CN113484468A - Motor vehicle environmental protection detection analysis method and system based on quartile algorithm - Google Patents
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Abstract
The application discloses a motor vehicle environment-friendly detection analysis method and system based on a quartile algorithm, wherein the method obtains target detection data by detecting the concentration of exhaust gas emitted by a motor vehicle; obtaining the concentration of the exhaust gas emitted by the batch of motor vehicles of the same type to obtain a plurality of groups of comparison detection data; processing the comparison detection data based on a quartile algorithm to obtain an upper quartile numerical value, a middle numerical value and a lower quartile numerical value of the comparison detection data; then according to the upper quartile value and the lower quartile value, determining the quartile distance of the comparison detection data, and determining the z fraction value of the motor vehicle based on the target detection data, the median value and the quartile distance through a z fraction calculation method; therefore, the environmental protection detection analysis result of the motor vehicle is determined according to the value of the z fraction value. The method can improve the detection accuracy of the exhaust emission condition of the vehicle, and is beneficial to environmental protection and normal operation of the motor vehicle. The method and the device can be widely applied to the technical field of motor vehicle detection.
Description
Technical Field
The application relates to the technical field of motor vehicle detection, in particular to a motor vehicle environment-friendly detection analysis method and system based on a quartile algorithm.
Background
In recent years, with the development of economy, the quantity of urban motor vehicles and non-road mobile machines is on the rise, and the increasing quantity becomes one of the main pollution sources of urban air pollution. The pollution harm of NOx, PM, HC, CO and the like discharged by the tail gas of the motor vehicle is more than several times or even tens times of that of common vehicles, especially for some old vehicles with super-old age and super-emission and non-road mobile engineering machinery, and the nitrogen oxide and particulate matters discharged by diesel vehicles account for a larger proportion. At present, in China, motor vehicle environmental protection inspection mechanisms are mainly used for regularly detecting vehicles in use in a motor vehicle emission detection mode, but due to the detection equipment calibration mode, the operating skill level of operators and the like, the accuracy and the authenticity of the environmental protection detection data of the motor vehicles in use cannot be guaranteed, objective examination and evaluation on the motor vehicle environmental protection inspection mechanisms are difficult, and the reliability of analysis results is low.
Disclosure of Invention
The present application aims to solve at least one of the technical problems in the related art to some extent.
Therefore, an object of the embodiments of the present application is to provide a method for detecting and analyzing environmental protection of a motor vehicle based on a quartile algorithm, which can effectively improve the detection accuracy of the exhaust emission condition of the vehicle, and is beneficial to environmental protection and normal operation of the motor vehicle.
Another object of the embodiments of the present application is to provide an environmental protection detection analysis system for a motor vehicle based on a quartile algorithm.
In order to achieve the technical purpose, the technical scheme adopted by the embodiment of the application comprises the following steps:
in a first aspect, an embodiment of the present application provides a motor vehicle environmental protection detection analysis method based on a quartile algorithm, including the following steps:
detecting the concentration of the exhaust gas emitted by the motor vehicle to obtain target detection data;
obtaining the concentration of the exhaust gas emitted by the batch of motor vehicles of the same type to obtain a plurality of groups of comparison detection data;
processing the comparison detection data through a quartile algorithm to obtain an upper quartile numerical value, a middle numerical value and a lower quartile numerical value of the comparison detection data;
determining a quartile distance of the comparison detection data according to the upper quartile value and the lower quartile value;
determining a z-fraction value of the motor vehicle based on the target detection data, the median value and the quartile range by a z-fraction calculation method;
and determining an environment-friendly detection analysis result of the motor vehicle according to the z score value.
In addition, the motor vehicle environmental protection detection analysis method based on the quartile algorithm according to the above embodiment of the present application may further have the following additional technical features:
further, in an embodiment of the present application, the detecting the concentration of the exhaust gas emitted from the vehicle to obtain the target detection data includes:
detecting the motor vehicle for multiple times on multiple different roads or under the condition of different drivers to obtain multiple groups of initial detection data;
and calculating the average value of the initial detection data to obtain the target detection data.
Further, in an embodiment of the present application, the method further includes the following steps:
when the workpiece is detected to pass through the torque detection post, acquiring the torque moment of the torque wrench at the torque detection post;
and determining that the torque moment is smaller than a second preset torque threshold value, and sending a stop instruction to the assembly line.
Further, in one embodiment of the present application, the target detection data includes at least one of hydrocarbon concentration data, carbon monoxide concentration data, or nitrogen oxide concentration data.
Further, in an embodiment of the present application, the upper quartile value is calculated by:
sequencing the comparison detection data from small to large, and determining the number of the comparison detection data;
determining the upper quartile position number according to the number of the comparison detection data by a formula Q1 ═ n +1 x 1/4; in the formula, Q1 represents the upper quartile position number, and n represents the number of comparison detection data;
and if the upper quartile position number is an integer, using the comparison detection data sequenced in the upper quartile position number as an upper quartile numerical value.
Further, in one embodiment of the present application, the method further comprises:
if the upper quartile position number is not an integer, rounding the upper quartile position number to a larger value to obtain a first numerical value; rounding the upper quartile position to obtain a second numerical value;
and carrying out weighted summation on the comparison detection data which are sequenced at the first numerical value and the second numerical value to obtain the upper quartile numerical value.
Further, in an embodiment of the present application, the performing a weighted summation on the comparison detection data sorted in the first value and the second value to obtain the upper quartile value includes:
determining the upper quartile value by the formula P1 ═ P1S × 3/4+ P1L × 1/4;
in the formula, P1S is the contrast detection data sorted at the second value, and P1L is the contrast detection data sorted at the first value.
Further, in an embodiment of the present application, the median value is calculated by:
sequencing the comparison detection data from small to large, and determining the number of the comparison detection data;
determining the position number of the median according to the number of the comparison detection data by a formula Q2 ═ n +1 x 1/2; in the formula, Q2 represents the number of median positions, and n represents the number of comparison detection data;
and if the median position number is an integer, taking the contrast detection data sequenced in the median position number as a median value.
Further, in an embodiment of the present application, the determining a z-fraction value of the motor vehicle based on the target detection data, the median value and the quartile range by the z-fraction calculation method includes:
determining a z score value of the motor vehicle by the formula z ═ ((X-X))/(a × IQR);
wherein z is a z score value of the motor vehicle, X represents target detection data, X represents a median value, a is a set constant value, and IQR represents a quarter-bit spacing.
Further, in one embodiment of the present application, the method further comprises the steps of:
sorting the z score values corresponding to a plurality of motor vehicles of the same type;
and taking the sequence value of the motor vehicle sequence as a horizontal axis coordinate, and taking the corresponding z score value as a vertical axis coordinate to generate a z score value distribution diagram of the motor vehicle.
In a second aspect, an embodiment of the present application provides a motor vehicle environmental protection detection analysis system based on a quartile algorithm, including:
the detection module is used for detecting the concentration of the exhaust gas discharged by the motor vehicle to obtain target detection data;
the acquisition module is used for acquiring the concentration of the exhaust gas emitted by the batch of motor vehicles of the same type to obtain a plurality of groups of comparison detection data;
the processing module is used for processing the comparison detection data through a quartile algorithm to obtain an upper quartile numerical value, a middle numerical value and a lower quartile numerical value of the comparison detection data;
the determining module is used for determining the quartile interval of the comparison detection data according to the upper quartile value and the lower quartile value;
the calculation module is used for determining a z-fraction value of the motor vehicle based on the target detection data, the median value and the quartile distance by a z-fraction calculation method;
and the analysis module is used for determining the environment-friendly detection analysis result of the motor vehicle according to the magnitude of the z score value.
In a third aspect, an embodiment of the present application provides a motor vehicle environmental protection detection analysis apparatus based on a quartile algorithm, including:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, the at least one program causes the at least one processor to implement the environmentally friendly motor vehicle detection analysis method based on the quartile algorithm of the first aspect.
In a fourth aspect, the present application further provides a computer-readable storage medium, in which a program executable by a processor is stored, and when the program executable by the processor is executed by the processor, the method for environmental detection and analysis of a motor vehicle based on a quartile algorithm according to the first aspect is implemented.
Advantages and benefits of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application:
according to the motor vehicle environment-friendly detection and analysis method based on the quartile algorithm, target detection data are obtained by detecting the concentration of exhaust gas emitted by a motor vehicle; obtaining a plurality of groups of comparison detection data by obtaining the concentration of the exhaust gas emitted by the batch of motor vehicles of the same type; processing the comparison detection data based on a quartile algorithm to obtain an upper quartile numerical value, a middle numerical value and a lower quartile numerical value of the comparison detection data; then according to the upper quartile value and the lower quartile value, determining the quartile distance of the comparison detection data, and determining the z fraction value of the motor vehicle based on the target detection data, the median value and the quartile distance through a z fraction calculation method; and determining the environmental protection detection analysis result of the motor vehicle according to the value of the z fraction value. The method can effectively improve the detection accuracy of the exhaust emission condition of the vehicle, and is beneficial to environmental protection and normal operation of the motor vehicle.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description is made on the drawings of the embodiments of the present application or the related technical solutions in the prior art, and it should be understood that the drawings in the following description are only for convenience and clarity of describing some embodiments in the technical solutions of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic flow chart of an embodiment of a motor vehicle environmental protection detection analysis method based on a quartile algorithm according to the present application;
FIG. 2 is a histogram of z-fraction values obtained by a motor vehicle environmental protection detection analysis method based on a quartile algorithm according to the present application;
FIG. 3 is a distribution diagram of z score values obtained by the motor vehicle environmental protection detection analysis method based on the quartile algorithm of the present application;
FIG. 4 is a schematic structural diagram of an embodiment of an environmental protection inspection analysis system for a motor vehicle based on a quartile algorithm according to the present application;
fig. 5 is a schematic structural diagram of a specific embodiment of the motor vehicle environmental protection detection analysis device based on the quartile algorithm.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application. The step numbers in the following embodiments are provided only for convenience of illustration, the order between the steps is not limited at all, and the execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.
The method in the embodiment of the application can be applied to terminal equipment, a server, software running in the terminal equipment or the server and the like. Here, the terminal device may be, but is not limited to, a tablet computer, a notebook computer, a desktop computer, and the like; the server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, and a big data and artificial intelligence platform.
Referring to fig. 1, the method mainly comprises the following steps:
in the embodiment of the application, for the motor vehicle to be inspected, the concentration of the exhaust gas emitted by the motor vehicle on the designated road can be detected, the designated road can be flexibly set and selected according to needs, for example, a plurality of detection stations can be arranged on one road, then the name of each detection station and the adopted detection mode are marked, then when the motor vehicle to be detected is detected and analyzed, the motor vehicle to be detected runs on the road provided with the detection stations through testers or other related personnel, and then target detection data are obtained from one or more detection stations on the road. When the motor vehicle is detected, the detection can be performed for multiple times, the data obtained by the detection is taken as initial detection data, and then the average value of multiple groups of initial detection data is obtained, so that target detection data is obtained, and the precision of the finally obtained target detection data is improved. Moreover, when multiple detections are performed, multiple sets of initial detection data can be obtained by detection in different time periods, different drivers and different roads.
In the embodiment of the present application, the detection analysis of the exhaust gas may include one or more gases, such as: the target detection data may include at least one of hydrocarbon concentration data, carbon monoxide concentration data, nitrogen oxide concentration data, or the like, which are generated from combustion of gasoline or diesel, and may be harmful to human bodies and the environment when the concentration is high. For example, after carbon monoxide is inhaled into a human body, red blood cells lose oxygen carrying capacity, so that a patient is suffocated; nitrogen oxides, such as nitric oxide, while not harmful by themselves, are highly reactive with oxygen to produce hydrogen dioxide, a toxic and pungent gas that can damage the respiratory tract of the human body leading to various conditions and can contaminate water, soil and the atmosphere.
in the embodiment of the application, the exhaust emission of the motor vehicle is detected and evaluated through a comparison mode, namely, the detection data of the motor vehicle participating in comparison is selected, and the motor vehicle to be detected is analyzed. Specifically, because different types of motor vehicles have different emission levels, the motor vehicles of the same type need to be classified and compared, for example, a plurality of detection lines can be set according to the classification of different types of motor vehicles such as gasoline lines, heavy diesel lines, light diesel lines and the like, and are respectively analyzed and evaluated, so that whether the current motor vehicle exceeds the normal emission level is correctly and effectively determined. In the embodiment of the application, the type of the motor vehicle to be detected can be determined firstly, then the exhaust gas concentration data of the motor vehicles which belong to the same type as the motor vehicle to be detected and are discharged on the specified road in the historical detection data is selected, and the obtained data is recorded as the comparison detection data. Since there may be more past detection data, in order to ensure the accuracy of detection and analysis as much as possible, the data closest to the current may be selected from the historical detection data as the comparison detection data, and multiple sets of comparison detection data may be selected. It should be noted here that vehicles of the same type may also include the vehicle to be detected itself, for example, the current state may be detected and analyzed by the previous emission situation of the vehicle to be detected. In addition, in the embodiment of the application, when the exhaust gas concentration data is acquired, multiple groups of data acquired under different working condition states can be acquired, for example, the exhaust gas concentration data can be acquired by different online vehicle measurement methods such as a simple transient working condition method, a loading and decelerating working condition method and the like.
in the embodiment of the application, the comparison detection data can be processed through a quartile algorithm. Specifically, the processing procedure of the quartile algorithm includes:
step S1, a top quartile calculation method: for the same type of motor vehicles, sequencing the comparison detection data from small to large, then adding 1 to the number of the comparison detection data, dividing by 4, and calculating to obtain a result value as the upper quartile position of the item, wherein the formula is as follows:
in the formula, Q1 represents the upper quartile position number, and n represents the number of comparison detection data.
If the value of Q1 is an integer, the upper quartile value is the comparison detection data ordered at the position Q1, and when the value of Q1 is not an integer, a weighting calculation is required, and the specific calculation method is as follows: weighting calculation is carried out on two adjacent contrast detection data ranked at the position Q1: for example, rounding the upper quartile position number to a larger value to obtain a first value, and sorting the contrast detection data at the first value as P1L; rounding the upper quartile position number to a smaller value to obtain a second value, and sorting the contrast detection data at the second value can be recorded as P1S. Then, by sorting three quarters of the contrast detection data at the second value and adding one quarter of the first value, the upper quartile value can be obtained, and the formula is: p1 ═ P1S × 3/4+ P1L × 1/4.
Step S2, median calculation method: for the same type of motor vehicles, sequencing the comparison detection data from small to large, then adding 1 to the number of the comparison detection data, dividing by 2, and calculating to obtain a result value as the median position of the item, wherein the formula is as follows: q2 ═ (n + 1)/2; in the formula, Q2 represents the number of median positions, and n represents the number of comparison detection data. If the value of Q2 is an integer, then the median value is the contrast check data ordered at position Q2, and when the value of Q2 is not an integer, a weighting calculation is also required, the calculation method is: and averaging two adjacent comparison detection data of Q2 to obtain a median value.
Step S3, the following quartile calculation method: for the same type of motor vehicles, sequencing the comparison detection data from small to large, then adding 1 to the number of the comparison detection data, dividing by 4, and multiplying by 3, wherein the calculated result value is the position of the lower quartile of the item, and the formula is as follows:
in the formula, Q3 represents the lower quartile position number, and n represents the number of comparison detection data.
If the value of Q3 is an integer, the next quartile value is the contrast detection data sorted at the position Q3, and when the value Q3 is not an integer, weighting calculation is required, the specific calculation method is similar to the foregoing step S1, for example, the number of the next quartile position is rounded up to obtain a third value, and the contrast detection data sorted at the third value can be recorded as P2L; rounding the lower quartile position number to a smaller value to obtain a fourth numerical value, and recording the comparison detection data sequenced at the fourth numerical value as P2S, wherein the calculation formula of the lower quartile numerical value is as follows:
step S4, IQR (quadridentate spacing) calculation method: the absolute value of the difference between the lower quartile value and the upper quartile value.
in the embodiment of the application, after the median value and the quartile distance are obtained, the z score value can be determined according to the target detection data of the motor vehicle to be detected, and specifically, the z score value can be determined through a formula
And determining a z-score value of the motor vehicle, wherein z is the z-score value of the motor vehicle, X represents target detection data, X represents a median value, a is a set constant value, and IQR represents a quarter-bit spacing. In general, the value of a may be set to 0.7413.
And step 160, determining an environmental protection detection analysis result of the motor vehicle according to the value of the z fraction value.
In the embodiment of the application, after the z score value of the motor vehicle is obtained through calculation, the exhaust emission level of the motor vehicle, namely the environmental protection detection analysis result, can be determined according to the preset score interval. For example, in some embodiments, the results of the environmental detection analysis may be classified as "qualified," suspect, "" disqualified. When the value of a is set to 0.7413, the evaluation criterion according to the z score value can be set as follows: when the absolute value of z is less than or equal to 2, the environmental protection detection analysis is a qualified result, which indicates that the working condition of the motor vehicle is good, and the exhaust emission basically meets the environmental protection requirement; when 2 < | z | < 3, the environmental protection detection analysis is a suspicious result, which indicates that the exhaust emission of the motor vehicle may have problems and further detection and verification are needed; when the absolute value of z is more than or equal to 3, the environmental protection detection analysis is an unsatisfactory result, which indicates that the detection result of the motor vehicle detection line does not meet the supervision and inspection management requirements of environmental protection departments, and a comparison test and calibration of detection equipment need to be performed on the detection line inside the environmental protection mechanism.
Optionally, in some embodiments, the method in the present application may further include the following steps:
step 170, sorting the z score values corresponding to a plurality of motor vehicles of the same type;
and step 180, taking the sequence value of the motor vehicle sequence as a horizontal axis coordinate, taking the corresponding z score value as a vertical axis coordinate, and generating a z score value distribution graph of the motor vehicle.
In this embodiment, whether a certain type of vehicle has a serious exhaust emission problem may also be analyzed for a certain type of vehicle of a fixed vehicle type, and in some embodiments, a z score value corresponding to a plurality of vehicles of the same type may be obtained, and a histogram may be established, for example, fig. 2 is a histogram of z score values determined by a certain type of vehicle according to carbon monoxide concentration data, where a horizontal axis represents the z score value and a vertical axis represents the number of vehicles at the z score value, and when more vehicles are located on both sides, it is indicated that the vehicle of the type has the emission pollution problem of carbon monoxide. In some embodiments, the z-score values corresponding to a plurality of vehicles of the same type may be sorted, and then the sorted values of the vehicles are taken as horizontal axis coordinates, and the corresponding z-score values are taken as vertical axis coordinates, so as to generate a z-score value distribution graph of the vehicles, referring to fig. 3, fig. 3 is a z-score value distribution graph determined by a certain type of vehicle according to the carbon monoxide concentration data, a curve in the distribution graph may be fitted by a straight line, and when the slope of the straight line is larger, it indicates that the vehicle of the type has the carbon monoxide emission pollution problem.
It can be understood that the method in the embodiment of the application can compare and analyze the evaluation scores of the same pollutant detection item of the motor vehicle under different detection methods such as a simple transient condition method, a loading and decelerating condition method and the like, so that comprehensive evaluation results of a gasoline line, a heavy diesel line, a light diesel line and the like of a motor vehicle environmental inspection mechanism can be formed, supervision, inspection and management of the motor vehicle environmental inspection mechanism by an ecological environment department are facilitated, and the accuracy and reliability of environmental-friendly periodic inspection information of the detected motor vehicle are improved.
The following describes in detail a vehicle environmental protection detection analysis system based on a quartile algorithm according to an embodiment of the present application with reference to the drawings.
Referring to fig. 4, the system for detecting and analyzing environmental protection of a motor vehicle based on a quartile algorithm provided in the embodiment of the present application includes:
the detection module 101 is used for detecting the concentration of the exhaust gas emitted by the motor vehicle to obtain target detection data;
the acquisition module 102 is used for acquiring the concentration of the exhaust gas emitted by the batch of motor vehicles of the same type to obtain a plurality of groups of comparison detection data;
the processing module 103 is configured to process the comparison detection data through a quartile algorithm to obtain an upper quartile value, a middle value and a lower quartile value of the comparison detection data;
a determining module 104, configured to determine a quartile distance between the comparison detection data according to the upper quartile value and the lower quartile value;
the calculating module 105 is used for determining a z-fraction value of the motor vehicle based on the target detection data, the median value and the quartile distance by a z-fraction calculating method;
and the analysis module 106 is used for determining an environment-friendly detection analysis result of the motor vehicle according to the magnitude of the z-fraction value.
It is to be understood that the contents in the foregoing method embodiments are all applicable to this system embodiment, the functions specifically implemented by this system embodiment are the same as those in the foregoing method embodiment, and the advantageous effects achieved by this system embodiment are also the same as those achieved by the foregoing method embodiment.
Referring to fig. 5, an embodiment of the present application provides a motor vehicle environmental protection detection analysis apparatus based on a quartile algorithm, including:
at least one processor 201;
at least one memory 202 for storing at least one program;
the at least one program, when executed by the at least one processor 201, causes the at least one processor 201 to implement a method for environmentally friendly detection and analysis of a motor vehicle based on a quartile algorithm.
Similarly, the contents of the method embodiments are all applicable to the apparatus embodiments, the functions specifically implemented by the apparatus embodiments are the same as the method embodiments, and the beneficial effects achieved by the apparatus embodiments are also the same as the beneficial effects achieved by the method embodiments.
The embodiment of the present application further provides a computer-readable storage medium, in which a program executable by the processor 201 is stored, and the program executable by the processor 201 is used for executing the above-mentioned environment-friendly detection and analysis method for the vehicle based on the quartile algorithm when executed by the processor 201.
Similarly, the contents in the above method embodiments are all applicable to the computer-readable storage medium embodiments, the functions specifically implemented by the computer-readable storage medium embodiments are the same as those in the above method embodiments, and the beneficial effects achieved by the computer-readable storage medium embodiments are also the same as those achieved by the above method embodiments.
In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present application are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.
Furthermore, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion regarding the actual implementation of each module is not necessary for an understanding of the present application. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the present application as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the application, which is defined by the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the foregoing description of the specification, reference to the description of "one embodiment/example," "another embodiment/example," or "certain embodiments/examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: numerous changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.
While the present application has been described with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A motor vehicle environmental protection detection analysis method based on a quartile algorithm is characterized by comprising the following steps:
detecting the concentration of the exhaust gas emitted by the motor vehicle to obtain target detection data;
obtaining the concentration of the exhaust gas emitted by the batch of motor vehicles of the same type to obtain a plurality of groups of comparison detection data;
processing the comparison detection data through a quartile algorithm to obtain an upper quartile numerical value, a middle numerical value and a lower quartile numerical value of the comparison detection data;
determining a quartile distance of the comparison detection data according to the upper quartile value and the lower quartile value;
determining a z-fraction value of the motor vehicle based on the target detection data, the median value and the quartile range by a z-fraction calculation method;
and determining an environment-friendly detection analysis result of the motor vehicle according to the z score value.
2. The environmentally friendly motor vehicle detection and analysis method based on the quartile algorithm according to claim 1, wherein the detecting the concentration of the exhaust gas emitted by the motor vehicle to obtain target detection data comprises:
detecting the motor vehicle for multiple times on multiple different roads or under the condition of different drivers to obtain multiple groups of initial detection data;
and calculating the average value of the initial detection data to obtain the target detection data.
3. The environmentally friendly automotive detection and analysis method based on the quartile algorithm according to any one of claims 1 or 2, wherein the target detection data comprises at least one of hydrocarbon concentration data, carbon monoxide concentration data or nitrogen oxide concentration data.
4. The environmentally friendly motor vehicle detection and analysis method based on the quartile algorithm according to claim 1, wherein the upper quartile value is calculated by the following steps:
sequencing the comparison detection data from small to large, and determining the number of the comparison detection data;
determining the upper quartile position number according to the number of the comparison detection data by a formula Q1 ═ n +1 x 1/4; in the formula, Q1 represents the upper quartile position number, and n represents the number of comparison detection data;
and if the upper quartile position number is an integer, using the comparison detection data sequenced in the upper quartile position number as an upper quartile numerical value.
5. The environmentally friendly motor vehicle detection and analysis method based on the quartile algorithm of claim 4, wherein the method further comprises:
if the upper quartile position number is not an integer, rounding the upper quartile position number to a larger value to obtain a first numerical value; rounding the upper quartile position to obtain a second numerical value;
and carrying out weighted summation on the comparison detection data which are sequenced at the first numerical value and the second numerical value to obtain the upper quartile numerical value.
6. The environmentally friendly motor vehicle inspection analysis method based on quartile algorithm of claim 5, wherein the weighted summation of the comparison inspection data sorted at the first and second values to obtain the upper quartile value comprises:
determining the upper quartile value by the formula P1 ═ P1S × 3/4+ P1L × 1/4;
in the formula, P1S is the contrast detection data sorted at the second value, and P1L is the contrast detection data sorted at the first value.
7. The environmentally friendly motor vehicle detection and analysis method based on the quartile algorithm of claim 1, wherein the median value is calculated by the following steps:
sequencing the comparison detection data from small to large, and determining the number of the comparison detection data;
determining the position number of the median according to the number of the comparison detection data by a formula Q2 ═ n +1 x 1/2; in the formula, Q2 represents the number of median positions, and n represents the number of comparison detection data;
and if the median position number is an integer, taking the contrast detection data sequenced in the median position number as a median value.
8. The environmentally friendly motor vehicle detection and analysis method based on quartile algorithm of claim 1, wherein the determining the z-fraction value of the motor vehicle based on the target detection data, the median value and the quartile range by the z-fraction calculation method comprises:
by the formula
Determining a z-score value of the motor vehicle;
wherein z is a z score value of the motor vehicle, X represents target detection data, X represents a median value, a is a set constant value, and IQR represents a quarter-bit spacing.
9. The environmentally friendly motor vehicle detection and analysis method based on the quartile algorithm of claim 1, further comprising the steps of:
sorting the z score values corresponding to a plurality of motor vehicles of the same type;
and taking the sequence value of the motor vehicle sequence as a horizontal axis coordinate, and taking the corresponding z score value as a vertical axis coordinate to generate a z score value distribution diagram of the motor vehicle.
10. A motor vehicle environmental protection detection analysis system based on quartile algorithm, characterized by includes:
the detection module is used for detecting the concentration of the exhaust gas discharged by the motor vehicle to obtain target detection data;
the acquisition module is used for acquiring the concentration of the exhaust gas emitted by the batch of motor vehicles of the same type to obtain a plurality of groups of comparison detection data;
the processing module is used for processing the comparison detection data through a quartile algorithm to obtain an upper quartile numerical value, a middle numerical value and a lower quartile numerical value of the comparison detection data;
the determining module is used for determining the quartile interval of the comparison detection data according to the upper quartile value and the lower quartile value;
the calculation module is used for determining a z-fraction value of the motor vehicle based on the target detection data, the median value and the quartile distance by a z-fraction calculation method;
and the analysis module is used for determining the environment-friendly detection analysis result of the motor vehicle according to the magnitude of the z score value.
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