CN112834235A - Vehicle exhaust detection method and device, computer equipment and readable storage medium - Google Patents

Vehicle exhaust detection method and device, computer equipment and readable storage medium Download PDF

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CN112834235A
CN112834235A CN202011620962.9A CN202011620962A CN112834235A CN 112834235 A CN112834235 A CN 112834235A CN 202011620962 A CN202011620962 A CN 202011620962A CN 112834235 A CN112834235 A CN 112834235A
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vehicle
information
exhaust
detected
preset
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CN112834235B (en
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潘英杰
陆超
徐锦坤
李亚楠
黄海生
姚德山
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ANHUI BAOLONG ENVIRONMENTAL TECHNOLOGY CO LTD
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ANHUI BAOLONG ENVIRONMENTAL TECHNOLOGY CO LTD
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M17/00Testing of vehicles
    • G01M17/007Wheeled or endless-tracked vehicles
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N1/00Sampling; Preparing specimens for investigation
    • G01N1/02Devices for withdrawing samples
    • G01N1/22Devices for withdrawing samples in the gaseous state
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N1/00Sampling; Preparing specimens for investigation
    • G01N1/02Devices for withdrawing samples
    • G01N1/22Devices for withdrawing samples in the gaseous state
    • G01N1/24Suction devices
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004Gaseous mixtures, e.g. polluted air
    • G01N33/0009General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0036General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004Gaseous mixtures, e.g. polluted air
    • G01N33/0009General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0036General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
    • G01N33/0037NOx
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004Gaseous mixtures, e.g. polluted air
    • G01N33/0009General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0036General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
    • G01N33/004CO or CO2
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004Gaseous mixtures, e.g. polluted air
    • G01N33/0009General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0073Control unit therefor
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00Road transport of goods or passengers
    • Y02T10/10Internal combustion engine [ICE] based vehicles
    • Y02T10/40Engine management systems

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Abstract

The invention is suitable for the technical field of vehicle detection, and provides a vehicle tail gas detection method, a device, computer equipment and a readable storage medium, wherein the method comprises the following steps: acquiring vehicle information of a vehicle to be detected and distance information between the vehicle to be detected and a gas detection device, wherein the vehicle information carries exhaust pipe position information; continuously acquiring the concentration information of the polluted gas detected by the gas detection device, and determining the time sequence data of the concentration of the polluted gas; determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration; and correcting the characteristic of the pollutant concentration peak value according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model, and determining a vehicle exhaust detection result. According to the invention, the tail gas pipe position is locked by continuously collecting the time sequence data of the gas concentration of the vehicle from the head to the tail of the vehicle, the tail gas detection rate is high, the correction processing is carried out on the pollutant concentration peak value by combining the preset pollutant concentration peak value correction model, and the obtained vehicle tail gas detection result is more accurate.

Description

Vehicle exhaust detection method and device, computer equipment and readable storage medium
Technical Field
The invention belongs to the technical field of vehicle detection, and particularly relates to a vehicle tail gas detection method, a vehicle tail gas detection device, computer equipment and a readable storage medium.
Background
With the increasing pollution of automobile exhaust emission to the environment, the strengthening of the regulation of automobile exhaust emission becomes more serious, and the exhaust emission of heavy goods vehicles, which is one of the important sources of air pollution, is also more and more emphasized.
At present, a method for supervising a road heavy truck mainly comprises an annual inspection and road spot inspection mode of an environmental inspection station, a video monitoring mode and a laser remote sensing mode, wherein the annual inspection and road spot inspection mode of the environmental inspection station is difficult to obtain real road emission data, the method requires that a diesel truck regularly arrives at an environmental inspection station of a vehicle management station to perform a tail gas emission test of a working condition method, manual stopping is performed on a road, and a portable tail gas analyzer is used for performing road inspection; the test result of the ring inspection station is seriously interfered by human, the road inspection consumes manpower and material resources and has extremely low efficiency, and the purpose of monitoring the heavy-duty road truck is difficult to achieve; the video monitoring can realize road monitoring, but has limitations, data are uploaded to a background through video monitoring snapshot or video recording, and then the black smoke cars in the monitoring videos or images are extracted by adopting methods such as manual examination or image recognition, mode training for screening the black smoke cars and the like; the manual examination is time-consuming and labor-consuming, the efficiency is not high, the qualitative detection can be only carried out on the particles in the tail gas, the quantitative detection cannot be carried out on the particles invisible to naked eyes, and the nitrogen oxide components cannot be detected; the tail gas of the vehicle is measured by laser remote sensing technology, so that the accuracy and the precision are high, but at present, an instrument of an open light path monitors the vehicle with an exhaust pipe at the tail part, most of the exhaust pipes of a diesel truck are arranged in the middle, at the bottom and on a measuring surface of the whole vehicle, especially, the trailer type commonly used for logistics is irregular, and the existing remote sensing equipment can be shielded by a vehicle body structure no matter the existing remote sensing equipment is distributed in a vertical or horizontal light path, so that the existing remote sensing equipment has poor monitoring effect on the diesel truck and low detection rate.
Therefore, the existing method for monitoring the road heavy truck has the problems of poor monitoring effect on the diesel truck and low tail gas detection rate.
Disclosure of Invention
The embodiment of the invention aims to provide a vehicle tail gas detection method, and aims to solve the problems of poor monitoring effect on a diesel truck and low tail gas detection rate in the conventional road heavy truck supervision method.
The embodiment of the invention is realized in such a way that a vehicle tail gas detection method comprises the following steps:
when a response is made that a vehicle to be detected enters a monitoring area, vehicle information of the vehicle to be detected and distance information between the vehicle to be detected and a gas detection device are obtained, wherein the vehicle information carries exhaust pipe position information;
continuously acquiring the polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area, and determining the polluted gas concentration time sequence data of the vehicle to be detected;
determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration;
and correcting the characteristic of the pollutant concentration peak value according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model, and determining a vehicle tail gas detection result of the vehicle to be detected.
Another object of an embodiment of the present invention is to provide a vehicle exhaust gas detection apparatus, including:
the device comprises a vehicle information and distance information acquisition unit, a gas detection unit and a monitoring unit, wherein the vehicle information and distance information acquisition unit is used for acquiring vehicle information of a vehicle to be detected and distance information between the vehicle to be detected and a gas detection device when responding that the vehicle to be detected enters a monitoring area, and the vehicle information carries exhaust pipe position information;
the polluted gas concentration time sequence data determining unit is used for continuously acquiring the polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area and determining the polluted gas concentration time sequence data of the vehicle to be detected;
the pollutant concentration peak characteristic determining unit is used for determining the pollutant concentration peak characteristic according to the polluted gas concentration time sequence data; and
and the vehicle tail gas detection result determining unit is used for correcting the characteristic of the pollutant concentration peak value according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model, and determining the vehicle tail gas detection result of the vehicle to be detected.
It is a further object of an embodiment of the invention to provide a computer arrangement comprising a memory and a processor, the memory having stored therein a computer program which, when executed by the processor, causes the processor to carry out the steps of the vehicle exhaust detection method.
Another object of an embodiment of the present invention is a computer readable storage medium having a computer program stored thereon, which, when executed by a processor, causes the processor to perform the steps of the vehicle exhaust gas detection method.
According to the vehicle tail gas detection method provided by the embodiment of the invention, when a response is sent to a to-be-detected vehicle entering a monitoring area, vehicle information carrying exhaust pipe position information of the to-be-detected vehicle and distance information between the to-be-detected vehicle and a gas detection device are obtained, and polluted gas concentration information detected by the gas detection device when the to-be-detected vehicle is in the monitoring area is continuously obtained, so that polluted gas concentration time sequence data of the to-be-detected vehicle is determined; and determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration, and correcting the peak value characteristic of the pollutant concentration according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model to determine the vehicle tail gas detection result of the vehicle to be detected. According to the invention, the time sequence data of the concentration of the polluted gas of the vehicle from the head to the tail of the vehicle in the monitoring area is continuously acquired, the position of the tail gas pipe area of the vehicle is accurately locked, the interference of the irregular structure of the vehicle body on the tail gas detection is avoided, the tail gas detection rate is high, and the characteristic of the concentration peak of the pollutant is corrected according to the distance information and the position information of the exhaust pipe in combination with the preset pollutant concentration peak correction model, so that the obtained vehicle tail gas detection result is more accurate.
Drawings
FIG. 1 is a diagram of an application environment of a method for detecting vehicle exhaust according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for detecting vehicle emissions according to an embodiment of the present invention;
FIG. 3 is a diagram of exemplary timing data peaks provided in accordance with an embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps of generating a preset exhaust gas data modification model according to an embodiment of the present invention;
FIG. 5 is a flow chart of another method for detecting vehicle emissions according to an embodiment of the present invention;
fig. 6 is a block diagram of a vehicle exhaust gas detection device according to an embodiment of the present invention;
fig. 7 is a block diagram illustrating another vehicle exhaust gas detection apparatus according to an embodiment of the present invention;
FIG. 8 is a block diagram showing an internal configuration of a computer device according to one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of the present application.
The embodiment of the invention provides a vehicle tail gas detection method for solving the problems of poor monitoring effect on a diesel truck and low tail gas detectable rate of the existing road heavy truck supervision method, and the method comprises the steps of obtaining vehicle information carrying exhaust pipe position information of a vehicle to be detected and distance information between the vehicle to be detected and a gas detection device when responding to that the vehicle to be detected enters a monitoring area, continuously obtaining polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area, and determining polluted gas concentration time sequence data of the vehicle to be detected; and determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration, and correcting the peak value characteristic of the pollutant concentration according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model to determine the vehicle tail gas detection result of the vehicle to be detected. According to the invention, the time sequence data of the concentration of the polluted gas of the vehicle from the head to the tail of the vehicle in the monitoring area is continuously acquired, the position of the tail gas pipe area of the vehicle is accurately locked, the interference of the irregular structure of the vehicle body on the tail gas detection is avoided, the tail gas detection rate is high, and the characteristic of the concentration peak of the pollutant is corrected according to the distance information and the position information of the exhaust pipe in combination with the preset pollutant concentration peak correction model, so that the obtained vehicle tail gas detection result is more accurate. The invention can realize the diesel truck tail gas detection through the bayonet, can effectively capture the tail gas smoke mass of the vehicle, avoids the influence of light blocking caused by a complex structure of the vehicle in the existing remote sensing application process, improves the detection rate of the tail gas detection and reduces the misjudgment.
To further explain the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of the embodiments, structures, features and effects according to the present invention will be given with reference to the accompanying drawings and preferred embodiments.
Fig. 1 is an application environment diagram of a vehicle exhaust detection method according to an embodiment of the present invention, as shown in fig. 1, in the application environment, the application environment includes a data acquisition terminal 110, a gas detection device 120, and a computer device 130.
The computer device 130 may be an independent physical server or terminal, may also be a server cluster formed by a plurality of physical servers, and may be a cloud server providing basic cloud computing services such as a cloud server, a cloud database, a cloud storage, and a CDN.
The data collection terminal 110 may be, but is not limited to, a camera, a range finder, a speedometer, etc. The auxiliary structure of the gas detection device 120 may include a cluster fan and a tail gas absorption bin, and the air at the bottom of the vehicle is continuously blown to the absorption bin through the cluster fan, wherein the tail gas discharged by the exhaust pipe is also included, and the concentration of each detected polluted gas in the absorption bin is continuously collected by the gas detection device 120 to obtain the concentration information of the polluted gas. The data acquisition terminal 110 and the gas detection device 120 may be connected to the computer device 130 through a network, and may acquire vehicle information of the vehicle to be detected and distance information between the vehicle to be detected and the gas detection device through the data acquisition terminal 110, and detect concentration information of the pollutant gas in the vehicle exhaust through the gas detection device 120, and transmit the data to the computer device 130, which is not limited herein.
As shown in fig. 2, in an embodiment, a method for detecting vehicle exhaust gas is provided, and this embodiment is mainly illustrated by applying the method to the computer device 130 in fig. 1. The vehicle exhaust detection method specifically comprises the following steps:
step S201, when a vehicle to be detected enters a monitoring area in response, vehicle information of the vehicle to be detected and distance information between the vehicle to be detected and a gas detection device are obtained, wherein the vehicle information carries exhaust pipe position information.
In the embodiment of the invention, the monitoring area can be arranged in a toll station, a check station and other bayonet scenes, vehicles in the scenes usually run at low speed, the acquired vehicle information or distance information is more accurate, meanwhile, aerodynamic turbulence caused by the running of the vehicles at low speed is small, the cluster fan can play a leading role, and the effectiveness of gas delivery is ensured.
In the embodiment of the invention, when the detected vehicle passes through the gate lane, the high-definition camera can be used for carrying out movement detection and identification on the vehicle and acquiring vehicle information, including license plate numbers, vehicle types, height and inclination angles of the exhaust pipe, snap pictures, video and the like, and triggering the cluster fan and starting a gas detection device, a speed device and other continuous acquisition processes.
In the embodiment of the present invention, the vehicle information of the vehicle to be detected includes, but is not limited to, license plate information, vehicle type information, speed information, acceleration information, vehicle traffic video information, and height and inclination angle information of an exhaust pipe.
Step S202, continuously acquiring polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area, and determining polluted gas concentration time sequence data of the vehicle to be detected.
In the embodiment of the invention, in order to obtain the tail gas of the diesel truck, the directional cluster fan is arranged at the position of the tail gas pipe of the diesel truck, which is generally 50cm high, and is used for actively conveying the tail gas of the diesel truck; in addition, screens are arranged on two sides of the bayonet lane to avoid the interference of ambient wind speed and wind direction, and a semi-closed absorption bin is arranged opposite to the cluster fan for collecting and converging tail gas in a short time and in a small space range; the gas detection device can be arranged in the semi-closed absorption bin, and the gas detection device can select various conventional gas detection instruments such as an open light path, an extraction type instrument and the like, but the equipment sample collection device or the measurement channel is ensured to be positioned in the absorption bin.
In the embodiment of the invention, from the head of a diesel truck to the tail of the truck, the bundling fan continuously blows air at the bottom of the truck to the absorption bin, wherein the tail gas is exhausted by the exhaust pipe, and the gas detection device continuously collects the concentration of each measured polluted gas in the absorption bin to obtain the concentration time sequence data of the passing of the whole truck.
And step S203, determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration.
In the embodiment of the invention, the time sequence data of the concentration of the polluted gas is a typical time sequence data peak diagram shown in fig. 3, which carries vehicle tail gas detection data, the time sequence concentration data is analyzed to find the characteristic of the concentration peak of the pollutant, and the characteristic of the concentration peak of the pollutant determined from the characteristic is the moment when the tail gas pipe passes through the cluster fan, so that the position of the exhaust pipe is locked, and the tail gas capture and detection of the exhaust pipe of the diesel truck under the condition of irregular distribution at the bottom are realized.
And S204, correcting the characteristic of the pollutant concentration peak value according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model, and determining a vehicle exhaust detection result of the vehicle to be detected.
In the embodiment of the invention, the preset pollutant concentration peak value correction model can refer to the existing gas diffusion model, for example, concentration inversion is carried out on the proportional relation of each component in the tail gas through the gas diffusion model, and the result is corrected according to factors including vehicle speed, acceleration, distance, height and inclination angle of an exhaust pipe, equipment precision and the like, so that whether the real emission of the vehicle exceeds the standard or not can be determined with higher precision in the follow-up process, and all measurement data in the whole process are integrated and filed.
In a preferred embodiment of the present invention, as shown in fig. 4, the preset pollutant concentration peak value correction model may be further generated by:
in an embodiment of the present invention, the generating step of the preset pollutant concentration peak value correction model includes:
step S401, a plurality of vehicle samples with known target pollutant concentration peak characteristics are obtained.
In an embodiment of the present invention, the vehicle sample with the known peak target pollutant concentration characteristic may be acquired by a vehicle detection center.
Step S402, acquiring corresponding exhaust pipe position information and distance information between the exhaust pipe position information and the gas detection device when the vehicle sample passes through the monitoring area, and acquiring a response pollutant concentration peak value corresponding to the distance information between the exhaust pipe position information and the gas detection device.
And step S403, taking the exhaust pipe position information of the vehicle sample, the distance information between the exhaust pipe position information and the gas detection device and the response pollutant concentration peak value characteristic as the input of a pollutant concentration peak value correction model, taking the target pollutant concentration peak value characteristic as the output of the pollutant concentration peak value correction model, training and generating the pollutant concentration peak value correction model.
In the embodiment of the invention, a pollutant concentration peak value correction model is trained by taking exhaust pipe position information of a plurality of vehicle samples, distance information between the exhaust pipe position information and a gas detection device, response pollutant concentration peak value characteristics and target pollutant concentration peak value characteristics as parameters; when the loss difference between the exhaust pipe position information of a certain vehicle sample, the distance information between the exhaust pipe position information and a gas detection device, the pollutant concentration peak value characteristic determined by a response pollutant concentration peak value characteristic and a convolutional neural network model containing variable parameters and the marked target pollutant concentration peak value characteristic of the vehicle sample does not meet a preset threshold value, the variable parameters of the convolutional neural network model need to be further adjusted, the loss difference is recalculated, and the steps are repeated until the loss difference meets the preset threshold value; when the loss difference between the exhaust pipe position information of a certain vehicle sample, the distance information between the exhaust pipe position information and a gas detection device, the pollutant concentration peak value characteristic determined by a response pollutant concentration peak value characteristic and a convolutional neural network model containing variable parameters and the marked target pollutant concentration peak value characteristic of the vehicle sample is smaller than a certain threshold value, the convolutional neural network model is a required preset pollutant concentration peak value correction model at the moment, and the pollutant concentration peak value correction model obtained through training can accurately correct the pollutant concentration peak value characteristic according to the distance information and the exhaust pipe position information.
According to the vehicle tail gas detection method provided by the embodiment of the invention, when a response is sent to a to-be-detected vehicle entering a monitoring area, vehicle information carrying exhaust pipe position information of the to-be-detected vehicle and distance information between the to-be-detected vehicle and a gas detection device are obtained, and polluted gas concentration information detected by the gas detection device when the to-be-detected vehicle is in the monitoring area is continuously obtained, so that polluted gas concentration time sequence data of the to-be-detected vehicle is determined; and determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration, and correcting the peak value characteristic of the pollutant concentration according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model to determine the vehicle tail gas detection result of the vehicle to be detected. According to the invention, the time sequence data of the concentration of the polluted gas of the vehicle from the head to the tail of the vehicle in the monitoring area is continuously acquired, the position of the tail gas pipe area of the vehicle is accurately locked, the interference of the irregular structure of the vehicle body on the tail gas detection is avoided, the tail gas detection rate is high, and the characteristic of the concentration peak of the pollutant is corrected according to the distance information and the position information of the exhaust pipe in combination with the preset pollutant concentration peak correction model, so that the obtained vehicle tail gas detection result is more accurate. The invention can realize the diesel truck tail gas detection through the bayonet, can effectively capture the tail gas smoke mass of the vehicle, avoids the influence of light blocking caused by a complex structure of the vehicle in the existing remote sensing application process, improves the detection rate of the tail gas detection and reduces the misjudgment.
In one embodiment, as shown in fig. 5, a vehicle exhaust gas detection method is different from the method shown in fig. 2 in that the vehicle exhaust gas detection method further includes:
and S501, obtaining vehicle information that the vehicle to be detected meets a preset vehicle exhaust emission standard.
In the embodiment of the present invention, the vehicle information of the preset vehicle exhaust emission standard includes, but is not limited to, engine speed, engine torque, oil consumption, vehicle speed, total engine running time, exhaust temperature, exhaust flow information, and the like. The exhaust emission standards corresponding to vehicles with different vehicle information are different, so that the vehicle information of the vehicle to be detected, which meets the preset vehicle exhaust emission standard, is obtained, the standard vehicle exhaust data corresponding to the vehicle to be detected is determined through the vehicle information and a preset vehicle exhaust detection model, and the standard vehicle exhaust data is used as the comparison standard of the vehicle exhaust data of the vehicle to be detected.
And step S502, determining standard vehicle exhaust data according to the vehicle information of the preset vehicle exhaust emission standard and a preset vehicle exhaust detection model established based on a convolutional neural network.
In the embodiment of the invention, the vehicle exhaust detection model established based on the convolutional neural network is generated by training a plurality of vehicle information samples which are collected in advance and accord with the preset vehicle exhaust emission standard and standard exhaust emission data samples corresponding to the vehicle information samples through the convolutional neural network containing variable parameters.
In an embodiment of the present invention, the structure of the convolutional neural network model includes an input layer, a plurality of convolutional layers, a plurality of pooling layers, at least one fully-connected layer, and an output layer, wherein variable parameters exist in the plurality of convolutional layers and the plurality of fully-connected layers. When the variable parameters in the plurality of convolution layers and the plurality of full connection layers are changed, the same vehicle information samples which accord with the preset vehicle exhaust emission standard are input, and the output vehicle exhaust emission data are different. Whether the established vehicle exhaust gas detection model meets the requirements can be judged by judging whether the loss difference of the plurality of vehicle information samples meeting the preset vehicle exhaust gas emission standard meets the preset conditions, for example, when the loss difference of the vehicle information samples meeting the preset vehicle exhaust gas emission standard is smaller than a certain threshold value, the vehicle information meeting the preset vehicle exhaust gas emission standard is input according to the trained vehicle exhaust gas detection model, and more accurate standard exhaust gas emission data can be obtained.
Step S503, when the difference value between the vehicle exhaust detection result of the vehicle to be detected and the standard vehicle exhaust data exceeds a preset threshold value, determining that the exhaust emission of the vehicle to be detected exceeds the standard.
In the embodiment of the present invention, the preset threshold may be set according to the performance of the device and/or the implementation requirement during the specific implementation, and the size of the preset threshold is not specifically limited in the embodiment of the present invention, for example, the preset threshold may be 0.5%, 1%, 5%, and the like.
And step S504, uploading the vehicle information of the vehicle to be detected to a server-side platform of a background supervision center.
According to the vehicle exhaust detection method provided by the embodiment of the invention, vehicle information that a vehicle to be detected meets a preset vehicle exhaust emission standard is obtained; determining standard vehicle exhaust data according to the vehicle information and a preset vehicle exhaust detection model established based on a convolutional neural network; when the difference value between the vehicle exhaust data and the standard vehicle exhaust data exceeds a preset threshold value, determining that the exhaust emission of the vehicle to be detected exceeds a standard; the vehicle exhaust detection model established based on the convolutional neural network is obtained by training the vehicle information sample conforming to the preset vehicle exhaust emission standard and the standard exhaust emission data sample corresponding to the vehicle information sample, and can be used for expressing a hidden relation between the vehicle information conforming to the preset vehicle exhaust emission standard and the standard vehicle exhaust data.
As shown in fig. 6, in an embodiment, a vehicle exhaust detection device is provided, which may be integrated in the computer device 130, and specifically may include a vehicle information and distance information obtaining unit 610, a pollutant concentration time series data determining unit 620, a pollutant concentration peak characteristic determining unit 630, and a vehicle exhaust detection result determining unit 640.
The vehicle information and distance information acquiring unit 610 is configured to acquire vehicle information of a vehicle to be detected and distance information between the vehicle to be detected and a gas detection device when it is responded that the vehicle to be detected enters a monitoring area, where the vehicle information carries exhaust pipe position information.
In the embodiment of the invention, the monitoring area can be arranged in a toll station, a check station and other bayonet scenes, vehicles in the scenes usually run at low speed, the acquired vehicle information or distance information is more accurate, meanwhile, aerodynamic turbulence caused by the running of the vehicles at low speed is small, the cluster fan can play a leading role, and the effectiveness of gas delivery is ensured.
In the embodiment of the invention, when the detected vehicle passes through the gate lane, the high-definition camera can be used for carrying out movement detection and identification on the vehicle and acquiring vehicle information, including license plate numbers, vehicle types, height and inclination angles of the exhaust pipe, snap pictures, video and the like, and triggering the cluster fan and starting a gas detection device, a speed device and other continuous acquisition processes.
In the embodiment of the present invention, the vehicle information of the vehicle to be detected includes, but is not limited to, license plate information, vehicle type information, speed information, acceleration information, vehicle traffic video information, and height and inclination angle information of an exhaust pipe.
And the polluted gas concentration time sequence data determining unit 620 is used for continuously acquiring the polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area, and determining the polluted gas concentration time sequence data of the vehicle to be detected.
In the embodiment of the invention, in order to obtain the tail gas of the diesel truck, the directional cluster fan is arranged at the position of the tail gas pipe of the diesel truck, which is generally 50cm high, and is used for actively conveying the tail gas of the diesel truck; in addition, screens are arranged on two sides of the bayonet lane to avoid the interference of ambient wind speed and wind direction, and a semi-closed absorption bin is arranged opposite to the cluster fan for collecting and converging tail gas in a short time and in a small space range; the gas detection device can be arranged in the semi-closed absorption bin, and the gas detection device can select various conventional gas detection instruments such as an open light path, an extraction type instrument and the like, but the equipment sample collection device or the measurement channel is ensured to be positioned in the absorption bin.
In the embodiment of the invention, from the head of a diesel truck to the tail of the truck, the bundling fan continuously blows air at the bottom of the truck to the absorption bin, wherein the tail gas is exhausted by the exhaust pipe, and the gas detection device continuously collects the concentration of each measured polluted gas in the absorption bin to obtain the concentration time sequence data of the passing of the whole truck.
And a pollutant concentration peak characteristic determining unit 630, configured to determine a pollutant concentration peak characteristic according to the pollutant gas concentration time series data.
In the embodiment of the invention, the time sequence data of the concentration of the polluted gas is a typical time sequence data peak diagram shown in fig. 3, which carries vehicle tail gas detection data, the time sequence concentration data is analyzed to find the characteristic of the concentration peak of the pollutant, and the characteristic of the concentration peak of the pollutant determined from the characteristic is the moment when the tail gas pipe passes through the cluster fan, so that the position of the exhaust pipe is locked, and the tail gas capture and detection of the exhaust pipe of the diesel truck under the condition of irregular distribution at the bottom are realized.
And the vehicle tail gas detection result determining unit 640 is configured to correct the characteristic of the pollutant concentration peak according to the distance information, the exhaust pipe position information, and a preset pollutant concentration peak correction model, and determine a vehicle tail gas detection result of the vehicle to be detected.
In the embodiment of the invention, the preset pollutant concentration peak value correction model can refer to the existing gas diffusion model, for example, concentration inversion is carried out on the proportional relation of each component in the tail gas through the gas diffusion model, and the result is corrected according to factors including vehicle speed, acceleration, distance, height and inclination angle of an exhaust pipe, equipment precision and the like, so that whether the real emission of the vehicle exceeds the standard or not can be determined with higher precision in the follow-up process, and all measurement data in the whole process are integrated and filed. The preset pollutant concentration peak value correction model can also be established by the generation step of the preset pollutant concentration peak value correction model shown in fig. 4.
According to the vehicle tail gas detection device provided by the embodiment of the invention, when a response is sent to a to-be-detected vehicle entering a monitoring area, vehicle information carrying exhaust pipe position information of the to-be-detected vehicle and distance information between the to-be-detected vehicle and a gas detection device are obtained, and polluted gas concentration information detected by the gas detection device when the to-be-detected vehicle is in the monitoring area is continuously obtained, so that polluted gas concentration time sequence data of the to-be-detected vehicle is determined; and determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration, and correcting the peak value characteristic of the pollutant concentration according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model to determine the vehicle tail gas detection result of the vehicle to be detected. According to the invention, the time sequence data of the concentration of the polluted gas of the vehicle from the head to the tail of the vehicle in the monitoring area is continuously acquired, the position of the tail gas pipe area of the vehicle is accurately locked, the interference of the irregular structure of the vehicle body on the tail gas detection is avoided, the tail gas detection rate is high, and the characteristic of the concentration peak of the pollutant is corrected according to the distance information and the position information of the exhaust pipe in combination with the preset pollutant concentration peak correction model, so that the obtained vehicle tail gas detection result is more accurate. The invention can realize the diesel truck tail gas detection through the bayonet, can effectively capture the tail gas smoke mass of the vehicle, avoids the influence of light blocking caused by a complex structure of the vehicle in the existing remote sensing application process, improves the detection rate of the tail gas detection and reduces the misjudgment.
As shown in fig. 7, in one embodiment, there is provided a vehicle exhaust gas detecting apparatus, which is different from the apparatus shown in fig. 6, further comprising:
and a standard vehicle information obtaining unit 710, configured to obtain vehicle information that the vehicle to be detected meets a preset vehicle exhaust emission standard.
In the embodiment of the present invention, the vehicle information of the preset vehicle exhaust emission standard includes, but is not limited to, engine speed, engine torque, oil consumption, vehicle speed, total engine running time, exhaust temperature, exhaust flow information, and the like. The exhaust emission standards corresponding to vehicles with different vehicle information are different, so that the vehicle information of the vehicle to be detected, which meets the preset vehicle exhaust emission standard, is obtained, the standard vehicle exhaust data corresponding to the vehicle to be detected is determined through the vehicle information and a preset vehicle exhaust detection model, and the standard vehicle exhaust data is used as the comparison standard of the vehicle exhaust data of the vehicle to be detected.
And the standard vehicle exhaust data determining unit 720 is configured to determine standard vehicle exhaust data according to the vehicle information of the preset vehicle exhaust emission standard and a preset vehicle exhaust detection model established based on a convolutional neural network.
In the embodiment of the invention, the vehicle exhaust detection model established based on the convolutional neural network is generated by training a plurality of vehicle information samples which are collected in advance and accord with the preset vehicle exhaust emission standard and standard exhaust emission data samples corresponding to the vehicle information samples through the convolutional neural network containing variable parameters.
In an embodiment of the present invention, the structure of the convolutional neural network model includes an input layer, a plurality of convolutional layers, a plurality of pooling layers, at least one fully-connected layer, and an output layer, wherein variable parameters exist in the plurality of convolutional layers and the plurality of fully-connected layers. When the variable parameters in the plurality of convolution layers and the plurality of full connection layers are changed, the same vehicle information samples which accord with the preset vehicle exhaust emission standard are input, and the output vehicle exhaust emission data are different. Whether the established vehicle exhaust gas detection model meets the requirements can be judged by judging whether the loss difference of the plurality of vehicle information samples meeting the preset vehicle exhaust gas emission standard meets the preset conditions, for example, when the loss difference of the vehicle information samples meeting the preset vehicle exhaust gas emission standard is smaller than a certain threshold value, the vehicle information meeting the preset vehicle exhaust gas emission standard is input according to the trained vehicle exhaust gas detection model, and more accurate standard exhaust gas emission data can be obtained.
And the exhaust gas exceeding judgment unit 730 is configured to determine that the exhaust emission of the vehicle to be detected exceeds a preset threshold when judging that the difference value between the vehicle exhaust detection result of the vehicle to be detected and the standard vehicle exhaust data exceeds the preset threshold.
In the embodiment of the present invention, the preset threshold may be set according to the performance of the device and/or the implementation requirement during the specific implementation, and the size of the preset threshold is not specifically limited in the embodiment of the present invention, for example, the preset threshold may be 0.5%, 1%, 5%, and the like.
And the vehicle information uploading unit 740 is configured to upload the vehicle information of the vehicle to be detected to a server-side platform of the background monitoring center.
According to the vehicle exhaust gas detection device provided by the embodiment of the invention, the vehicle information that the vehicle to be detected meets the preset vehicle exhaust gas emission standard is obtained; determining standard vehicle exhaust data according to the vehicle information and a preset vehicle exhaust detection model established based on a convolutional neural network; when the difference value between the vehicle exhaust data and the standard vehicle exhaust data exceeds a preset threshold value, determining that the exhaust emission of the vehicle to be detected exceeds a standard; the vehicle exhaust detection model established based on the convolutional neural network is obtained by training the vehicle information sample conforming to the preset vehicle exhaust emission standard and the standard exhaust emission data sample corresponding to the vehicle information sample, and can be used for expressing a hidden relation between the vehicle information conforming to the preset vehicle exhaust emission standard and the standard vehicle exhaust data.
FIG. 8 is a diagram illustrating an internal structure of a computer device in one embodiment. The computer device may specifically be the computer device 130 in fig. 1. As shown in fig. 8, the computer apparatus includes a processor, a memory, a network interface, an input device, and a display screen connected through a system bus. Wherein the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program that, when executed by the processor, causes the processor to implement the vehicle exhaust detection method. The internal memory may also have a computer program stored therein, which when executed by the processor, causes the processor to perform a vehicle emission detection method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, the vehicle exhaust gas detection device provided by the present application may be implemented in the form of a computer program that is executable on a computer device as shown in fig. 8. The memory of the computer device may store various program modules constituting the vehicle exhaust gas detection apparatus, such as a vehicle information and distance information acquisition unit 610, a polluted gas concentration time series data determination unit 620, a pollutant concentration peak characteristic determination unit 630, and a vehicle exhaust gas detection result determination unit 640 shown in fig. 6. The respective program modules constitute computer programs that cause the processor to execute the steps in the vehicle exhaust gas detection method of the respective embodiments of the present application described in the present specification.
For example, the computer device shown in fig. 8 may execute step S201 by the vehicle information and distance information acquiring unit 610 in the vehicle exhaust gas detecting apparatus shown in fig. 6. The computer apparatus may perform step S202 by the contaminated gas concentration timing data determination unit 620. The computer device may perform step S203 by the contaminant concentration peak characteristic determination unit 630. The computer device may perform step S204 by the vehicle exhaust detection result determination unit 640.
In one embodiment, a computer device is proposed, the computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
when a response is made that a vehicle to be detected enters a monitoring area, vehicle information of the vehicle to be detected and distance information between the vehicle to be detected and a gas detection device are obtained, wherein the vehicle information carries exhaust pipe position information;
continuously acquiring the polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area, and determining the polluted gas concentration time sequence data of the vehicle to be detected;
determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration;
and correcting the characteristic of the pollutant concentration peak value according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model, and determining a vehicle tail gas detection result of the vehicle to be detected.
In one embodiment, a computer readable storage medium is provided, having a computer program stored thereon, which, when executed by a processor, causes the processor to perform the steps of:
when a response is made that a vehicle to be detected enters a monitoring area, vehicle information of the vehicle to be detected and distance information between the vehicle to be detected and a gas detection device are obtained, wherein the vehicle information carries exhaust pipe position information;
continuously acquiring the polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area, and determining the polluted gas concentration time sequence data of the vehicle to be detected;
determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration;
and correcting the characteristic of the pollutant concentration peak value according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model, and determining a vehicle tail gas detection result of the vehicle to be detected.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. A vehicle exhaust detection method, comprising:
when a response is made that a vehicle to be detected enters a monitoring area, vehicle information of the vehicle to be detected and distance information between the vehicle to be detected and a gas detection device are obtained, wherein the vehicle information carries exhaust pipe position information;
continuously acquiring the polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area, and determining the polluted gas concentration time sequence data of the vehicle to be detected;
determining the peak value characteristic of the pollutant concentration according to the time sequence data of the pollutant gas concentration;
and correcting the characteristic of the pollutant concentration peak value according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model, and determining a vehicle tail gas detection result of the vehicle to be detected.
2. The vehicle exhaust detection method according to claim 1, wherein the generating step of the preset pollutant concentration peak value correction model includes:
obtaining a plurality of vehicle samples with known target pollutant concentration peak characteristics;
acquiring corresponding exhaust pipe position information and distance information between the exhaust pipe position information and the gas detection device when the vehicle sample passes through a monitoring area, and acquiring response pollutant concentration peak values corresponding to the exhaust pipe position information and the distance information between the exhaust pipe position information and the gas detection device;
and training and generating a pollutant concentration peak value correction model by taking the exhaust pipe position information of the vehicle sample, the distance information between the exhaust pipe position information and the gas detection device and the response pollutant concentration peak value characteristic as the input of the pollutant concentration peak value correction model and taking the target pollutant concentration peak value characteristic as the output of the pollutant concentration peak value correction model.
3. The vehicle exhaust detection method according to claim 1, further comprising:
acquiring vehicle information that the vehicle to be detected meets a preset vehicle exhaust emission standard;
determining standard vehicle exhaust data according to the vehicle information of the preset vehicle exhaust emission standard and a preset vehicle exhaust detection model established based on a convolutional neural network, wherein the vehicle exhaust detection model established based on the convolutional neural network is generated by pre-collecting a plurality of vehicle information samples meeting the preset vehicle exhaust emission standard and standard exhaust emission data samples corresponding to the vehicle information samples through convolutional neural network training;
when the difference value between the vehicle exhaust detection result of the vehicle to be detected and the standard vehicle exhaust data exceeds a preset threshold value, determining that the exhaust emission of the vehicle to be detected exceeds a standard;
and uploading the vehicle information of the vehicle to be detected to a server-side platform of a background supervision center.
4. The vehicle exhaust detection method according to claim 3, wherein the vehicle information of the preset vehicle exhaust emission standard includes engine speed, engine torque, oil consumption, vehicle speed, total engine running time, exhaust temperature and exhaust flow information.
5. The vehicle exhaust detection method according to claim 1, wherein the vehicle information of the vehicle to be detected includes license plate information, vehicle type information, speed information, acceleration information, vehicle traffic video information, and exhaust pipe height and inclination angle information.
6. A vehicle exhaust gas detection device, comprising:
the device comprises a vehicle information and distance information acquisition unit, a gas detection unit and a monitoring unit, wherein the vehicle information and distance information acquisition unit is used for acquiring vehicle information of a vehicle to be detected and distance information between the vehicle to be detected and a gas detection device when responding that the vehicle to be detected enters a monitoring area, and the vehicle information carries exhaust pipe position information;
the polluted gas concentration time sequence data determining unit is used for continuously acquiring the polluted gas concentration information detected by the gas detection device when the vehicle to be detected is in the monitoring area and determining the polluted gas concentration time sequence data of the vehicle to be detected;
the pollutant concentration peak characteristic determining unit is used for determining the pollutant concentration peak characteristic according to the polluted gas concentration time sequence data; and
and the vehicle tail gas detection result determining unit is used for correcting the characteristic of the pollutant concentration peak value according to the distance information, the exhaust pipe position information and a preset pollutant concentration peak value correction model, and determining the vehicle tail gas detection result of the vehicle to be detected.
7. The vehicle exhaust gas detection apparatus according to claim 6, characterized by further comprising:
the standard vehicle information acquisition unit is used for acquiring the vehicle information of the vehicle to be detected, wherein the vehicle information accords with a preset vehicle exhaust emission standard;
the standard vehicle exhaust data determining unit is used for determining standard vehicle exhaust data according to vehicle information of a preset vehicle exhaust emission standard and a preset vehicle exhaust detection model established based on a convolutional neural network, wherein the vehicle exhaust detection model established based on the convolutional neural network is generated by pre-collecting a plurality of vehicle information samples meeting the preset vehicle exhaust emission standard and standard exhaust emission data samples corresponding to the vehicle information samples through convolutional neural network training;
the exhaust gas standard exceeding judging unit is used for determining that the exhaust emission of the vehicle to be detected exceeds a standard when judging that the difference value between the vehicle exhaust detection result of the vehicle to be detected and the standard vehicle exhaust data exceeds a preset threshold value; and
and the vehicle information uploading unit is used for uploading the vehicle information of the vehicle to be detected to a server-side platform of the background supervision center.
8. The vehicle exhaust gas detection device according to claim 7, wherein the vehicle information of the preset vehicle exhaust emission standard includes engine speed, engine torque, oil consumption, vehicle speed, total engine running time, exhaust gas temperature, and exhaust gas flow information.
9. A computer arrangement, characterized by comprising a memory and a processor, the memory having stored therein a computer program which, when executed by the processor, causes the processor to carry out the steps of the vehicle exhaust detection method according to any one of claims 1 to 5.
10. A computer-readable storage medium, having a computer program stored thereon, which, when being executed by a processor, causes the processor to carry out the steps of the vehicle exhaust detection method according to any one of claims 1 to 6.
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114236053A (en) * 2021-12-16 2022-03-25 北京华志信科技股份有限公司 Integrated comprehensive supervision method for vehicle exhaust
CN114607495A (en) * 2022-03-21 2022-06-10 潍柴动力股份有限公司 Method and device for determining concentration of nitrogen oxide, electronic equipment and storage medium
CN114645762A (en) * 2022-05-23 2022-06-21 山东新凌志检测技术有限公司 Motor vehicle tail gas purification monitoring system and method
CN115372045A (en) * 2022-10-25 2022-11-22 佛山市顺德区美的洗涤电器制造有限公司 Method and device for measuring direct collection efficiency, range hood and medium
CN116448949A (en) * 2023-03-22 2023-07-18 宁波远亚车辆检测有限公司 Automobile pollutant detection method, system, intelligent terminal and storage medium

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4459266A (en) * 1982-01-05 1984-07-10 Lamoreaux Charles L Air purity monitoring system
JPH10142105A (en) * 1996-11-07 1998-05-29 Toyota Motor Corp Method and device for measuring exhaust flow rate using trace gas
JP2002071525A (en) * 2000-08-25 2002-03-08 Horiba Ltd System for measuring automobile exhaust gas
CN102918245A (en) * 2010-05-25 2013-02-06 五十铃自动车株式会社 Selective catalytic reduction system
US20130181836A1 (en) * 2012-01-18 2013-07-18 Xerox Corporation Image-based determination of co and co2 concentrations in vehicle exhaust gas emissions
CN103850812A (en) * 2012-11-29 2014-06-11 福特环球技术公司 SYSTEMs AND METHODs FOR IMPROVING VEHICLE PERFORMANCE
CN107219330A (en) * 2017-04-27 2017-09-29 深圳市元征科技股份有限公司 Vehicle exhaust monitoring method, system and computer-readable recording medium
CN206710256U (en) * 2017-05-03 2017-12-05 安徽宝龙环保科技有限公司 A kind of Design of Vehicle Tail Gas Analyzer
CN107843693A (en) * 2017-10-30 2018-03-27 武汉万集信息技术有限公司 A kind of telemetering motor vehicle tail system and method based on laser scanning positioning
CN108226046A (en) * 2017-12-26 2018-06-29 中国科学技术大学 A kind of telemetering motor vehicle tail modified result method
CN110243762A (en) * 2019-06-18 2019-09-17 深圳大雷汽车检测股份有限公司 Telemetering motor vehicle tail and supervisory systems and self study high emitter decision algorithm
CN110988273A (en) * 2019-12-27 2020-04-10 长安大学 Automatic tail gas detection device

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4459266A (en) * 1982-01-05 1984-07-10 Lamoreaux Charles L Air purity monitoring system
JPH10142105A (en) * 1996-11-07 1998-05-29 Toyota Motor Corp Method and device for measuring exhaust flow rate using trace gas
JP2002071525A (en) * 2000-08-25 2002-03-08 Horiba Ltd System for measuring automobile exhaust gas
CN102918245A (en) * 2010-05-25 2013-02-06 五十铃自动车株式会社 Selective catalytic reduction system
US20130181836A1 (en) * 2012-01-18 2013-07-18 Xerox Corporation Image-based determination of co and co2 concentrations in vehicle exhaust gas emissions
CN103850812A (en) * 2012-11-29 2014-06-11 福特环球技术公司 SYSTEMs AND METHODs FOR IMPROVING VEHICLE PERFORMANCE
CN107219330A (en) * 2017-04-27 2017-09-29 深圳市元征科技股份有限公司 Vehicle exhaust monitoring method, system and computer-readable recording medium
CN206710256U (en) * 2017-05-03 2017-12-05 安徽宝龙环保科技有限公司 A kind of Design of Vehicle Tail Gas Analyzer
CN107843693A (en) * 2017-10-30 2018-03-27 武汉万集信息技术有限公司 A kind of telemetering motor vehicle tail system and method based on laser scanning positioning
CN108226046A (en) * 2017-12-26 2018-06-29 中国科学技术大学 A kind of telemetering motor vehicle tail modified result method
CN110243762A (en) * 2019-06-18 2019-09-17 深圳大雷汽车检测股份有限公司 Telemetering motor vehicle tail and supervisory systems and self study high emitter decision algorithm
CN110988273A (en) * 2019-12-27 2020-04-10 长安大学 Automatic tail gas detection device

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
刘永红: ""佛山市轻型汽油车尾气动态排放特征分析"", 《环境科学与技术》 *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114236053A (en) * 2021-12-16 2022-03-25 北京华志信科技股份有限公司 Integrated comprehensive supervision method for vehicle exhaust
CN114607495A (en) * 2022-03-21 2022-06-10 潍柴动力股份有限公司 Method and device for determining concentration of nitrogen oxide, electronic equipment and storage medium
CN114645762A (en) * 2022-05-23 2022-06-21 山东新凌志检测技术有限公司 Motor vehicle tail gas purification monitoring system and method
CN114645762B (en) * 2022-05-23 2022-08-02 山东新凌志检测技术有限公司 Motor vehicle tail gas purification monitoring system and method
CN115372045A (en) * 2022-10-25 2022-11-22 佛山市顺德区美的洗涤电器制造有限公司 Method and device for measuring direct collection efficiency, range hood and medium
CN116448949A (en) * 2023-03-22 2023-07-18 宁波远亚车辆检测有限公司 Automobile pollutant detection method, system, intelligent terminal and storage medium
CN116448949B (en) * 2023-03-22 2023-10-31 宁波远亚车辆检测有限公司 Automobile pollutant detection method, system, intelligent terminal and storage medium

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