CN117351706A - Highway number monitoring and data closed-loop analysis system - Google Patents
Highway number monitoring and data closed-loop analysis system Download PDFInfo
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- CN117351706A CN117351706A CN202311283603.2A CN202311283603A CN117351706A CN 117351706 A CN117351706 A CN 117351706A CN 202311283603 A CN202311283603 A CN 202311283603A CN 117351706 A CN117351706 A CN 117351706A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/165—Anti-collision systems for passive traffic, e.g. including static obstacles, trees
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Abstract
The invention discloses a road number monitoring and data closed-loop analysis system, which belongs to the technical field of road data acquisition, and relates to an integrated data closed-loop analysis system based on acquisition, control and communication.
Description
Technical Field
The invention relates to the technical field of road data acquisition, in particular to a road number monitoring and data closed-loop analysis system.
Background
At present, road data of a road are generally collected by using a road condition inspection vehicle, however, the existing road condition inspection vehicle has the following defects: the camera is usually fixed on the top of the car body and exposed outside, and is often subjected to sunburn and rain, so that the service life of the camera is lower, aerial photogrammetry can be carried out by using an aerial survey unmanned aerial vehicle later, and aerial survey of the unmanned aerial vehicle is shortened, specifically, the aerial photography instrument is used for continuously shooting pictures on the ground on the unmanned aerial vehicle, and the steps of ground control point measurement, adjustment and drawing, three-dimensional plotting and the like are combined to draw a topographic map. However, due to the fact that a route is not reasonably planned, the unmanned aerial vehicle is unreasonable in flight route, and therefore a lot of resources are wasted.
Disclosure of Invention
The invention overcomes the defects of the prior art and makes the following improvements and optimizations aiming at the defects of the prior art.
The aim of the invention is achieved by the following technical scheme:
the invention provides a highway number monitoring and data closed-loop analysis system which is characterized by comprising an acquisition module, a control module, a communication module, a driving module and a photovoltaic power supply module which are sequentially connected;
the acquisition module comprises an unmanned aerial vehicle, and the unmanned aerial vehicle is used for acquiring highway data by carrying a camera;
the control module is used for obtaining a corresponding control signal according to the highway data sent by the acquisition module, sending the control signal to the driving module through the communication module, thereby intelligently controlling the flight track of the unmanned aerial vehicle and alarming the roadblock or other obstacles on the highway, and arranging a warning device at the front end of the roadblock or other obstacles;
the communication module is used for sending the control signal of the control module to the driving module;
the driving module is used for controlling the flight track of the unmanned aerial vehicle and driving the unmanned aerial vehicle to set a warning device at the front end of the roadblock or other obstacles according to the control signal of the control module;
the photovoltaic power supply module is used for supplying power to the acquisition module, the control module, the communication module and the driving module.
Preferably, the unmanned aerial vehicle is equipped with a camera, a temperature sensor, a humidity sensor, a distance sensor and a warning device.
Preferably, the control module comprises a central processing unit, a timer and an alarm unit, wherein the central processing unit is used for processing the information sent by the acquisition module, and the timer is used for recording the flight time of each unmanned aerial vehicle and simultaneously recording the charging duration of the rest unmanned aerial vehicles; the alarm unit is used for sending out alarm signals to other vehicles running in the highway through the unmanned aerial vehicle through the obstacle in the highway detected by the acquisition module.
Preferably, the communication module is arranged on the unmanned aerial vehicle and is used for carrying out communication networking with other unmanned aerial vehicle nodes.
Preferably, the photovoltaic power supply module comprises a thin film solar panel, a driving circuit and a rear-stage circuit which are sequentially connected.
More preferably, the input signals of the driving circuit consist of 3 high-side input signals VHI1, VHI2, VHI3 and 3 low-side input signals VLI1, VLI2, VLI3, which are respectively used for controlling the on-off of upper and lower bridge arms of the three-phase half-bridge, the input signals of the thin film solar cell panel are converted into 0-5 v square waves and are subjected to filtering shaping, then dead time for preventing the upper and lower bridge arms from being simultaneously conducted is generated through the dead time generating circuit, after high-side and low-side output voltage signals are formed, the high-side and low-side output voltage signals are input into corresponding IGBT devices, and finally electric energy is input into the unmanned aerial vehicle or the energy storage battery.
Preferably, the control module establishes a LightGBM model, and is based on an improved whale algorithm, and is used for controlling the flight trajectory of the unmanned aerial vehicle, and specifically comprises:
s1, initializing model parameters and population;
s2, training a LightGBM model, and calculating the individual fitness f of each whale according to an objective function i ;
S3, finding and recording the optimal position and the optimal value X in the population best ;
S4, updating the nonlinear convergence factor alpha and updating the coefficient vectorAnd->
Wherein,alpha is nonlinear convergence factor, r is interval [0,1]A random number vector within;
s5, judging whether p is smaller than 0.5, if not, updating the whale position according to the following formula;
where t represents the current number of iterations,indicating the current position +.>Representing the updated position, b being a spiral search shape parameter; l is interval [ -1,1]Random number in->A direction vector representing the position of the worst whale to the current position;
if yes, judging whether the absolute A is smaller than 1, and if not smaller than 1, updating the whale position according to the following formula;
wherein,for randomly selected whale individual positions in the current whale population,/->For a target whale individual position in the current whale population,
otherwise updating the whale position according to the following formula, and repeating the steps S4 and S5;
wherein,the position of the optimal whale in the current whale population;
and S6, when the maximum iteration times are reached, outputting an optimal individual and an adaptive degree value thereof to establish an optimal LightGBM model by using the output optimal parameter combination, and using the optimal LightGBM model for predicting tasks.
More preferably, the fitness of each whale position is calculated, new optimal and worst solutions are stored, and the iteration times are increased by 1; if the maximum iteration number is reached, stopping the circulation, otherwise, returning to the initial position, and taking the position of the leader as the optimal parameter.
The invention provides a highway number monitoring and data closed-loop analysis system, which is characterized in that highway data are collected by an unmanned aerial vehicle of a collection module, a control module based on a whale optimization algorithm is carried and used for controlling the flight track of the unmanned aerial vehicle, the algorithm has higher prediction accuracy, the resource waste can be effectively reduced, an optimal route can be accurately found by the optimal unmanned aerial vehicle, the closed loop is completed, and the power is efficiently used by a photovoltaic power supply module.
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 a road number monitoring and data closed-loop analysis system according to the present invention;
FIG. 2 is a schematic diagram of a whale optimization procedure according to the present invention;
fig. 3 is a schematic structural diagram of a photovoltaic power module according to the present invention.
Detailed Description
A road number monitoring and data closed loop analysis system is described in further detail below in connection with specific embodiments, which are for comparison and explanation purposes only, and the present invention is not limited to these embodiments.
In the description of the present invention, it should be understood that the directions or positional relationships indicated by the terms "upper", "lower", "left", "right", "top", "bottom", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
In one embodiment, the invention provides a road number monitoring and data closed-loop analysis system, as shown in fig. 1, which is characterized by comprising an acquisition module, a control module, a communication module, a driving module and a photovoltaic power supply module which are sequentially connected;
the acquisition module comprises an unmanned aerial vehicle, and the unmanned aerial vehicle is used for acquiring highway data by carrying a camera;
the control module is used for obtaining a corresponding control signal according to the highway data sent by the acquisition module, sending the control signal to the driving module through the communication module, thereby intelligently controlling the flight track of the unmanned aerial vehicle and alarming the roadblock or other obstacles on the highway, and arranging a warning device at the front end of the roadblock or other obstacles;
the communication module is used for sending the control signal of the control module to the driving module;
the driving module is used for controlling the flight track of the unmanned aerial vehicle and driving the unmanned aerial vehicle to set a warning device at the front end of the roadblock or other obstacles according to the control signal of the control module;
the photovoltaic power supply module is used for supplying power to the acquisition module, the control module, the communication module and the driving module.
Preferably, the unmanned aerial vehicle is equipped with a camera, a temperature sensor, a humidity sensor, a distance sensor and a warning device.
Preferably, the control module comprises a central processing unit, a timer and an alarm unit, wherein the central processing unit is used for processing the information sent by the acquisition module, and the timer is used for recording the flight time of each unmanned aerial vehicle and simultaneously recording the charging duration of the rest unmanned aerial vehicles; the alarm unit is used for sending out alarm signals to other vehicles running in the highway through the unmanned aerial vehicle through the obstacle in the highway detected by the acquisition module.
Preferably, the communication module is arranged on the unmanned aerial vehicle and is used for carrying out communication networking with other unmanned aerial vehicle nodes.
Preferably, the photovoltaic power supply module comprises a thin film solar panel, a driving circuit and a rear-stage circuit which are sequentially connected.
More preferably, as shown in fig. 3, the input signal of the driving circuit is composed of 3 high-side input signals VHI1, VHI2, VHI3 and 3 low-side input signals VLI1, VLI2, VLI3, which are respectively used for controlling the on-off of the upper bridge arm and the lower bridge arm of the three-phase half-bridge, converting the input signal of the thin-film solar panel into 0-5 v square wave, filtering and shaping, generating a dead time for preventing the upper bridge arm and the lower bridge arm from being simultaneously conducted through the dead time generating circuit, forming high-side and low-side output voltage signals, inputting the high-side output voltage signals into corresponding IGBT devices, and finally inputting electric energy into the unmanned aerial vehicle or the energy storage battery.
Preferably, as shown in fig. 2, the control module establishes a LightGBM model, and is based on an improved whale algorithm, and is used for controlling the flight trajectory of the unmanned aerial vehicle, and specifically includes:
s1, initializing model parameters and population;
s2, training a LightGBM model, and calculating the individual fitness f of each whale according to an objective function i ;
S3, finding and recording the optimal position and the optimal value X in the population best ;
S4, updating the nonlinear convergence factor alpha and updating the coefficient vectorAnd->
Wherein,alpha is nonlinear convergence factor, r is interval [0,1]A random number vector within;
s5, judging whether p is smaller than 0.5, if not, updating the whale position according to the following formula;
where t represents the current number of iterations,indicating the current position +.>Representing the updated position, b being a spiral search shape parameter; l is interval [ -1,1]Random number in->A direction vector representing the position of the worst whale to the current position;
if yes, judging whether the absolute A is smaller than 1, and if not smaller than 1, updating the whale position according to the following formula;
wherein,for randomly selected whale individual positions in the current whale population,/->For a target whale individual position in the current whale population,
otherwise updating the whale position according to the following formula, and repeating the steps S4 and S5;
wherein,the position of the optimal whale in the current whale population;
and S6, when the maximum iteration times are reached, outputting an optimal individual and an adaptive degree value thereof to establish an optimal LightGBM model by using the output optimal parameter combination, and using the optimal LightGBM model for predicting tasks.
More preferably, the fitness of each whale position is calculated, new optimal and worst solutions are stored, and the iteration times are increased by 1; if the maximum iteration number is reached, stopping the circulation, otherwise, returning to the initial position, and taking the position of the leader as the optimal parameter.
In an embodiment, unmanned aerial vehicles numbered 1 and 2 are executing tasks, receiving a control instruction sent by a control module, controlling the unmanned aerial vehicle numbered 1 to return to a charging position for charging although the unmanned aerial vehicle is at the nearest position due to insufficient electric quantity, enabling the unmanned aerial vehicle numbered 2 to be the optimal unmanned aerial vehicle, reaching a designated position through an optimal route, setting a warning device beside an obstacle, sending an alarm signal to other vehicles running in a highway, and then collecting highway data; and after the task is finished, executing the next task or returning to the charging place according to the control module to finish the closed loop of the system.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the scope of the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (8)
1. The highway number monitoring and data closed-loop analysis system is characterized by comprising an acquisition module, a control module, a communication module, a driving module and a photovoltaic power supply module which are connected in sequence;
the acquisition module comprises an unmanned aerial vehicle, and the unmanned aerial vehicle is used for acquiring highway data by carrying a camera;
the control module is used for obtaining a corresponding control signal according to the highway data sent by the acquisition module, sending the control signal to the driving module through the communication module, thereby intelligently controlling the flight track of the unmanned aerial vehicle and alarming the roadblock or other obstacles on the highway, and arranging a warning device at the front end of the roadblock or other obstacles;
the communication module is used for sending the control signal of the control module to the driving module;
the driving module is used for controlling the flight track of the unmanned aerial vehicle and driving the unmanned aerial vehicle to set a warning device at the front end of the roadblock or other obstacles according to the control signal of the control module;
the photovoltaic power supply module is used for supplying power to the acquisition module, the control module, the communication module and the driving module.
2. The highway number monitoring and data closed-loop analysis system according to claim 1, wherein the unmanned aerial vehicle is equipped with a camera, a temperature sensor, a humidity sensor, a distance sensor and a warning device.
3. The highway number monitoring and data closed-loop analysis system according to claim 1, wherein the control module comprises a central processing unit, a timer and an alarm unit, wherein the central processing unit is used for processing information sent by the acquisition module, and the timer is used for recording the flight time of each unmanned aerial vehicle and simultaneously recording the charging duration of the rest unmanned aerial vehicles; the alarm unit is used for sending out alarm signals to other vehicles running in the highway through the unmanned aerial vehicle through the obstacle in the highway detected by the acquisition module.
4. The highway number monitoring and data closed-loop analysis system according to claim 1, wherein the communication module is arranged on the unmanned aerial vehicle and is used for communication networking with other unmanned aerial vehicle nodes.
5. The highway number monitoring and data closed-loop analysis system according to claim 1, wherein the photovoltaic power supply module comprises a thin film solar panel, a driving circuit and a post-stage circuit which are sequentially connected.
6. The highway number monitoring and data closed-loop analysis system according to claim 5, wherein the input signals of the driving circuit consist of 3 high-side input signals VHI1, VHI2, VHI3 and 3 low-side input signals VLI1, VLI2 and VLI3, which are respectively used for controlling the on-off of upper and lower bridge arms of a three-phase half-bridge, the input signals of the thin film solar cell panel are converted into square waves with the voltage of 0-5 v and are subjected to filtering shaping, then dead time for preventing the upper and lower bridge arms from being simultaneously conducted is generated through a dead time generating circuit, the output voltage signals of the high and low sides are formed and then are input into corresponding IGBT devices, and finally electric energy is input into an unmanned aerial vehicle or an energy storage battery.
7. The highway number monitoring and data closed-loop analysis system according to claim 1, wherein the control module establishes a LightGBM model, and is based on an improved whale algorithm, and is used for controlling the flight trajectory of the unmanned aerial vehicle, and specifically comprises:
s1, initializing model parameters and population;
s2, training a LightGBM model, and calculating individual fitness f of each whale according to an objective function;
s3, finding and recording the optimal position and the optimal value X in the population best ;
S4, updating the nonlinear convergence factor alpha and updating the coefficient vectorAnd->
Wherein,alpha is nonlinear convergence factor, r is interval [0,1]A random number vector within;
s5, judging whether p is smaller than 0.5, if not, updating the whale position according to the following formula;
where t represents the current number of iterations,indicating the current position +.>Representing the updated position, b being a spiral search shape parameter; l is interval [ -1,1]Random number in->A direction vector representing the position of the worst whale to the current position;
if yes, judging whether the absolute A is smaller than 1, and if not smaller than 1, updating the whale position according to the following formula;
wherein,for randomly selected whale individual positions in the current whale population,/->For a target whale individual position in the current whale population,
otherwise updating the whale position according to the following formula, and repeating the steps S4 and S5;
wherein,the position of the optimal whale in the current whale population;
and S6, when the maximum iteration times are reached, outputting an optimal individual and an adaptive degree value thereof to establish an optimal LightGBM model by using the output optimal parameter combination, and using the optimal LightGBM model for predicting tasks.
8. The highway number monitoring and data closed loop analysis system according to claim 7 wherein the fitness of each whale position is calculated and new optimal and worst solutions are stored with the number of iterations added to 1; if the maximum iteration number is reached, stopping the circulation, otherwise, returning to the initial position, and taking the position of the leader as the optimal parameter.
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Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102156267A (en) * | 2011-01-18 | 2011-08-17 | 东南大学 | Experimental device for high-power photovoltaic grid-connected inverter |
CN206532417U (en) * | 2017-01-17 | 2017-09-29 | 长安大学 | A kind of highway driving environment automatic Synthesis monitor warning systems based on unmanned plane |
CN109753082A (en) * | 2018-12-29 | 2019-05-14 | 北京邮电大学 | Multiple no-manned plane network cooperating communication means |
CN112734130A (en) * | 2021-01-21 | 2021-04-30 | 河北工业大学 | Fault early warning method for double-fed fan main shaft |
CN113848889A (en) * | 2021-09-09 | 2021-12-28 | 武汉工程大学 | Path planning method based on combination of whale optimization algorithm and artificial potential field method |
CN113885555A (en) * | 2021-09-14 | 2022-01-04 | 安徽送变电工程有限公司 | Multi-machine task allocation method and system for power transmission line dense channel routing inspection |
CN115100863A (en) * | 2022-06-23 | 2022-09-23 | 中国人民公安大学 | Road monitoring method, device, equipment and storage medium |
CN116822123A (en) * | 2023-03-03 | 2023-09-29 | 国网江西省电力有限公司电力科学研究院 | Photovoltaic power prediction method based on WPD-SE-MIC strategy |
-
2023
- 2023-10-07 CN CN202311283603.2A patent/CN117351706A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102156267A (en) * | 2011-01-18 | 2011-08-17 | 东南大学 | Experimental device for high-power photovoltaic grid-connected inverter |
CN206532417U (en) * | 2017-01-17 | 2017-09-29 | 长安大学 | A kind of highway driving environment automatic Synthesis monitor warning systems based on unmanned plane |
CN109753082A (en) * | 2018-12-29 | 2019-05-14 | 北京邮电大学 | Multiple no-manned plane network cooperating communication means |
CN112734130A (en) * | 2021-01-21 | 2021-04-30 | 河北工业大学 | Fault early warning method for double-fed fan main shaft |
CN113848889A (en) * | 2021-09-09 | 2021-12-28 | 武汉工程大学 | Path planning method based on combination of whale optimization algorithm and artificial potential field method |
CN113885555A (en) * | 2021-09-14 | 2022-01-04 | 安徽送变电工程有限公司 | Multi-machine task allocation method and system for power transmission line dense channel routing inspection |
CN115100863A (en) * | 2022-06-23 | 2022-09-23 | 中国人民公安大学 | Road monitoring method, device, equipment and storage medium |
CN116822123A (en) * | 2023-03-03 | 2023-09-29 | 国网江西省电力有限公司电力科学研究院 | Photovoltaic power prediction method based on WPD-SE-MIC strategy |
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