxial acceleration sensor, guarantee the power supply of monitoring process.
As one embodiment of the present invention, the process of determining whether the road status is abnormal by the analysis module includes:
acquiring acceleration data a (t) and angular velocity data based on a triaxial acceleration sensor；
By the formulaRespectively calculating and obtaining the speed on X, Y, Z shaft、/>、/>；
By the formulaRespectively calculating and obtaining the displacement on X, Y, Z axis、/>、/>；
By the formulaCalculating to obtain rotation angle->；
Wherein t is the current time, t-1 is the last time, and the duration of t-1 is a preset fixed value;is the speed of the last moment; />The displacement is the displacement at the last moment; />The rotation angle is the rotation angle at the last moment;
will be、/>、/>Respectively with the early warning displacement threshold->And (3) performing comparison:
if it is、/>、/>Any one of which has a value of +.>Judging whether the road state is abnormal or not;
will beAnd the early warning angle threshold value->And (3) performing comparison:
if it isAnd judging whether the road state is abnormal or not.
Through the above technical solution, the embodiment provides a specific method for acquiring the reverse deformation amount of the acceleration data through the triaxial acceleration sensor, specifically, through a formulaRespectively calculating and obtaining the speed on X, Y, Z shaft、、The method comprises the steps of carrying out a first treatment on the surface of the Will be，，Respectively put into the formula to obtain the speed on the X, Y, Z shaft、、The method comprises the steps of carrying out a first treatment on the surface of the And then will be=、=、=Respectively bring into formulaFurther, the displacement on the X, Y, Z axis can be obtained、、The method comprises the steps of carrying out a first treatment on the surface of the Similarly, based on the formulaThe rotation angle can be monitored and judged according to the obtained angular velocity, and then the rotation angle is determined by、、Respectively with the early warning displacement threshold valueThe comparison is carried out,and early warning angle thresholdComparing, and early warning the displacement threshold valueEarly warning angle thresholdFitting the critical data in the safety risk state, thus if、、Any one of the values is greater than or equal toOr (b) And judging whether the highway state is abnormal or not, so that the early warning judgment of the highway state can be realized.
As one embodiment of the present invention, the process of performing the risk potential analysis by the analysis module includes:
before t time is acquiredHistorical climate state information, ponding state information and real-time vehicle state information of a period;
fitting the allowable displacement of X, Y, Z axis in each direction according to the historical climate state information, the ponding state information and the real-time vehicle state information、/>、/>Angle allowance->；
Will be、/>、/>、/>Respectively and->、/>、/>、/>And comparing, and judging whether potential risks exist according to the comparison result.
By the above technical scheme, the present embodiment provides a process of performing all-in-one risk analysis by using the time before the current timeHistorical climate state information, ponding state information and real-time vehicle state information of a period of time, and according to the displacement allowable quantity generated in the period of time>、/>、/>Angle allowance->The displacement and the selection angle which are monitored in real time are used for prediction, and the displacement and the selection angle are compared with the corresponding allowable amount, so that whether the problem of overlarge displacement or rotation angle exists can be judged according to the comparison, further, the timely early warning process can be carried out before the displacement or rotation angle reaches the early warning threshold value, the road can be timely trimmed, and the driving safety is improved.
As one embodiment of the present invention, the process of obtaining the displacement allowance and the angle allowance is as follows:
by the formulaCalculating to obtain the displacement allowance of X-axis +.>；
By the formulaCalculating to obtain the displacement allowance of Y-axis +.>；
By the formulaCalculating to obtain the displacement allowance of the Z axis>；
By the formulaCalculating the angle allowance +.>；
wherein ,is the basic displacement; />Is the basic angle variation; />、/>、/>X, Y, Z axis influence coefficients, respectively; n is the number of the existing ponding time intervals, i epsilon [1, N]；/>The ith water accumulation time interval;=/>-/>the method comprises the steps of carrying out a first treatment on the surface of the r (t) is a historical rainfall variation curve with time; />A natural absorption function for rainfall in the area; m is the number of rainfall time intervals, j is E [1, M]；/>Is the j thA rainfall time interval; />For the first judgment function, ++>Is a second judging function; g 1 、g 2 Is a displacement weight coefficient; h is a 1 、h 2 Is an angle weight coefficient; />The influence coefficient of the highway load on the displacement in the X-axis direction is obtained; />The influence coefficient of the road load on the Y-axis displacement is obtained; />The influence coefficient of the road load on the displacement in the Z axis direction is obtained; />The angle influence coefficient is used for highway load.
Through the technical scheme, the embodiment provides the displacement allowable quantity、/>、/>Angle allowance->Taking the calculation process of the displacement allowable quantity of the X axis as an example, and based on the basic displacement quantity, the method comprises the following steps of +.>Data record adjustment to the direction;
in combination with rainfall and ponding to the road in the areaInfluence factor and influence coefficient of highway load on displacement in X-axis directionFurther, the correction of the basic displacement is realized, and the displacement allowable quantity of the X axis is obtained>；
Wherein, the influence of the rainfall and the accumulated water quantity on the road in the area is judged according to the accumulated time length of the accumulated water and the real-time rainfall, wherein, a first judging functionSecond judging function->Obtained from the fitting data, therefore,reflecting the influence state of accumulated water quantity, +.>Reflects the influence state of rainfall inventory, wherein ∈>Is a rainfall natural absorption function of the area, which is based on the accumulated rainfallIs varied by a variation of (a) and thus by +.>The road state can be judged more accurately according to the rainfall;
similarly, the displacement allowance of the Y axis is obtained according to the processDisplacement allowance of Z axis->Angle allowance->。
The basic displacement in the above technical schemeFoundation angle variation->Selecting and setting natural deformation data in an ideal state; rainfall natural absorption function->Fitting and analyzing according to the topography of the region; displacement weight coefficient g 1 、g 2 Angle weight coefficient h 1 、h 2 Then the fitting process is analyzed based on the test data and is not described in detail herein.
As one embodiment of the present invention, the displacement influence coefficient、/>、/>Angle influence coefficient->The acquisition process of (1) comprises:
acquisition based on road monitoring moduleThe image information in the time period is identified, and the road vehicle type and the corresponding running time point are obtained;
predicting vehicle weight data according to vehicle type, and acquiring displacement influence coefficients based on the vehicle weight data and corresponding driving time points、/>、/>Angle influence coefficient->。
Coefficient of displacement influence、/>、/>Angle influence coefficient->The calculation process of (1) comprises:
by the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain angle influence coefficient->；
Wherein D isThe traffic in the time period, k is [1, D ]]；W k Predicted vehicle weight for the kth vehicle; q isThe number of driving in the interval, l E [1, Q]；/>Predicted vehicle weight for the first vehicle; o is->The number of driving in the interval e E [1,O ]]；W e Predicted vehicle weight for the e-th vehicle; />、/>、/>Is a preset adjustment coefficient;for load displacement influencing functions +.>As a load angle influence function; />、/>、/>The component coefficients of the X, Y, Z axes, respectively.
Through the technical scheme, the embodiment gives the displacement influence coefficient、/>、/>Angle influence coefficient->According to the road monitoring module ∈A>The image information in the time period is identified, and the road vehicle type and the corresponding running time point are obtained; then, the vehicle weight data is predicted according to the vehicle type, and the displacement influence coefficient is obtained based on the vehicle weight data and the corresponding driving time point>、/>、/>Angle influence coefficient->Specifically, the displacement influence coefficient in the X-axis +.>For example, the total mass of the vehicle during rainfall and the total mass of the vehicle during water accumulation are calculated for comprehensive analysis, wherein the adjustment coefficient is preset>、/>、/>Fitting a setting according to the influence data in the test data, wherein +.>＜/>＜/>The method comprises the steps of carrying out a first treatment on the surface of the Whereas the load displacement influence function +.>Load angle influencing function->Obtained by BIM analysis fitting based on road base data, and X, Y, Z axis component coefficient +.>、/>、/>According to the method of setting the coordinate system, determined after stress analysis, therefore, by +.> The influence condition of displacement on the X axis can be obtained; similarly, the displacement influence coefficient +.>、/>Angle influence coefficient->。
As an embodiment of the present invention, the process of performing the risk potential analysis by the analysis module further includes:
will be、/>、/>、/>Respectively and->、/>、/>、/>And (3) performing comparison:
if it is、/>、/>And->Judging that the potential risk analysis result is normal;
otherwise, judging that the potential risk analysis result is abnormal.
By the technical proposal, by the method of、/>、/>、/>Respectively and->、/>、/>、/>The comparison is carried out, obviously only at +.>、/>、And->And when the road state is normal, if the road state is not normal, the potential risk is indicated, and the corresponding road section needs to be trimmed in time, so that the early warning of the road state is realized through the comparison process.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (1)
1. Highway state early warning system based on wisdom aggregate technique, characterized in that, the system includes:
the aggregate sensing sensors are provided with a plurality of groups and are uniformly buried under the pavement and used for sensing the deformation state of the pavement;
the weather monitoring sensor is used for monitoring the weather state of the current area in real time;
the ponding amount monitoring sensor is provided with a plurality of groups and is used for monitoring ponding states of corresponding areas;
the road monitoring module is used for monitoring the real-time vehicle state on the road;
the analysis module is used for judging whether the highway state is abnormal or not according to the deformation state, carrying out potential risk analysis on the deformation state according to the climate state, the ponding state and the real-time vehicle state, and carrying out early warning when the abnormality or the potential risk is judged to exist;
the aggregate perception sensor comprises:
3D aggregate is obtained through 3D printing according to a real aggregate 3D model, and a placing groove is formed;
the three-axis acceleration sensor is arranged in the 3D aggregate placing groove;
the solar panel power supply module is electrically connected with the triaxial acceleration sensor and is used for supplying power to the triaxial acceleration sensor;
the process of judging whether the road state is abnormal by the analysis module comprises the following steps:
based on three axesThe acceleration sensor acquires acceleration data a (t) and angular velocity data；
By the formulaRespectively calculating and obtaining the speed on the X, Y, Z shaft>、、/>；
By the formulaRespectively calculating and obtaining the displacement on the X, Y, Z axis>、、/>；
By the formulaCalculating to obtain rotation angle->；
Wherein t is the current time, t-1 is the last time, and the duration of t-1 is a preset fixed value;to get up toA speed at one instant; />The displacement is the displacement at the last moment; />The rotation angle is the rotation angle at the last moment;
will be、/>、/>Respectively with the early warning displacement threshold->And (3) performing comparison:
if it is、/>、/>Any one of which has a value of +.>Judging whether the road state is abnormal or not;
will beAnd the early warning angle threshold value->And (3) performing comparison:
if it isJudging whether the road state is abnormal or not;
the process of the analysis module for potential risk analysis comprises the following steps:
before t time is acquiredHistorical climate state information, ponding state information and real-time vehicle state information of a period;
fitting the allowable displacement of X, Y, Z axis in each direction according to the historical climate state information, the ponding state information and the real-time vehicle state information、/>、/>Angle allowance->；
Will be、/>、/>、/>Respectively and->、/>、/>、/>Comparing, and judging whether potential risks exist according to the comparison result;
the acquisition process of the displacement allowable quantity and the angle allowable quantity comprises the following steps:
by the formulaCalculating to obtain the displacement allowance of X-axis +.>；
By the formulaCalculating to obtain the displacement allowance of Y-axis +.>；
By the formulaCalculating to obtain the displacement allowance of the Z axis>；
By the formulaCalculating the angle allowance +.>；
wherein ,is the basic displacement; />Is the basic angle variation; />、/>、/>X, Y, Z axis influence coefficients, respectively; n is the number of the existing ponding time intervals, i epsilon [1, N]；/>The ith water accumulation time interval;=/>-/>the method comprises the steps of carrying out a first treatment on the surface of the r (t) is a historical rainfall variation curve with time; />A natural absorption function for rainfall in the area; m is the number of rainfall time intervals, j is E [1, M]；/>The j-th rainfall time interval; />For the first judgment function, ++>Is a second judging function; g 1 、g 2 Is a displacement weight coefficient; h is a 1 、h 2 Is an angle weight coefficient; />The influence coefficient of the highway load on the displacement in the X-axis direction is obtained; />The influence coefficient of the road load on the Y-axis displacement is obtained; />The influence coefficient of the road load on the displacement in the Z axis direction is obtained; />The angle influence coefficient is the road load;
coefficient of displacement influence、/>、/>Angle influence coefficient->The acquisition process of (1) comprises:
acquisition based on road monitoring moduleThe image information in the time period is identified, and the road vehicle type and the corresponding running time point are obtained;
predicting vehicle weight data according to vehicle type, and acquiring displacement influence coefficients based on the vehicle weight data and corresponding driving time points、/>、/>Angle influence coefficient->；
Coefficient of displacement influence、/>、/>Angle influence coefficient->The calculation process of (1) comprises:
by the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain displacement influence coefficient->；
By the formula Calculating to obtain angle influence coefficient->；
Wherein D isThe traffic in the time period, k is [1, D ]]；W k Predicted vehicle weight for the kth vehicle; q is->The number of driving in the interval, l E [1, Q]；/>Predicted vehicle weight for the first vehicle; o is->The number of driving in the interval e E [1,O ]]；W e Predicted vehicle weight for the e-th vehicle; />、/>、/>Is a preset adjustment coefficient; />For load displacement influencing functions +.>As a load angle influence function; />、/>、/>Component coefficients of X, Y, Z axes respectively;
the process of the analysis module for potential risk analysis further comprises:
will be、/>、/>、/>Respectively and->、/>、/>、/>And (3) performing comparison:
if it is、/>、/>And->Judging that the potential risk analysis result is normal;
otherwise, judging that the potential risk analysis result is abnormal.
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| CN110322690A (en) * | 2019-06-17 | 2019-10-11 | 西北工业大学 | A kind of sinking section ponding condition monitoring early warning system and its prediction and warning method |
| CN112414393A (en) * | 2020-10-21 | 2021-02-26 | 衢州学院 | Boundary pile state monitoring method and device based on multi-element sensor |
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