CN116738319A - Expressway vehicle tire burst early warning device and method - Google Patents

Expressway vehicle tire burst early warning device and method Download PDF

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CN116738319A
CN116738319A CN202310764865.4A CN202310764865A CN116738319A CN 116738319 A CN116738319 A CN 116738319A CN 202310764865 A CN202310764865 A CN 202310764865A CN 116738319 A CN116738319 A CN 116738319A
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data
tire
vehicle
temperature
microcontroller
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赵亮
李海锦
秦笑
赵淑同
李宜达
熊梓姗
李楷烨
丁允哲
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Shandong Jiaotong University
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
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    • G—PHYSICS
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    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/0022—Radiation pyrometry, e.g. infrared or optical thermometry for sensing the radiation of moving bodies
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/08—Systems determining position data of a target for measuring distance only
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
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    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/0022—Radiation pyrometry, e.g. infrared or optical thermometry for sensing the radiation of moving bodies
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Abstract

The invention discloses a highway vehicle tire burst early warning device and a method, wherein the device comprises an information acquisition module, a microcontroller, a warning device and a video detection module, wherein the information acquisition module is arranged on two sides of a highway lane and is used for detecting a running vehicle in real time and acquiring temperature data of a running vehicle tire; the microcontroller performs vehicle identification and abnormal analysis of the temperature of the vehicle tyre according to the real-time data sent by the information acquisition module; the warning device is used for timely warning the vehicle with abnormal tire temperature state; the video detection module is used for collecting license plate information of the vehicle with abnormal tire temperature and transmitting the license plate information to the warning device through the microcontroller for precise early warning; the information of the warning device for accurate early warning comprises license plate information of the vehicle with abnormal tire temperature and temperature field state data of the surface of the tire. The invention greatly improves the safety level of a driver driving on a highway by early warning the vehicle with abnormal temperature conditions of the vehicle tires.

Description

Expressway vehicle tire burst early warning device and method
Technical Field
The invention relates to a device and a method for early warning tire burst of a highway vehicle, and belongs to the technical field of highway traffic safety.
Background
When an automobile runs on a road, if the temperature of the tire is too high, the tire burst is likely to be caused, the automobile is out of control, the safety hazard to the road is extremely high, and traffic accidents are easily caused. According to the related report investigation, traffic accidents caused by tire burst are very common every year, and become a big factor threatening the life safety of traffic participants; in the statistics of tire burst accidents, a considerable part of accidents are related to the excessive temperature of the tire.
The prior devices which are used in the market and have relatively shallow researches mainly comprise equipment installed in a vehicle, and mainly comprise methods of predicting cracks on a tire in advance, detecting metal objects inserted into the tire and the like. The prevention method has the problems of complicated detection steps, poor warning effect, easiness in damage caused by bumping and collision of the vehicle and the like.
At present, the lack of the vehicle tire burst early warning equipment arranged on the road causes that the road safety management department cannot make corresponding early warning on tire burst, and the road safety is affected.
Disclosure of Invention
In order to solve the problems, the invention provides a device and a method for early warning the tire burst of a highway vehicle, which can early warn the vehicle with abnormal tire temperature conditions and ensure the driving safety on the highway.
The technical scheme adopted for solving the technical problems is as follows:
in a first aspect, the invention provides a tire burst early warning device for a highway vehicle, which comprises an information acquisition module, a microcontroller, a warning device and a video detection module, wherein the information acquisition module is connected with the microcontroller, and is arranged on two sides of a highway lane and used for detecting a running vehicle in real time and acquiring temperature data of a tire of the running vehicle; the microcontroller performs vehicle identification and abnormal analysis of the temperature of the vehicle tyre according to the real-time data sent by the information acquisition module; the warning device is used for timely warning the vehicle with abnormal tire temperature state; the video detection module is used for collecting license plate information of the vehicle with abnormal tire temperature and transmitting the license plate information to the warning device through the microcontroller for precise early warning; the information of the warning device for accurate early warning comprises license plate information of the vehicle with abnormal tire temperature and temperature field state data of the surface of the tire; the warning device and the video detection module are connected with the microcontroller through the ZigBee information transmission module.
As one possible implementation manner of this embodiment, the information acquisition module includes a laser ranging sensor and an infrared thermal imager, where the laser ranging sensor is used to detect whether a moving object on the highway is a driving vehicle, and the infrared thermal imager measures the detected tire temperature state of the driving vehicle and acquires the tire surface temperature data and the tire surface temperature field area data of the driving vehicle.
As one possible implementation manner of the embodiment, the microcontroller judges whether the mobile object is a running vehicle according to the detection data of the laser ranging sensor; after judging that the moving object is a running vehicle, the microcontroller drives the infrared thermal imager to detect the temperature field state of the surface of the tire of the running vehicle, the microcontroller analyzes the temperature field state data of the surface of the tire of the running vehicle and compares the data with a set threshold value, if the threshold value is reached, the laser ranging sensor detects the data to judge a specific lane of the running vehicle and starts a video detection module of a corresponding lane, the video detection module captures the license plate number of the running vehicle and sends license plate information of the running vehicle to the microcontroller, and the microcontroller sends vehicle license plate information with abnormal tire temperature state and the temperature field state information of the surface of the tire to the warning device for accurate early warning of vehicle tire burst.
As a possible implementation manner of the embodiment, the microcontroller is connected with the internet of things transmission module, the microcontroller is connected with the background server through the internet of things transmission module, the microcontroller transmits tire surface temperature data and tire surface temperature field area data to the background server through the internet of things transmission module, the background server stores the tire temperature data acquired by the information acquisition module, analyzes the tire temperature data to form a data cluster and then sends the data cluster to the microcontroller to be used as a sample data cluster, and the microcontroller judges whether the tire burst risk exists or not by comparing the tire burst temperature threshold value and the tire temperature field area threshold value which are set in the database.
As a possible implementation manner of this embodiment, the microcontroller, the internet of things transmission module and the information acquisition module are installed on the detection upright posts on two sides of the same-directional lane of the expressway.
As a possible implementation manner of this embodiment, the process that the background server stores the tire temperature data collected by the information collecting module and analyzes the tire temperature data to form a data cluster specifically includes:
the tire surface temperature data and the tire surface temperature field area data are formed into a data set A (X, Y), wherein X represents the temperature value of the tire surface, and Y represents the size of the tire surface temperature field area;
the data set a (X, Y) is categorized, and the data points are categorized into data clusters.
As a possible implementation manner of this embodiment, the specific process of classifying the data sets a (X, Y) into the data clusters is as follows:
screening target data points of a data set, wherein the target data points comprise core data points, boundary data points and outlier data points, and the core data points have at least the number of data points with minimum distance in the adjacent distance of the core data points: the boundary data points are positioned at the edges of the data set, and the number of surrounding data points is less than the minimum cluster point minPoints; the outlier data points are located in a low density region of the data set;
clustering the screened data sets;
dynamically establishing whether the clustered data points are core points or not, and then setting the minimum cluster point to be greater than or equal to the dimension of the data set;
establishing a cluster maximum radius of the key parameters by using the Euclidean distance method;
judging whether data points which are more than or equal to the minimum cluster point exist around the maximum radius of the data point cluster by utilizing the established maximum radius value of the cluster, if so, using the data points as a data cluster,
and continuing to cluster the rest data points until all the data points are clustered, and obtaining the categorized data clusters.
As a possible implementation manner of this embodiment, the categorized data cluster determines, through a contour coefficient s (i), whether the data cluster meets a clustering requirement:
、
where a (i) is the average distance of sample i from other samples in the same cluster, where a smaller a (i) indicates that sample i should be clustered into the data cluster; b (i) is the inter-cluster dissimilarity of sample i: b (i) =min (b (i 1), b (i 2), b (ik)), calculating the average distance bij of the sample i to all samples of some other cluster Cj, and the minimum value of the average distance bij is called the dissimilarity between the sample i and the cluster Cj;
if the contour coefficient s (i) is close to 1, the sample i is reasonably clustered; if the contour coefficient s (i) is close to-1, it is indicated that sample i should be more classified into another cluster.
As one possible implementation manner of this embodiment, the process of the microcontroller analyzing the temperature field state data of the tire surface of the running vehicle and comparing the data with the set threshold value specifically includes:
placing the vehicle tire surface temperature data and the tire surface temperature field area data into a data set a (X, Y);
judging whether the data is a data noise point in the data set according to the classified data clusters, and if so, matching the data noise point with a set warning threshold; the warning threshold value comprises a tire burst temperature threshold value and a tire temperature field area threshold value, wherein the normal temperature of the tire burst temperature threshold value is [0 ℃,100℃ ]]The critical temperature is 100 ℃ and 121 DEG C]The dangerous temperature is [121 ℃, ++ infinity]The method comprises the steps of carrying out a first treatment on the surface of the The tire temperature field area threshold value is [102cm ] 2 ,+∞]；
If the data noise point is within the dangerous temperature range of the tire burst temperature threshold value or within the tire temperature field area threshold value, the tire of the vehicle is at risk of burst.
As one possible implementation manner of this embodiment, the information collecting modules have three groups, the distance between each group is 100m, and two information collecting modules of each group are installed on the detection upright posts on two sides of the same-directional lane of the expressway.
In a second aspect, the method for early warning of tire burst of a highway vehicle provided by the embodiment of the invention comprises the following steps:
acquiring time interval data of the moving object passing through the laser ranging sensor by using the laser ranging sensor and sending the time interval data to the microcontroller;
the microcontroller removes clutter in the time interval data by using a Kalman filtering algorithm, extracts effective time interval data, compares the effective time interval data with a set threshold value of whether the moving object is a driving vehicle, and judges that the moving object is the driving vehicle if the moving object accords with the threshold value of whether the moving object is the driving vehicle;
after detecting that a running vehicle exists, starting an infrared thermal imager, acquiring tire surface temperature data and tire surface temperature field area data of the running vehicle, and sending the tire surface temperature data and the tire surface temperature field area data to a microcontroller;
the microcontroller processes the tire surface temperature data and the tire surface temperature field area data by adopting a Kalman filtering algorithm and transmits the data to a background server;
the background server classifies the data set into data clusters and sends the data clusters to the microcontroller;
the microcontroller compares the tire burst temperature threshold value and the tire temperature field area threshold value which are set in the database and are classified into the data cluster, and judges whether the running vehicle has a tire burst risk or not;
if the running vehicle has a tire burst risk, starting a laser ranging sensor, detecting the distance between the running vehicle and the laser ranging sensor, judging the lane where the running vehicle is located, starting a video detection module of the lane where the running vehicle is located, recording the license plate number of the vehicle with the tire burst risk, and sending the license plate number to a warning device;
the warning device combines the acquired license plate information with warning information, and the vehicle driver is accurately warned in a mode of voice warning and display screen warning.
As one possible implementation manner of this embodiment, the threshold value of whether the moving object is a running vehicle is [0.055s,0.11s ].
As a possible implementation manner of this embodiment, the specific process of classifying the data set into the data cluster by the background server is:
the tire surface temperature data and the tire surface temperature field area data are formed into a data set A (X, Y), wherein X represents the temperature value of the tire surface, and Y represents the size of the tire surface temperature field area;
the data set a (X, Y) is categorized, and the data points are categorized into data clusters.
As a possible implementation manner of this embodiment, the specific process of classifying the data sets a (X, Y) into the data clusters is as follows:
screening target data points of a data set, wherein the target data points comprise core data points, boundary data points and outlier data points, and the core data points have at least the number of data points with minimum distance in the adjacent distance of the core data points: the boundary data points are positioned at the edges of the data set, and the number of surrounding data points is less than the minimum cluster point minPoints; the outlier data points are located in a low density region of the data set;
clustering the screened data sets;
dynamically establishing whether the clustered data points are core points or not, and then setting the minimum cluster point to be greater than or equal to the dimension of the data set;
establishing a cluster maximum radius of the key parameters by using the Euclidean distance method;
judging whether data points which are more than or equal to the minimum cluster point exist around the maximum radius of the data point cluster by utilizing the established maximum radius value of the cluster, if so, using the data points as a data cluster,
and continuing to cluster the rest data points until all the data points are clustered, and obtaining the categorized data clusters.
As a possible implementation manner of this embodiment, the categorized data cluster determines, through a contour coefficient s (i), whether the data cluster meets a clustering requirement:
、
where a (i) is the average distance of sample i from other samples in the same cluster, where a smaller a (i) indicates that sample i should be clustered into the data cluster; b (i) is the inter-cluster dissimilarity of sample i: b (i) =min (b (i 1), b (i 2), b (ik)), calculating the average distance bij of the sample i to all samples of some other cluster Cj, j=1, 2..k, the minimum value of the average distance bij being the dissimilarity of the sample i with the cluster Cj;
if the contour coefficient s (i) is close to 1, the sample i is reasonably clustered; if the contour coefficient s (i) is close to-1, it is indicated that sample i should be more classified into another cluster.
As a possible implementation manner of this embodiment, the process of determining whether the running vehicle has a tire burst risk by using the microcontroller to classify the running vehicle into the tire burst temperature threshold and the tire temperature field area threshold set in the data cluster comparison database specifically includes:
placing the vehicle tire surface temperature data and the tire surface temperature field area data into a data set a (X, Y);
judging whether the data is a number or not according to the classified data clustersAccording to the concentrated data noise points, if so, matching the data noise points with the set warning threshold; the warning threshold value comprises a tire burst temperature threshold value and a tire temperature field area threshold value, wherein the normal temperature of the tire burst temperature threshold value is [0 ℃,100℃ ]]The critical temperature is 100 ℃ and 121 DEG C]The dangerous temperature is [121 ℃, ++ infinity]The method comprises the steps of carrying out a first treatment on the surface of the The tire temperature field area threshold value is [102cm ] 2 ,+∞]；
If the data noise point is within the dangerous temperature range of the tire burst temperature threshold value or within the tire temperature field area threshold value, the tire of the vehicle is at risk of burst.
The technical scheme of the embodiment of the invention has the following beneficial effects:
the technical scheme of the invention provides a tire burst early warning device for a highway vehicle, which comprises an information acquisition module, a microcontroller, a warning device and a video detection module, wherein the information acquisition module is connected with the microcontroller, and is arranged on two sides of a highway lane and used for detecting a running vehicle in real time and acquiring temperature data of a tire of the running vehicle; the microcontroller performs vehicle identification and abnormal analysis of the temperature of the vehicle tyre according to the real-time data sent by the information acquisition module; the warning device is used for timely warning the vehicle with abnormal tire temperature state; the video detection module is used for collecting license plate information of the vehicle with abnormal tire temperature and transmitting the license plate information to the warning device through the microcontroller for precise early warning; the information of the warning device for accurate early warning comprises license plate information of the vehicle with abnormal tire temperature and temperature field state data of the surface of the tire; the warning device and the video detection module are connected with the microcontroller through the ZigBee information transmission module. The invention greatly improves the safety level of a driver driving on a highway by early warning the vehicle with abnormal temperature conditions of the vehicle tires, and the device is also suitable for various highway sections and has strong universality.
The invention judges whether the data is the data noise point, judges whether the tire burst risk exists or not by adopting the data noise point and the set warning threshold value, and greatly improves the accuracy and the precision of judging whether the tire burst risk exists or not by adopting the DBSCAN algorithm to analyze and process the temperature data of the tire of the running vehicle, effectively and timely detects the vehicle with the tire burst risk, simultaneously realizes timely early warning, greatly reduces traffic accidents caused by the tire burst of the vehicle, and powerfully ensures traffic safety.
The invention uses the algorithm control and information transmission module, reduces human intervention to the greatest extent, and effectively solves the problems of poor detection precision and low service life of products in the market.
Drawings
FIG. 1 is a schematic diagram of an expressway vehicle puncture warning device, according to an exemplary embodiment;
FIG. 2 is a schematic diagram of a structure of a test post and test device according to an exemplary embodiment;
FIG. 3 is a schematic diagram illustrating the installation of a test post according to an exemplary embodiment;
FIG. 4 is a schematic diagram illustrating an installation structure of a warning device according to an exemplary embodiment;
FIG. 5 is a flow chart illustrating a method of warning of a tire burst of a highway vehicle according to an exemplary embodiment;
in the figure, A is a group A detection point, B is a group B detection point, C is a group C detection point, 1 is a detection upright post, 2 is a warning device and a video detection device, 3 is an LED display screen, 4 is a voice warning device, 5 is a zigbee information transmission module, 6 is a video detection device, 7 is a solar panel, 8 is a laser ranging sensor, 9 is an infrared thermal imager, 10 is a microcontroller and an Internet of things transmission module, and 11 is a storage battery.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
in order to clearly illustrate the technical features of the present solution, the present invention will be described in detail below with reference to the following detailed description and the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different structures of the invention. In order to simplify the present disclosure, components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and processes are omitted so as to not unnecessarily obscure the present invention.
As shown in fig. 1, the expressway vehicle tire burst early warning device provided by the embodiment of the invention comprises an information acquisition module, a microcontroller, a warning device and a video detection module, wherein the information acquisition module is connected with the microcontroller and is arranged on two sides of an expressway lane and used for detecting a running vehicle in real time and acquiring temperature data of a running vehicle tire; the microcontroller performs vehicle identification and abnormal analysis of the temperature of the vehicle tyre according to the real-time data sent by the information acquisition module; the warning device is used for timely warning the vehicle with abnormal tire temperature state; the video detection module is used for collecting license plate information of the vehicle with abnormal tire temperature and transmitting the license plate information to the warning device through the microcontroller for precise early warning; the information of the warning device for accurate early warning comprises license plate information of the vehicle with abnormal tire temperature and temperature field state data of the surface of the tire; the warning device and the video detection module are connected with the microcontroller through the ZigBee information transmission module.
As a possible implementation manner of this embodiment, as shown in fig. 1 and 2, the information acquisition module includes a laser ranging sensor 8 and a thermal infrared imager 9, where the laser ranging sensor 8 is used to detect whether a moving object on a highway is a driving vehicle, and the thermal infrared imager 9 measures the detected tire temperature state of the driving vehicle and acquires the tire surface temperature data and the tire surface temperature field area data of the driving vehicle. The infrared thermal imager can adopt FOTRIC 686 series thermal imagers. The principle of detecting whether a moving object on a highway is a running vehicle is as follows: when a moving object passes, the time length for shielding the laser ranging sensor is recorded, then the time length is compared with a threshold value in a database from time to time, and if the time length is consistent with the threshold value, the passing of the running vehicle is judged.
As one possible implementation manner of the embodiment, the microcontroller judges whether the mobile object is a running vehicle according to the detection data of the laser ranging sensor; after judging that the moving object is a running vehicle, the microcontroller drives the infrared thermal imager to detect the temperature field state of the surface of the tire of the running vehicle, the microcontroller analyzes the temperature field state data of the surface of the tire of the running vehicle and compares the data with a set threshold value, if the threshold value is reached, the laser ranging sensor detects the data to judge a specific lane of the running vehicle and starts a video detection module of a corresponding lane, the video detection module captures the license plate number of the running vehicle and sends license plate information of the running vehicle to the microcontroller, and the microcontroller sends vehicle license plate information with abnormal tire temperature state and the temperature field state information of the surface of the tire to the warning device for accurate early warning of vehicle tire burst.
As a possible implementation manner of the embodiment, as shown in fig. 1, the microcontroller is connected with an internet of things transmission module, the microcontroller is connected with a background server through the internet of things transmission module, the microcontroller transmits tire surface temperature data and tire surface temperature field area data to the background server through the internet of things transmission module, the background server stores the tire temperature data collected by the information collection module, analyzes the tire temperature data to form a data cluster and then sends the data cluster to the microcontroller to be used as a sample data cluster, and the microcontroller judges whether the tire burst risk exists or not by comparing the tire burst temperature threshold value and the tire surface temperature field area threshold value which are set in the database. The microcontroller can adopt STC15 series singlechip, thing networking transmission module can adopt zigBee thing networking transmission module.
As a possible implementation manner of this embodiment, as shown in fig. 4, the warning device includes an LED display screen 3 and a voice warning device 4. The warning device and the video detection module can be arranged at the top of a toll station or on an expressway portal frame information board. The warning device is connected with the information transmission module, and timely and accurate double warning is carried out on the vehicle by receiving the warning information sent by the information acquisition device.
As a possible implementation manner of this embodiment, the microcontroller, the internet of things transmission module and the information acquisition module are installed on the detection upright posts on two sides of the same-directional lane of the expressway, as shown in fig. 2 and 3. As shown in fig. 3, the detection upright post is further provided with a power supply unit for providing working power for the microcontroller, the internet of things transmission module and the information acquisition module, and the power supply unit comprises a storage battery 11 and a solar cell panel 7, wherein the storage battery pack is positioned at the bottom of the upright post, and the solar cell panel is positioned at the upper end of the upright post.
As a possible implementation manner of this embodiment, the process that the background server stores the tire temperature data collected by the information collecting module and analyzes the tire temperature data to form a data cluster specifically includes:
the tire surface temperature data and the tire surface temperature field area data are formed into a data set A (X, Y), wherein X represents the temperature value of the tire surface, and Y represents the size of the tire surface temperature field area;
the data set a (X, Y) is categorized, and the data points are categorized into data clusters.
As a possible implementation manner of this embodiment, the specific process of classifying the data sets a (X, Y) into the data clusters is as follows:
screening target data points of a data set, wherein the target data points comprise core data points, boundary data points and outlier data points, and the core data points have at least the number of data points with minimum distance in the adjacent distance of the core data points: the boundary data points are positioned at the edges of the data set, and the number of surrounding data points is less than the minimum cluster point minPoints; the outlier data points are located in a low density region of the data set;
clustering the screened data sets;
dynamically establishing whether the clustered data points are core points or not, and then setting the minimum cluster point to be greater than or equal to the dimension of the data set;
establishing a cluster maximum radius Epsilon of key parameters by using an Euclidean distance method;
judging whether data points which are more than or equal to the minimum cluster point exist around the maximum radius of the data point cluster by utilizing the established maximum radius value of the cluster, if so, using the data points as a data cluster,
and continuing to cluster the rest data points through the steps until all the data points are clustered, and obtaining the categorized data clusters.
As a possible implementation manner of this embodiment, the categorized data cluster determines, through a contour coefficient s (i), whether the data cluster meets a clustering requirement:
、
where a (i) is the average distance of sample i from other samples in the same cluster, where a smaller a (i) indicates that sample i should be clustered into the data cluster; b (i) is the inter-cluster dissimilarity of sample i: b (i) =min (b (i 1), b (i 2), b (ik)), calculating the average distance bij of the sample i to all samples of some other cluster Cj, and the minimum value of the average distance bij is called the dissimilarity between the sample i and the cluster Cj;
if the contour coefficient s (i) is close to 1, the sample i is reasonably clustered; if the contour coefficient s (i) is close to-1, it is indicated that sample i should be more classified into another cluster.
Two important parameters, minPointshe and Epsilon, are involved in the clustering of the algorithm, whether the data point is a core point is established, and then the minPointshe is set to be greater than or equal to the dimension of the data set. That is, the minuPointshe values of the features are determined by multiplying their dimension numbers by 2. After establishing the important parameter minPoints (minimum cluster points), the algorithm goes through Euclidean distance method. A key parameter Epsilon (cluster maximum radius) is established. The established Epsilon value is used for judging whether data points which are more than or equal to minPoints exist around the maximum radius of the data point cluster, if so, the data points are used as one data cluster, and then the rest data points are clustered through the steps until all the data points are clustered.
As one possible implementation manner of this embodiment, the process of the microcontroller analyzing the temperature field state data of the tire surface of the running vehicle and comparing the data with the set threshold value specifically includes:
placing the vehicle tire surface temperature data and the tire surface temperature field area data into a data set a (X, Y);
judging whether the data is a data noise point in the data set according to the classified data clusters, and if so, matching the data noise point with a set warning threshold; the warning threshold value comprises a tire burst temperature threshold value and a tire temperature field area threshold value, wherein the normal temperature of the tire burst temperature threshold value is [0 ℃,100℃ ]]The critical temperature is 100 ℃ and 121 DEG C]The dangerous temperature is [121 ℃, ++ infinity]The method comprises the steps of carrying out a first treatment on the surface of the The tire temperature field area threshold value is [102cm ] 2 ,+∞]；
If the data noise point is within the dangerous temperature range of the tire burst temperature threshold value or within the tire temperature field area threshold value, the tire of the vehicle is at risk of burst.
According to the invention, the DBSCAN algorithm is adopted to analyze and process the temperature data of the running vehicle tires, so that the accuracy and the precision of judging whether the vehicle has a tire burst risk or not are greatly improved, the vehicle with the tire burst risk is effectively and timely detected, meanwhile, timely early warning is realized, traffic accidents caused by the tire burst of the vehicle are greatly reduced, and the traffic safety is effectively ensured.
Most of the tire burst areas are at tire shoulder and tire side due to high temperature, so that the temperature sensor at the road side can detect the temperature at the tire crown and the temperature field area, and further the tire burst prevention effect can be achieved. According to the method, the temperature field image acquired by the thermal infrared imager is calculated by means of the Python OpenCV image recognition technology, so that the irregular temperature field area of the tire at the tire crown is acquired.
As a possible implementation manner of this embodiment, as shown in fig. 3, the information collecting modules include three groups A, B and C, where a distance between each group is 100m, and two information collecting modules of each group are installed on the detecting upright posts on two sides of the same-directional lane of the expressway.
The mounting mode of the expressway vehicle tire burst early warning device is as follows: a warning device is arranged at the entrance of the toll station; the video detection device is arranged outside the toll station entrance 100m, then the first group of information acquisition devices are arranged at the position 200m away from the toll station entrance, the information acquisition devices are respectively arranged at two sides of a road and used for acquiring vehicle information, and then the second group of information acquisition devices and the third group of information acquisition devices are respectively arranged at the positions 300m and 400m away from the toll station.
As shown in fig. 5, the method for early warning of tire burst of a highway vehicle provided by the embodiment of the invention comprises the following steps:
acquiring time interval data of the moving object passing through the laser ranging sensor by using the laser ranging sensor and sending the time interval data to the microcontroller;
the microcontroller removes clutter in the time interval data by using a Kalman filtering algorithm, extracts effective time interval data, compares the effective time interval data with a set threshold value of whether the moving object is a driving vehicle, and judges that the moving object is the driving vehicle if the moving object accords with the threshold value of whether the moving object is the driving vehicle;
after detecting that a running vehicle exists, starting an infrared thermal imager, acquiring tire surface temperature data and tire surface temperature field area data of the running vehicle, and sending the tire surface temperature data and the tire surface temperature field area data to a microcontroller;
the microcontroller processes the tire surface temperature data and the tire surface temperature field area data by adopting a Kalman filtering algorithm and transmits the data to a background server;
the background server classifies the data set into data clusters and sends the data clusters to the microcontroller;
the microcontroller compares the tire burst temperature threshold value and the tire temperature field area threshold value which are set in the database and are classified into the data cluster, and judges whether the running vehicle has a tire burst risk or not;
if the running vehicle has a tire burst risk, starting a laser ranging sensor, detecting the distance between the running vehicle and the laser ranging sensor, judging the lane where the running vehicle is located, starting a video detection module of the lane where the running vehicle is located, recording the license plate number of the vehicle with the tire burst risk, and sending the license plate number to a warning device;
the warning device combines the acquired license plate information with warning information, and the vehicle driver is accurately warned in a mode of voice warning and display screen warning.
As one possible implementation manner of this embodiment, the threshold value of whether the moving object is a running vehicle is [0.055s,0.11s ].
As a possible implementation manner of this embodiment, the specific process of classifying the data set into the data cluster by the background server is:
the tire surface temperature data and the tire surface temperature field area data are formed into a data set A (X, Y), wherein X represents the temperature value of the tire surface, and Y represents the size of the tire surface temperature field area;
the data set a (X, Y) is categorized, and the data points are categorized into data clusters.
As a possible implementation manner of this embodiment, the specific process of classifying the data sets a (X, Y) into the data clusters is as follows:
screening target data points of a data set, wherein the target data points comprise core data points, boundary data points and outlier data points, and the core data points have at least the number of data points with minimum distance in the adjacent distance of the core data points: the boundary data points are positioned at the edges of the data set, and the number of surrounding data points is less than the minimum cluster point minPoints; the outlier data points are located in a low density region of the data set;
clustering the screened data sets;
dynamically establishing whether the clustered data points are core points or not, and then setting the minimum cluster point to be greater than or equal to the dimension of the data set;
establishing a cluster maximum radius of the key parameters by using the Euclidean distance method;
judging whether data points which are more than or equal to the minimum cluster point exist around the maximum radius of the data point cluster by utilizing the established maximum radius value of the cluster, if so, using the data points as a data cluster,
and continuing to cluster the rest data points through the steps until all the data points are clustered, and obtaining the categorized data clusters.
As a possible implementation manner of this embodiment, the categorized data cluster determines, through a contour coefficient s (i), whether the data cluster meets a clustering requirement:
、
where a (i) is the average distance of sample i from other samples in the same cluster, where a smaller a (i) indicates that sample i should be clustered into the data cluster; b (i) is the inter-cluster dissimilarity of sample i: b (i) =min (b (i 1), b (i 2), b (ik)), calculating the average distance bij of the sample i to all samples of some other cluster Cj, and the minimum value of the average distance bij is called the dissimilarity between the sample i and the cluster Cj;
if the contour coefficient s (i) is close to 1, the sample i is reasonably clustered; if the contour coefficient s (i) is close to-1, it is indicated that sample i should be more classified into another cluster.
As a possible implementation manner of this embodiment, the process of determining whether the running vehicle has a tire burst risk by using the microcontroller to classify the running vehicle into the tire burst temperature threshold and the tire temperature field area threshold set in the data cluster comparison database specifically includes:
placing the vehicle tire surface temperature data and the tire surface temperature field area data into a data set a (X, Y);
judging whether the data is a data noise point in the data set according to the classified data clusters, and if so, matching the data noise point with a set warning threshold; the warning threshold value comprises a tire burst temperature threshold value and a tire temperature field area threshold value, wherein the normal temperature of the tire burst temperature threshold value is [0 ℃,100℃ ]]The critical temperature is 100 ℃ and 121 DEG C]The dangerous temperature is [121 ℃, ++ infinity]The method comprises the steps of carrying out a first treatment on the surface of the The tire temperature field area threshold value is [102cm ] 2 ,+∞]；
If the data noise point is within the dangerous temperature range of the tire burst temperature threshold value or within the tire temperature field area threshold value, the tire of the vehicle is at risk of burst.
According to the invention, two sensors are used for data output, so that the electronization of output information is realized; compared with other tire burst prevention methods installed in the vehicle tires and the vehicle body, the tire burst prevention method is more accurate and less affected; simultaneously, using a Kalman filtering algorithm to effectively filter abnormal data transmitted from a road; different from the traditional threshold detection method, the DBSCAN algorithm is adopted to more accurately and efficiently identify the tire state information, so that the vehicle is accurately pre-warned; the detection method can be used in various places such as urban and rural highways, mountain area curved roads, residential communities, underground parking lots and the like, and has a wide application range.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.

Claims (10)

1. The expressway vehicle tire burst early warning device is characterized by comprising an information acquisition module, a microcontroller, a warning device and a video detection module, wherein the information acquisition module is connected with the microcontroller and is arranged on two sides of an expressway lane and used for detecting a running vehicle in real time and acquiring temperature data of a running vehicle tire; the microcontroller performs vehicle identification and abnormal analysis of the temperature of the vehicle tyre according to the real-time data sent by the information acquisition module; the warning device is used for timely warning the vehicle with abnormal tire temperature state; the video detection module is used for collecting license plate information of the vehicle with abnormal tire temperature and transmitting the license plate information to the warning device through the microcontroller for precise early warning; the information of the warning device for accurate early warning comprises license plate information of the vehicle with abnormal tire temperature and temperature field state data of the surface of the tire; the warning device and the video detection module are connected with the microcontroller through the ZigBee information transmission module.
2. The expressway vehicle tire burst warning device according to claim 1, wherein the information acquisition module comprises a laser ranging sensor and an infrared thermal imager, the laser ranging sensor is used for detecting whether a moving object on the expressway is a running vehicle or not, the infrared thermal imager is used for measuring the detected temperature state of the running vehicle tire, and acquiring the surface temperature data of the running vehicle tire and the surface temperature field area data of the tire.
3. The expressway vehicle tire burst warning device according to claim 1, wherein the microcontroller judges whether the moving object is a running vehicle according to the detection data of the laser ranging sensor; after judging that the moving object is a running vehicle, the microcontroller drives the infrared thermal imager to detect the temperature field state of the surface of the tire of the running vehicle, the microcontroller analyzes the temperature field state data of the surface of the tire of the running vehicle and compares the data with a set threshold value, if the threshold value is reached, the laser ranging sensor detects the data to judge a specific lane of the running vehicle and starts a video detection module of a corresponding lane, the video detection module captures the license plate number of the running vehicle and sends license plate information of the running vehicle to the microcontroller, and the microcontroller sends vehicle license plate information with abnormal tire temperature state and the temperature field state information of the surface of the tire to the warning device for accurate early warning of vehicle tire burst.
4. The expressway vehicle tire burst early warning device according to claim 1, wherein the microcontroller is connected with an internet of things transmission module, the microcontroller is connected with a background server through the internet of things transmission module, the microcontroller transmits tire surface temperature data and tire surface temperature field area data to the background server through the internet of things transmission module, the background server stores the tire temperature data acquired by the information acquisition module, analyzes the tire temperature data to form a data cluster and then sends the data cluster to the microcontroller to serve as a sample data cluster, and the microcontroller judges whether tire burst risks exist in the vehicle by comparing the tire burst temperature threshold value and the tire surface temperature field area threshold value which are set in the database.
5. The expressway vehicle tire burst early warning device according to claim 4, wherein the microcontroller, the internet of things transmission module and the information acquisition module are installed on detection upright posts on two sides of an expressway homodromous lane.
6. The expressway vehicle tire burst early warning device according to claim 4, wherein the process of storing the tire temperature data collected by the information collecting module and analyzing the tire temperature data to form a data cluster by the background server specifically comprises:
the tire surface temperature data and the tire surface temperature field area data are formed into a data set A (X, Y), wherein X represents the temperature value of the tire surface, and Y represents the size of the tire surface temperature field area;
the data set a (X, Y) is categorized, and the data points are categorized into data clusters.
7. The expressway vehicle tire burst warning device according to claim 6, wherein the classifying of the data set a (X, Y) and the classifying of each data point into the data cluster is as follows:
screening target data points of a data set, wherein the target data points comprise core data points, boundary data points and outlier data points, and the core data points have at least the number of data points with minimum distance in the adjacent distance of the core data points: the boundary data points are positioned at the edges of the data set, and the number of surrounding data points is less than the minimum cluster point minPoints; the outlier data points are located in a low density region of the data set;
clustering the screened data sets;
dynamically establishing whether the clustered data points are core points or not, and then setting the minimum cluster point to be greater than or equal to the dimension of the data set;
establishing a cluster maximum radius of the key parameters by using the Euclidean distance method;
judging whether data points which are more than or equal to the minimum cluster point exist around the maximum radius of the data point cluster by utilizing the established maximum radius value of the cluster, if so, using the data points as a data cluster,
and continuing to cluster the rest data points until all the data points are clustered, and obtaining the categorized data clusters.
8. The expressway vehicle tire burst warning device of claim 7, wherein the microcontroller analyzes temperature field state data of the tire surface of the driving vehicle and compares the data with a set threshold value specifically comprises:
placing the vehicle tire surface temperature data and the tire surface temperature field area data into a data set a (X, Y);
judging whether the data is a data noise point in the data set according to the classified data clusters, and if so, matching the data noise point with a set warning threshold; the warning threshold value comprises a tire burst temperature threshold value and a tire temperature field area threshold value, wherein the normal temperature of the tire burst temperature threshold value is [0 ℃,100℃ ]]The critical temperature is 100 ℃ and 121 DEG C]The dangerous temperature is [121 ℃, ++ infinity]The method comprises the steps of carrying out a first treatment on the surface of the The tire temperature field area threshold value is [102cm ] 2 ,+∞]；
If the data noise point is within the dangerous temperature range of the tire burst temperature threshold value or within the tire temperature field area threshold value, the tire of the vehicle is at risk of burst.
9. The expressway vehicle tire burst warning device according to any one of claims 1-8, wherein three groups of information acquisition modules are arranged, the distance between each group is 100m, and each group of two information acquisition modules are arranged on detection upright posts on two sides of an expressway homodromous lane.
10. The expressway vehicle tire burst early warning method is characterized by comprising the following steps of:
acquiring time interval data of the moving object passing through the laser ranging sensor by using the laser ranging sensor and sending the time interval data to the microcontroller;
the microcontroller removes clutter in the time interval data by using a Kalman filtering algorithm, extracts effective time interval data, compares the effective time interval data with a set threshold value of whether the moving object is a driving vehicle, and judges that the moving object is the driving vehicle if the moving object accords with the threshold value of whether the moving object is the driving vehicle;
after detecting that a running vehicle exists, starting an infrared thermal imager, acquiring tire surface temperature data and tire surface temperature field area data of the running vehicle, and sending the tire surface temperature data and the tire surface temperature field area data to a microcontroller;
the microcontroller processes the tire surface temperature data and the tire surface temperature field area data by adopting a Kalman filtering algorithm and transmits the data to a background server;
the background server classifies the data set into data clusters and sends the data clusters to the microcontroller;
the microcontroller compares the tire burst temperature threshold value and the tire temperature field area threshold value which are set in the database and are classified into the data cluster, and judges whether the running vehicle has a tire burst risk or not;
if the running vehicle has a tire burst risk, starting a laser ranging sensor, detecting the distance between the running vehicle and the laser ranging sensor, judging the lane where the running vehicle is located, starting a video detection module of the lane where the running vehicle is located, recording the license plate number of the vehicle with the tire burst risk, and sending the license plate number to a warning device;
the warning device combines the acquired license plate information with warning information, and the vehicle driver is accurately warned in a mode of voice warning and display screen warning.
CN202310764865.4A 2023-06-27 2023-06-27 Expressway vehicle tire burst early warning device and method Pending CN116738319A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117894159A (en) * 2024-03-15 2024-04-16 杭州企智互联科技有限公司 Intelligent community security monitoring system based on Internet of things

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117894159A (en) * 2024-03-15 2024-04-16 杭州企智互联科技有限公司 Intelligent community security monitoring system based on Internet of things
CN117894159B (en) * 2024-03-15 2024-06-04 杭州企智互联科技有限公司 Intelligent community security monitoring system based on Internet of things

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