Heavy diesel vehicle tampering behavior identification method and system, storage medium and terminal

Abstract

The invention relates to a heavy diesel vehicle tampering behavior recognition method and system, a storage medium and a terminal. The method comprises the steps that vehicle CVN information is acquired; when the vehicle CVN information is inconsistent with preset standard CVN information, accumulating risk points, and obtaining vehicle emission index information; comparing the vehicle emission index information with preset initial reference index information to determine the number of distinguishing index items, and accumulating risk points according to the number of distinguishing index items; if the risk integral is greater than a preset tampering risk value, defining the vehicle as a suspected vehicle, and pushing and outputting the vehicle CVN information of the suspected vehicle; determining vehicle positioning information of the suspected vehicle according to the vehicle CVN information; real vehicle monitoring detection is carried out on the suspected vehicle according to the vehicle CVN information and the vehicle positioning information, and vehicle operation auxiliary information is acquired; and outputting a judgment result when the vehicle operation auxiliary information is consistent with the preset cheating type information. The tampered vehicle is recognized through the method, and the recognition efficiency is high.

Description

Technical Field

[0001] The present invention relates to the field of vehicles, and in particular to a method, system, storage medium and terminal for identifying tampering behavior of a heavy diesel vehicle. Background Art

[0002] Heavy-duty diesel trucks produce a large amount of exhaust pollutants when driving and are an important source of urban pollutant emissions. They pose a serious threat to the physical and mental health of the people and have become a key target of national mobile source emission supervision and management.

[0003] The exhaust gas emitted by trucks contains a large amount of nitrogen oxides. At present, the main method for controlling nitrogen oxide emissions from trucks is to install a catalytic reduction device on the vehicle to decompose the nitrogen oxides. Since urea needs to be added to the catalytic reduction device during use to catalyze the nitrogen oxides, this will increase additional operating costs for freight vehicle companies. In actual testing, it was found that many companies illegally tampered with diesel vehicles through cheating in order to reduce the operating costs of diesel vehicles. This tampering is usually difficult to monitor and detect directly through the vehicle remote monitoring terminal, and it needs to be solved urgently. Summary of the invention

[0004] In order to effectively monitor and investigate illegally tampered diesel vehicles, the present invention provides a method, system, storage medium and terminal for identifying tampering behavior of heavy-duty diesel vehicles.

[0005] In a first aspect, the present invention provides a method for identifying tampering behavior of a heavy-duty diesel vehicle, which adopts the following technical solution:

[0006] A method for identifying tampering behavior of a heavy-duty diesel vehicle, comprising:

[0007] Get vehicle CVN information;

[0008] When the vehicle CVN information is inconsistent with the preset standard CVN information, accumulating risk points and obtaining vehicle emission index information, wherein the vehicle emission index information includes multiple index items;

[0009] Compare the vehicle emission index information with the preset initial benchmark index information to determine the number of distinguishing index items, and accumulate risk points according to the number of distinguishing index items;

[0010] If the risk score is greater than the preset tampering risk value, it is defined as a suspected vehicle, and the vehicle CVN information of the suspected vehicle is pushed out;

[0011] Determine the vehicle location information of the suspected vehicle based on the vehicle CVN information;

[0012] Conduct real-vehicle monitoring and detection on suspected vehicles based on vehicle CVN information and vehicle positioning information, and obtain vehicle operation auxiliary information;

[0013] When the vehicle operation auxiliary information is consistent with the preset cheating type information, the judgment result is output.

[0014] By adopting the above technical solution, the risk score of the vehicle is first estimated through the system. If the risk score of the vehicle is high, it means that there is a high probability that the vehicle has been tampered with. At this time, the information of the vehicle is pushed to the staff, and the staff conducts real-life monitoring and investigation of the vehicle, thereby effectively identifying and investigating the tampered vehicles and improving the identification efficiency.

[0015] Optionally, the vehicle operation auxiliary information acquisition method includes:

[0016] Obtain the fuel consumption, urea level change, and SCR upstream and downstream emission concentration difference of the suspected vehicle when running the preset detection trip;

[0017] Match the corresponding urea consumption according to the fuel consumption;

[0018] If the change in urea liquid level is less than the urea consumption, it is defined as a sensor abnormality. The sensor is detected according to the sensor abnormality detection method, and a sensor abnormality prompt is output;

[0019] Based on the fact that the change in urea liquid level is not less than the urea consumption, the output of the vehicle normal prompt or the acquisition of urea content information in the urea solution is determined according to the comparison relationship between the upstream and downstream emission concentration difference of the SCR and the preset reference difference range;

[0020] When the urea content information is lower than a preset reference urea content, a vehicle tampering prompt is output.

[0021] By adopting the above technical solution, by analyzing the actual urea liquid level change and the theoretical urea consumption, it is determined whether the sensor is abnormal or the urea itself is added abnormally, which is highly efficient.

[0022] Optionally, the sensor anomaly detection method includes:

[0023] Obtain the median SCR inlet temperature when the suspected vehicle is running;

[0024] When the median of the SCR inlet temperature is greater than the preset urea injection start point temperature, the urea injection start trigger information is obtained;

[0025] Determine whether to output a vehicle normal prompt or a vehicle tampering prompt according to a comparison between the urea injection trigger information and the preset standard injection information;

[0026] Based on the median of the SCR inlet temperature being no greater than the urea starting injection point temperature, the sensor image information is obtained at the installation position of the sensor;

[0027] Determine a detection gap between the sensor and a preset detected object from a preset reference installation database according to the sensor image information;

[0028] According to the comparison between the detection gap and the preset reference gap, it is determined whether to output a vehicle normal prompt or a vehicle tampering prompt.

[0029] By adopting the above technical solution, by analyzing the median SCR inlet temperature and the urea starting injection point temperature, it is possible to determine whether the vehicle has tampered with the sensor or the internal program, and determine the method of tampering, which is highly efficient.

[0030] Optionally, a method for determining whether a sensor has been tampered with includes:

[0031] Retrieve the historical data of the median temperature of the SCR inlet for a preset time period from the preset historical database;

[0032] Establish a temperature and time curve based on the historical data of the median SCR inlet temperature and the time period;

[0033] Determine the decay angle based on the temperature and time curve;

[0034] Since the attenuation angle is not 0, it is defined as natural looseness, and the vehicle is output as normal;

[0035] Based on the decay angle being 0, the starting temperature value is determined by establishing a temperature and time curve;

[0036] When the starting temperature value is not greater than the urea starting injection point temperature, it is defined as human tampering and a vehicle tampering prompt is output.

[0037] By adopting the above technical solution, a graph curve is established for the median historical data of the SCR inlet temperature and the time period. According to the slope of the graph line and the starting temperature of the graph curve, it can be determined whether the temperature acquisition error of the sensor is caused by natural looseness or by manual tampering of the sensor. Identification through the graph curve is more efficient.

[0038] Optionally, the vehicle operation auxiliary information acquisition method further includes:

[0039] Obtain the running speed, running torque and nitrogen oxide emission concentration of the vehicle during operation;

[0040] Generate a concentration model image according to the operating speed, the operating torque and the nitrogen oxide emission concentration;

[0041] In the concentration model image, the nitrogen oxide emission concentration is set from light to dark color output from low to high;

[0042] Determining an identification range area according to a preset speed range and a preset torque range;

[0043] Determine the area of ​​the dark block within the preset recognition range;

[0044] Whether to output a normal vehicle prompt or a vehicle tampering prompt is determined based on a comparison between the dark-colored image block area and a preset reference image block area.

[0045] By adopting the above technical solution, an image model of nitrogen oxide emission concentration is established in the form of images and color depths, and the nitrogen oxide emission concentration is analyzed from the image model. By comparing whether the emissions of the vehicle to be tested are significantly different from those of normal vehicles, it is intuitively determined whether the vehicle has been tampered with.

[0046] Optionally, also include:

[0047] Determine the location area of ​​the vehicle according to the vehicle location information;

[0048] According to the location area of ​​the vehicle, the distribution of CVN-changed vehicles in the area is obtained by querying from the preset CVN database;

[0049] Determine the range of cluster vehicles based on the distribution of CVN-changed vehicles;

[0050] When the vehicle positioning information falls within the range of cluster vehicles, risk points are accumulated, and the vehicle is set as a suspected vehicle or a key inspection vehicle based on the vehicle attribution identification method.

[0051] By adopting the above technical solution, vehicles within the range of the cluster vehicle may belong to the same company and have a high probability of being tampered with. By analyzing whether the vehicle is within the range of the cluster vehicle in the area, it is possible to effectively determine whether the vehicle has been tampered with to a certain extent.

[0052] Optionally, the vehicle ownership identification method includes:

[0053] According to the vehicle CVN information, the historical positioning track of the vehicle and the corresponding positioning point time are retrieved from the preset historical track database;

[0054] Determine the suspected positioning points and the number of suspected positioning points that fall within the cluster vehicle range according to the historical positioning trajectory and the cluster vehicle range;

[0055] Calculate the ratio of the number of suspected positioning points to the historical positioning trajectory, and define the ratio as the suspected probability;

[0056] When the suspected probability is not greater than the preset reference probability, it is a passing vehicle and the vehicle is set as a suspected vehicle;

[0057] When the suspected probability is greater than the preset reference probability, the discrete degree of the positioning point time corresponding to the suspected positioning point is calculated;

[0058] Based on the large degree of dispersion, it is a passing vehicle and is set as a suspected vehicle;

[0059] Since the discreteness is small, it is a local vehicle and is set as a key vehicle for inspection.

[0060] By adopting the above technical solution, the probability that a vehicle belongs to the range of cluster vehicles is determined according to the proportion of the vehicle's historical trajectory falling into the range of cluster vehicles. A larger proportion indicates a larger probability. When the proportion is large, the ownership of the vehicle is further determined according to the discrete degree of the positioning point time corresponding to the suspected positioning point. The ownership of the vehicle can be effectively identified according to the order or disorder of time.

[0061] In the second aspect, the present application provides a vehicle tampering behavior recognition system, which adopts the following technical solutions:

[0062] A vehicle tampering behavior recognition system, comprising:

[0063] The acquisition module is used to obtain vehicle CVN information, vehicle emission index information, vehicle operation auxiliary information, fuel consumption, urea liquid level change, SCR upstream and downstream emission concentration difference, SCR inlet temperature median of the suspected vehicle when running, urea injection trigger information, operating speed, operating torque, and nitrogen oxide emission concentration;

[0064] A memory for storing a program of any one of the above-mentioned methods for identifying tampering behavior of heavy-duty diesel vehicles;

[0065] The program in the processor and the memory can be loaded and executed by the processor and implement any of the above-mentioned methods for identifying tampering behavior of heavy-duty diesel vehicles.

[0066] In a third aspect, the present application provides a computer storage medium capable of storing a corresponding program, using the following technical solution:

[0067] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned methods for identifying tampering behavior of heavy-duty diesel vehicles.

[0068] In a fourth aspect, the present application provides an intelligent terminal, which adopts the following technical solution:

[0069] An intelligent terminal includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute any one of the above-mentioned methods for identifying tampering behavior of heavy-duty diesel vehicles.

[0070] In summary, the present application includes at least one of the following beneficial technical effects:

[0071] 1. The system estimates the risk score of the vehicle. If the risk score of the vehicle is high, it means that the vehicle is likely to have been tampered with. At this time, the vehicle information is pushed to the staff, who will monitor and investigate the vehicle in real time, so that the tampered vehicle can be effectively identified and investigated, improving the identification efficiency;

[0072] 2. By analyzing the actual urea level change and theoretical urea consumption of the vehicle, as well as the median SCR inlet temperature and urea injection start point temperature, it is possible to effectively identify whether the sensor and urea have been tampered with;

[0073] 3. Analyze whether the vehicle is in the cluster vehicle range of the area through vehicle positioning information, and then determine the probability that the vehicle belongs to the cluster vehicle range based on the proportion of the vehicle's historical trajectory falling into the cluster vehicle range. Finally, the vehicle's ownership is further determined based on the discrete degree of the positioning point time corresponding to the suspected positioning point, thereby effectively identifying whether the vehicle has been tampered with. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 is a method flow chart of a method for identifying tampering behavior of a heavy-duty diesel vehicle according to an embodiment of the present invention;

[0075] Figure 2 is a method flow chart of a method for obtaining vehicle operation auxiliary information according to an embodiment of the present invention;

[0076] Figure 3 is a method flow chart of a sensor abnormality detection method according to an embodiment of the present invention;

[0077] Figure 4 is a flow chart of a method for determining whether a sensor has been tampered with manually according to an embodiment of the present invention;

[0078] Figure 5 is a method flow chart of a method for analyzing a vehicle tampering risk based on location information according to an embodiment of the present invention;

[0079] Figure 6 It is a method flow chart of the vehicle ownership identification method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0081] The embodiment of the present application discloses a method for identifying tampering behavior of a heavy-duty diesel vehicle.

[0082] Reference Figure 1 , a method for identifying tampering behavior of heavy-duty diesel vehicles comprises the following steps:

[0083] Step S100: Obtain vehicle CVN information.

[0084] The CVN in the vehicle CVN information is a key identifier that is primarily used for calibration verification of the vehicle's engine control module. The purpose of the CVN is to ensure the integrity and consistency of the engine control module's calibration files, helping to prevent unauthorized modification or manipulation.

[0085] The OBD vehicle electronic control system can remotely query and retrieve the vehicle's CVN information from the system.

[0086] Step S101: when the vehicle CVN information is inconsistent with the preset standard CVN information, risk points are accumulated and vehicle emission index information is obtained, wherein the vehicle emission index information includes a plurality of index items.

[0087] The CVN of a vehicle is usually not allowed to be changed at will unless someone tampered with it illegally. Therefore, after obtaining the CVN information of the vehicle, it is necessary to determine whether the CVN information of the vehicle has been tampered with, because when the emission index and other parameters of the vehicle are changed, the CVN information of the vehicle may change.

[0088] The standard CVN information refers to the CVN value of the vehicle when it leaves the factory. This CVN value is equivalent to the vehicle's ID card and is generally unique and unchanged, so it will not be elaborated here.

[0089] When the vehicle CVN information is inconsistent with the standard CVN information, it means that the vehicle CVN information has been changed, which may be a risk of tampering, or it may be caused by normal vehicle modification.

[0090] The risk score refers to a parameter used to pre-evaluate the probability of vehicle tampering before excluding inspectors from conducting actual vehicle inspections. The risk score is related to the changes in the vehicle's emission indicators. The larger the risk score, the greater the probability that the vehicle has been tampered with.

[0091] When the vehicle CVN information is changed, 1 point will be added to the risk score because there is a possibility of tampering.

[0092] Vehicle emission index information refers to multiple parameter indicators related to emissions in the vehicle, and the vehicle emission index information is the index obtained after the vehicle CVN information is changed. The vehicle emission index information is remotely queried and retrieved from the system through the OBD vehicle electronic control system.

[0093] If individuals or car companies tamper with vehicles in order to reduce the operating costs of urea, the vehicle emission index information may be different from the standard indicators, and there may be situations where the parameters are not within the specified range or the parameters are blocked and cannot be viewed. Due to damage to the vehicle itself, it may also cause deviations in multiple indicators in the vehicle emission index information. Therefore, the vehicle emission index information can only be used to determine whether the vehicle has a tampering risk, but cannot be determined. The vehicle emission index information cannot determine whether the vehicle has been tampered with in structure or procedure.

[0094] Step S102: Compare the vehicle emission index information with the preset initial benchmark index information to determine the number of distinguishing index items, and accumulate risk points according to the number of distinguishing index items.

[0095] The benchmark standard information is the emission index before the vehicle CVN information corresponding to the vehicle emission index information is changed, and is also the fixed qualified index for vehicle emissions, which will not be elaborated here.

[0096] By comparing the vehicle emission index information with the initial baseline index information, the number of different index items between the two can be determined. The risk score is increased according to the number of different index items. The more different index items there are, the greater the accumulated risk score is, indicating that the vehicle is more likely to be tampered with.

[0097] Step S103: If the risk score is greater than the preset tampering risk value, the vehicle is defined as a suspected vehicle, and the vehicle CVN information of the suspected vehicle is pushed and output.

[0098] The tampering risk value is a reference value set by the technician to determine whether the vehicle has been tampered with, which will not be elaborated here. When the risk score is not greater than the tampering risk value, it means that the probability of tampering with the vehicle is low, but because the vehicle has a number of different indicators, the vehicle will still appear in the monitoring of the OBD vehicle electronic control system. When the risk score is greater than the tampering risk value, the vehicle will be judged as a vehicle with a high suspicion of tampering. At this time, the CVN information of the vehicle will be pushed to the control terminal of the inspector for the actual vehicle inspection, and the inspector will inspect the actual vehicle.

[0099] Step S104: Determine the vehicle location information of the suspected vehicle according to the vehicle CVN information.

[0100] The vehicle positioning information refers to the current location of the vehicle. The vehicle CVN information is bound to the vehicle, matched with the vehicle CVN information through the OBD vehicle electronic control system, and then the vehicle positioning information is retrieved from the positioning chip in the vehicle through the vehicle CVN information.

[0101] Step S105: Perform real vehicle monitoring and detection on the suspected vehicle according to the vehicle CVN information and vehicle positioning information, and obtain vehicle operation auxiliary information.

[0102] Vehicle operation auxiliary information is various information obtained by inspectors from the actual vehicle during vehicle operation, which is used to determine whether the suspected vehicle has been tampered with, including urea conditions, sensor conditions, nitrogen oxide emissions, etc. The method of obtaining vehicle operation auxiliary information is not described here, and will be introduced in detail in the subsequent plan.

[0103] The inspectors will locate the vehicle based on the vehicle positioning information and conduct a full vehicle inspection or monitoring of the actual vehicle.

[0104] Step S106: When the vehicle operation auxiliary information is consistent with the preset cheating type information, a determination result is output.

[0105] Cheating type information refers to a database set up by technicians based on experience that contains various methods of illegally tampering with vehicles to reduce operating costs. It will not be elaborated here.

[0106] When the vehicle operation auxiliary information obtained matches one of the types in the cheating type information, it means that the vehicle is indeed suspected of illegal tampering. At this time, the identification is completed, the judgment result is output, and the investigator is prompted to investigate the vehicle. The judgment result includes tampered vehicles and normal vehicles, here it is tampered vehicles.

[0107] When the acquired vehicle operation auxiliary information is inconsistent with all types in the cheating type information, it means that the vehicle is a normal vehicle, and the determination result of the normal vehicle is output at this time.

[0108] Reference Figure 2 The vehicle operation auxiliary information acquisition method comprises the following steps:

[0109] Step S200: Obtaining the fuel consumption, urea liquid level change, and SCR upstream and downstream emission concentration difference of the suspected vehicle when running a preset detection trip.

[0110] The detection trip is a trip reference value set by the technicians to obtain the fuel consumption and urea liquid level change of the vehicle in a fixed trip, which will not be elaborated here.

[0111] Fuel consumption refers to the amount of fuel consumed during the test trip. The fuel consumption is acquired by the sensor in the fuel tank and recorded in the system.

[0112] The urea liquid level change refers to the change in the urea liquid level within the detection stroke. The urea liquid level change is obtained by a liquid level gauge set in the box and recorded in the system.

[0113] The SCR upstream and downstream emission concentration difference refers to the concentration of nitrogen oxides at the inlet and outlet of the SCR. The concentration difference of the SCR upstream and downstream emission is obtained by testing the concentration at the inlet and outlet respectively through the sensors installed on it and calculating the difference. The test results can be saved in the system. SCR is a catalytic reduction device in the vehicle, which can decompose the nitrogen oxides passing through it into nitrogen and water under the catalysis of urea.

[0114] Fuel consumption, urea level change and SCR upstream and downstream emission concentration difference can be retrieved from the system through the OBD vehicle electronic control system.

[0115] Step S201: Matching the corresponding urea consumption according to the fuel consumption.

[0116] In order to make the nitrogen oxides produced when fuel is consumed be catalyzed by urea to generate clean exhaust gas when discharged, a fixed proportion of urea is required for catalysis when fuel is consumed. The urea consumption corresponds to the fuel consumption one by one. The actual urea consumption that should be consumed can be determined based on the fuel consumption. The urea consumption here is the consumption obtained by theoretical calculation, not the actual consumption.

[0117] Under normal circumstances, the change in urea liquid level should be consistent with the urea consumption. If the vehicle is tampered with, the two may be inconsistent.

[0118] Step S2011: Based on the fact that the change in urea liquid level is less than the urea consumption, it is defined as a sensor abnormality, the sensor is detected according to a sensor abnormality detection method, and a sensor abnormality prompt is output.

[0119] If the actual urea level change is less than the theoretical urea consumption, there may be a sensor tampering problem. The sensor here is a temperature sensor installed at the SCR inlet. Urea will only be injected when the temperature at the SCR inlet reaches the set standard temperature. When the temperature detected by the temperature sensor is abnormal, the urea consumption may be less.

[0120] When the above-mentioned urea liquid level change is less than the urea consumption, a sensor abnormality signal will be output, which is used to alert the staff of possible tampering locations.

[0121] The sensor anomaly detection method is a method for detecting whether the sensor has been tampered with. It will not be described in detail here and will be introduced in detail in the subsequent solutions.

[0122] Step S2012: Based on the urea liquid level change being not less than the urea consumption, outputting a vehicle normal prompt or obtaining urea content information in the urea solution is determined according to a comparison relationship between the SCR upstream and downstream emission concentration difference and a preset reference difference range.

[0123] When the change in urea liquid level is not less than the urea consumption, it means that the sensor can obtain normal data and the change in urea liquid level meets the consumption requirements. At this time, check whether the emission concentration difference between upstream and downstream of the SCR is abnormal to determine whether there is abnormal addition of urea itself.

[0124] The benchmark difference range is a reference value set by technicians to measure whether the emission concentration difference between upstream and downstream of the SCR meets the standards.

[0125] When the SCR upstream and downstream emission concentration difference falls within the reference difference range, it means that the SCR upstream and downstream emission concentration difference meets the requirements. If the urea liquid level change also meets the requirements at this time, it means that the vehicle is a normal vehicle.

[0126] When the emission concentration difference between the upstream and downstream of the SCR does not fall within the reference difference range, it means that the emission concentration difference between the upstream and downstream of the SCR does not meet the requirements, the SCR does not completely catalyze the nitrogen oxides, and a large amount of nitrogen oxides are still discharged. If the urea liquid level change meets the consumption requirements at this time, the only possibility is that there is a problem with the urea itself. At this time, it is necessary to obtain the urea content information in the urea solution. There may be a problem with the urea content in the urea solution. The urea content in the urea solution can be obtained through the concentration sensor set in the urea tank.

[0127] Step S20121: When the urea content information is lower than a preset reference urea content, a vehicle tampering prompt is output.

[0128] The baseline urea content is the urea content specified by the standard for removing nitrogen oxides in SCR, which will not be elaborated here.

[0129] If the urea content information is lower than the benchmark urea content, it confirms that the urea has been tampered with. The abnormal addition of water to the urea solution makes the urea content lower, far lower than the benchmark urea content. Although the same amount of urea is consumed, this amount of urea cannot remove the preset nitrogen oxides, so it means that the vehicle is a tampered vehicle.

[0130] Reference Figure 3 ,The sensor anomaly detection method includes the following steps:

[0131] Step S300: Obtain the median SCR inlet temperature when the suspected vehicle is running.

[0132] The median SCR inlet temperature is the temperature value obtained by the temperature sensor installed at the SCR inlet. When the median SCR inlet temperature reaches the preset temperature, the system will inject urea into the SCR to treat nitrogen oxides.

[0133] Step S3011: when the median temperature of the SCR inlet is greater than the preset urea injection start point temperature, urea injection start trigger information is obtained.

[0134] The urea injection starting point temperature refers to the temperature set by the technician for the SCR to trigger the urea injection action signal. When the temperature of the SCR reaches the urea injection starting point temperature, the urea injection action will be triggered. I will not go into details here.

[0135] The urea injection trigger information is a signal for triggering the urea injection action, and can be directly obtained from the OBD vehicle electronic control system.

[0136] When the median SCR inlet temperature is greater than the preset urea injection start point temperature, the urea injection trigger information can be triggered under normal circumstances. If the program in the system is tampered with, the urea injection trigger information may not be triggered at this time, and the urea injection trigger information needs to be detected.

[0137] Step S30111: Determine whether to output a vehicle normal prompt or a vehicle tampering prompt based on the comparison between the urea injection trigger information and the preset standard injection information.

[0138] The standard injection information is a standard signal set by the technician in the program to trigger the urea injection action, which will not be described in detail here.

[0139] The acquired urea injection trigger information is compared with the standard injection information. If the two are consistent, the urea injection trigger information can be triggered when the median of the SCR inlet temperature is greater than the urea injection point temperature, indicating that the vehicle is a normal vehicle, and a vehicle normal prompt is output.

[0140] If the two are inconsistent, when the median SCR inlet temperature is greater than the urea start-up temperature, the urea start-up trigger information cannot be triggered. This indicates that the vehicle is a tampered vehicle, and a vehicle tampering prompt is output to prompt the staff to investigate the vehicle.

[0141] Step S3012: Based on the median of the SCR inlet temperature being no greater than the urea injection start temperature, sensor image information is acquired at the installation position of the sensor.

[0142] The median SCR inlet temperature cannot reach the urea starting injection point temperature, indicating that the sensor used to detect the SCR inlet temperature may be abnormal, causing the actual temperature that reaches the standard to be output too low after the sensor detection. At this time, the sensor image information is obtained. The sensor image information is obtained by the staff holding the OBA diagnostic instrument to take pictures. The OBA diagnostic instrument has an integrated camera function.

[0143] Step S30121: Determine the detection gap between the sensor and the preset detected part from a preset reference installation database according to the sensor image information.

[0144] The reference installation database is a database obtained by machine learning and contains images of sensors normally installed at installation locations, which will not be described in detail here.

[0145] The detection gap refers to the distance between the sensor and the installation location. Under normal conditions, the two should fit each other to achieve temperature collection.

[0146] By matching the sensor image information with the reference installation database, the gap image between the sensor and the installation position can be determined, and the distance of the detection gap can be obtained through image recognition.

[0147] Step S30122: Determine whether to output a vehicle normal prompt or a vehicle tampering prompt based on the comparison between the detection gap and the preset reference gap.

[0148] The reference gap is the standard gap set by the technicians for the sensor to collect temperature at the installation position, which will not be described in detail here.

[0149] If the detection gap is smaller than the reference gap, it means that the sensor is installed normally and the vehicle is normal.

[0150] If the detection gap is not smaller than the reference gap, it means that the sensor may have been raised during installation, causing a gap between the two. At this time, when the temperature is collected through the sensor, the temperature will be lower than the normal temperature value. If the above situation occurs, a vehicle tampering prompt will be output to prompt the staff to investigate.

[0151] Reference Figure 4 , there is a gap between the sensor and the installation position, which may be intentional tampering or the sensor may become loose due to vibration when the vehicle is driving. The method for determining whether the sensor has been tampered with includes the following steps:

[0152] Step S400: Retrieving historical data of the median SCR inlet temperature in a preset time period from a preset historical database.

[0153] The historical database is a database stored in the system and contains various historical data of the vehicle, which will not be described in detail here. The preset time period here refers to the time from the initial installation of the sensor to the time when the sensor is marked as a suspected tampered vehicle, which will not be described in detail here. The historical data of the median SCR inlet temperature is stored in the historical database, and the historical data of the median SCR inlet temperature can be retrieved from the historical database.

[0154] Step S401: establishing a temperature-time curve according to the SCR inlet temperature median historical data and the time period.

[0155] By graphing the historical data of the median SCR inlet temperature and the time period, the relationship between the two can be more directly determined.

[0156] Step S402: Determine the attenuation angle according to the temperature and time curve.

[0157] The attenuation angle refers to the slope of the curve in the temperature and time curve. The attenuation angle can be directly obtained from the temperature and time curve. The actual meaning of the attenuation angle is: after the sensor is installed at the installation location, whether the median SCR inlet temperature changes with time.

[0158] Step S4021: Based on the fact that the attenuation angle is not 0, it is defined as natural looseness, and a vehicle normal prompt is output.

[0159] If the attenuation angle is not 0, it means that the median SCR inlet temperature changes over time. At this time, the reason why the sensor collects a smaller SCR inlet temperature is that the sensor naturally loosens due to vehicle vibration, not because of human tampering with the sensor.

[0160] Step S4022: Based on the attenuation angle being 0, determine the starting temperature value by establishing a temperature and time curve.

[0161] If the attenuation angle is 0, the median SCR inlet temperature does not change with time, and remains unchanged with time, eliminating the possibility of the sensor loosening naturally. The starting temperature value refers to the temperature corresponding to the starting point of the temperature and time curve, which can be directly obtained from the curve. Its actual meaning is the median SCR inlet temperature obtained when the sensor is first installed.

[0162] Step S40221: When the starting temperature value is not greater than the urea injection starting point temperature, it is defined as human tampering, and a vehicle tampering prompt is output.

[0163] If the starting temperature value is not greater than the urea starting injection point temperature, it means that the sensor has been tampered with and raised during installation, and a vehicle tampering prompt is output at this time.

[0164] The vehicle operation auxiliary information acquisition method also includes the following steps:

[0165] Step S500: Acquire the running speed, running torque and nitrogen oxide emission concentration of the vehicle during operation.

[0166] The operating speed and operating torque can be retrieved from the system through the OBA automotive electronic system. The nitrogen oxide emission concentration refers to the nitrogen oxide concentration emitted from the SCR, which is detected by the exhaust gas concentration sensor installed at the rear of the vehicle and stored in the system.

[0167] Step S501: Generate a concentration model image according to the operating speed, the operating torque and the nitrogen oxide emission concentration.

[0168] The concentration model image is an image that includes parameters such as operating speed, operating torque and nitrogen oxide emission concentration. The concentration model image is generated by detecting the nitrogen oxide emission concentration at each range of operating speed and operating torque. The nitrogen oxide emission concentration at each range of operating speed and operating torque can be determined from the concentration model image.

[0169] Step S502: setting the color output of the nitrogen oxide emission concentration from low to high in the concentration model image from light to dark.

[0170] By setting different concentrations of nitrogen oxide emissions according to color depth, the change of nitrogen oxide emission concentration in various ranges of operating speed and operating torque can be intuitively reflected from the concentration model image.

[0171] Step S503: determining an identification range area according to a preset speed range and a preset torque range.

[0172] The preset speed range and the preset torque range are respectively the main torque range and speed range when the vehicle is in normal operation. The identification range area is used to compare the range area of ​​the exhaust emission conditions of a normal vehicle and an abnormal vehicle.

[0173] Step S504: Determine the area of ​​the dark-colored image block within the preset recognition range.

[0174] Depending on the concentration of nitrogen oxide emissions, different shades of color blocks will appear in the concentration model image. Deep blocks represent higher concentrations of nitrogen oxide emissions, and light blocks represent lower concentrations of nitrogen oxide emissions. The area of ​​the dark blocks is the area occupied by the dark blocks in the recognition range. The larger the area, the higher the concentration of nitrogen oxide emissions in the main torque range and speed range.

[0175] Step S505: Determine whether to output a vehicle normal prompt or a vehicle tampering prompt based on a comparison between the dark image block area and a preset reference image block area.

[0176] The reference block area is the dark block area within the identification range of the nitrogen oxide emission concentration of a normal vehicle in the main torque range and speed range, which is used for comparison with abnormal vehicles and will not be elaborated here.

[0177] When the area of ​​the dark block in the recognition range is larger than the area of ​​the reference block, it means that the nitrogen oxide emission concentration of the vehicle in the main torque range and speed range is greater than that of a normal vehicle, and the vehicle has abnormal nitrogen oxide emissions, and a vehicle tampering prompt is output.

[0178] When the area of ​​the dark-colored image block in the recognition range is not larger than the area of ​​the reference image block, it indicates that the vehicle is a normal vehicle, and a vehicle normal prompt is output.

[0179] Reference Figure 5 ,The analysis method for judging the vehicle tampering risk by positioning location information includes the following steps:

[0180] Step S600: Determine the vehicle's location area based on the vehicle's location information.

[0181] The positioning area refers to the area where the vehicle is currently located. The area where the vehicle is located can be directly determined based on the vehicle positioning information.

[0182] Step S601: According to the location area of ​​the vehicle, the distribution of CVN-changed vehicles in the area is obtained by querying from a preset CVN database.

[0183] The CVN database is a database storing vehicles whose CVN information has been changed in various regions, which will not be described in detail here. According to the region where the vehicle is currently located, the distribution of all vehicles whose CVN information has been changed in the region can be determined from the CVN database.

[0184] Step S602: Determine the cluster vehicle range according to the CVN change vehicle distribution.

[0185] The cluster vehicle range refers to the area range of all vehicles in the area whose vehicle CVN information has been changed and which show a clustered phenomenon on the map. In this embodiment, the cluster vehicle range can be a certain enterprise company, under which there are many vehicles whose vehicle CVN information has been changed, and many of them have a history of tampering. If the vehicle is a vehicle in the cluster vehicle range, there is a high risk probability that it is a tampered vehicle.

[0186] The distribution of CVN-changed vehicles is analyzed on the map, and the range where the cluster-distributed vehicles are located is determined as the cluster vehicle range.

[0187] Step S603: When the vehicle positioning information falls into the range of cluster vehicles, risk points are accumulated, and the vehicle is set as a suspected vehicle or a key inspection vehicle according to the vehicle attribution identification method.

[0188] If the vehicle positioning information shows that the vehicle is within the range of clustered vehicles, there is a high probability that the vehicle is a tampered vehicle. At this time, risk points are accumulated. The higher the risk points, the greater the probability that the vehicle is a tampered vehicle.

[0189] When the vehicle positioning information falls into the range of clustered vehicles, the vehicle may just be passing through the area, so the vehicle needs to be identified through the vehicle attribution identification method. If the vehicle belongs to the range of clustered vehicles, the vehicle will be set as a key inspection vehicle, and the staff will need to conduct a key inspection of the vehicle. If the vehicle does not belong to the range of clustered vehicles, the vehicle is just suspected of tampering. At this time, the vehicle is set as a suspected vehicle and judged by other indicators later.

[0190] The vehicle ownership identification method will not be described in detail here, but will be introduced in detail in the subsequent solution.

[0191] Reference Figure 6 , the vehicle ownership identification method includes the following steps:

[0192] Step S700: Retrieving the historical positioning trajectory of the vehicle and the corresponding positioning point time from a preset historical trajectory database according to the vehicle CVN information.

[0193] The historical trajectory database is a database of all the positioning point trajectories of the vehicle passing through the area recorded by the system, from which the positioning point of the vehicle in each area and the time when it appeared at the positioning point can be obtained, which will not be described in detail here.

[0194] The vehicle is located using the vehicle CVN information, and then the historical positioning trajectory of the vehicle and the positioning point time at the historical positioning trajectory are retrieved from the historical trajectory database through the OBA automotive electronic system.

[0195] Step S701: Determine the suspected positioning points and the number of suspected positioning points that fall within the cluster vehicle range according to the historical positioning trajectory and the cluster vehicle range.

[0196] The suspected positioning point refers to the positioning point in the historical positioning trajectory of the vehicle that is within the range of the cluster vehicle. The number of suspected positioning points is the number of positioning points within the range of the cluster vehicle.

[0197] The historical positioning trajectory is overlapped with the cluster vehicle range, and the overlapping part is the positioning point that falls within the cluster vehicle range, and then the number of positioning points is counted.

[0198] Step S702: Calculate the ratio of the number of suspected positioning points to the historical positioning trajectory, and define the ratio as the suspected probability.

[0199] The suspected probability refers to the probability that the vehicle is within the vehicle cluster range. By calculating the ratio of the number of suspected positioning points to the historical positioning trajectory, the larger the ratio, the more time the vehicle has been within the vehicle cluster range. The vehicle is likely to be within the vehicle cluster range, indicating that the probability that the vehicle is within the vehicle cluster range is greater.

[0200] Step S7021: When the suspected probability is not greater than the preset reference probability, it is a passing vehicle and the vehicle is set as a suspected vehicle.

[0201] The baseline probability is a reference value set by the technicians to measure the probability of whether the vehicle is within the range of cluster vehicles, which will not be elaborated here.

[0202] If the suspected probability is not greater than the baseline probability, it means that the vehicle only appears in the cluster vehicle range a small number of times. The vehicle is likely to be just a vehicle passing through the cluster vehicle range. The vehicle is only marked as a suspected vehicle, which may be suspected of tampering.

[0203] Step S7022: When the suspected probability is greater than the preset reference probability, the discrete degree of the positioning point time corresponding to the suspected positioning point is calculated.

[0204] If the suspected probability is greater than the baseline probability, it means that the vehicle appears more often within the vehicle cluster. There are two possibilities. The first possibility is that the vehicle just passes by frequently, resulting in a large number of positioning points falling within the vehicle cluster, but the vehicle is not within the vehicle cluster. The second possibility is that the vehicle is within the vehicle cluster.

[0205] The degree of discreteness of the positioning point time refers to whether all the times that the vehicle appears within the range of the cluster vehicle are within a relatively concentrated time range.

[0206] The possibility that the vehicle is within the range of the cluster vehicles is determined by the discrete degree of the positioning point time corresponding to the suspected positioning point.

[0207] Step S70221: Based on the large degree of discreteness, it is a passing vehicle and the vehicle is set as a suspected vehicle.

[0208] If the degree of discreteness is large, it means that the time when the vehicle appears within the range of the cluster vehicle is uncertain, and the vehicle is likely to be a passing vehicle, so the vehicle is set as a suspected vehicle.

[0209] Step S70222: Based on the small degree of discreteness, it is a local vehicle, and the vehicle is set as a key vehicle for inspection.

[0210] If the degree of discreteness is small, it means that the time when the vehicle appears within the range of the cluster vehicle is relatively fixed. The vehicle may be a corporate vehicle within the range of the cluster vehicle, which has relatively regular working hours. Therefore, the time when the vehicle appears within the range of the cluster vehicle is regular and will be concentrated in a time range. Based on this, the vehicle is defined as a local vehicle and set as a key inspection vehicle. There is a high probability that there is a tampering problem.

[0211] Based on the same inventive concept, an embodiment of the present invention provides a vehicle tampering behavior recognition system, comprising:

[0212] The acquisition module is used to obtain vehicle CVN information, vehicle emission index information, vehicle operation auxiliary information, fuel consumption, urea liquid level change, SCR upstream and downstream emission concentration difference, SCR inlet temperature median of the suspected vehicle when running, urea injection trigger information, operating speed, operating torque, and nitrogen oxide emission concentration;

[0213] A memory, used for storing a program of a method for identifying tampering behavior of a heavy diesel vehicle;

[0214] The program in the processor and the memory can be loaded and executed by the processor to implement the tampering behavior identification method of heavy-duty diesel vehicles.

[0215] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0216] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed by a method for identifying tampering behavior of a heavy-duty diesel vehicle.

[0217] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0218] Based on the same inventive concept, an embodiment of the present invention provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute a method for identifying tampering behavior of heavy-duty diesel vehicles.

[0219] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

Claims

1. A method for identifying tampering behavior of heavy diesel vehicles, characterized in that: include: Get vehicle CVN information; When the vehicle CVN information is inconsistent with the preset standard CVN information, accumulating risk points and obtaining vehicle emission index information, wherein the vehicle emission index information includes multiple index items; Compare the vehicle emission index information with the preset initial benchmark index information to determine the number of distinguishing index items, and accumulate risk points according to the number of distinguishing index items; If the risk score is greater than the preset tampering risk value, it is defined as a suspected vehicle, and the vehicle CVN information of the suspected vehicle is pushed out; Determine the vehicle location information of the suspected vehicle based on the vehicle CVN information; Conduct real-vehicle monitoring and detection on suspected vehicles based on vehicle CVN information and vehicle positioning information, and obtain vehicle operation auxiliary information; When the vehicle operation auxiliary information is consistent with the preset cheating type information, the judgment result is output.

2. The method for identifying tampering behavior of heavy-duty diesel vehicles according to claim 1 is characterized in that: The vehicle operation auxiliary information acquisition method comprises: Obtain the fuel consumption, urea level change, and SCR upstream and downstream emission concentration difference of the suspected vehicle when running the preset detection trip; Match the corresponding urea consumption according to the fuel consumption; If the change in urea liquid level is less than the urea consumption, it is defined as a sensor abnormality. The sensor is detected according to the sensor abnormality detection method, and a sensor abnormality prompt is output; Based on the fact that the change in urea liquid level is not less than the urea consumption, the output of the vehicle normal prompt or the acquisition of urea content information in the urea solution is determined according to the comparison relationship between the upstream and downstream emission concentration difference of the SCR and the preset reference difference range; When the urea content information is lower than a preset reference urea content, a vehicle tampering prompt is output.

3. The method for identifying tampering behavior of heavy-duty diesel vehicles according to claim 2 is characterized in that: Sensor anomaly detection methods include: Obtain the median SCR inlet temperature when the suspected vehicle is running; When the median of the SCR inlet temperature is greater than the preset urea injection start point temperature, the urea injection start trigger information is obtained; Determine whether to output a vehicle normal prompt or a vehicle tampering prompt according to a comparison between the urea injection trigger information and the preset standard injection information; Based on the median of the SCR inlet temperature being no greater than the urea starting injection point temperature, the sensor image information is obtained at the installation position of the sensor; Determine a detection gap between the sensor and a preset detected object from a preset reference installation database according to the sensor image information; According to the comparison between the detection gap and the preset reference gap, it is determined whether to output a vehicle normal prompt or a vehicle tampering prompt.

4. The method for identifying tampering behavior of heavy-duty diesel vehicles according to claim 3 is characterized in that: Methods for determining whether a sensor has been tampered with include: Retrieve the historical data of the median temperature of the SCR inlet for a preset time period from the preset historical database; Establish a temperature and time curve based on the historical data of the median SCR inlet temperature and the time period; Determine the attenuation angle based on the temperature and time curve; Since the attenuation angle is not 0, it is defined as natural looseness, and the vehicle is output as normal; Based on the decay angle being 0, the starting temperature value is determined by establishing a temperature and time curve; When the starting temperature value is not greater than the urea starting injection point temperature, it is defined as human tampering and a vehicle tampering prompt is output.

5. The method for identifying tampering behavior of heavy-duty diesel vehicles according to claim 1 is characterized in that: The vehicle operation auxiliary information acquisition method further includes: Obtain the running speed, running torque and nitrogen oxide emission concentration of the vehicle during operation; Generate a concentration model image according to the operating speed, the operating torque and the nitrogen oxide emission concentration; In the concentration model image, the nitrogen oxide emission concentration is set from light to dark color output from low to high; Determining an identification range area according to a preset speed range and a preset torque range; Determine the area of ​​the dark block within the preset recognition range; Whether to output a normal vehicle prompt or a vehicle tampering prompt is determined based on a comparison between the dark-colored image block area and a preset reference image block area.

6. The method for identifying tampering behavior of heavy-duty diesel vehicles according to claim 1 is characterized in that: Also includes: Determine the location area of ​​the vehicle according to the vehicle location information; According to the location area of ​​the vehicle, the distribution of CVN-changed vehicles in the area is obtained by querying from the preset CVN database; Determine the range of cluster vehicles based on the distribution of CVN-changed vehicles; When the vehicle positioning information falls within the range of cluster vehicles, risk points are accumulated, and the vehicle is set as a suspected vehicle or a key inspection vehicle based on the vehicle attribution identification method.

7. The method for identifying tampering behavior of heavy-duty diesel vehicles according to claim 6 is characterized in that: Vehicle ownership identification methods include: According to the vehicle CVN information, the historical positioning track of the vehicle and the corresponding positioning point time are retrieved from the preset historical track database; Determine the suspected positioning points and the number of suspected positioning points that fall within the cluster vehicle range according to the historical positioning trajectory and the cluster vehicle range; Calculate the ratio of the number of suspected positioning points to the historical positioning trajectory, and define the ratio as the suspected probability; When the suspected probability is not greater than the preset reference probability, it is a passing vehicle and the vehicle is set as a suspected vehicle; When the suspected probability is greater than the preset reference probability, the discrete degree of the positioning point time corresponding to the suspected positioning point is calculated; Based on the large degree of dispersion, it is a passing vehicle and is set as a suspected vehicle; Since the discreteness is small, it is a local vehicle and is set as a key vehicle for inspection.

8. A vehicle tampering behavior recognition system, characterized in that: include: The acquisition module is used to obtain vehicle CVN information, vehicle emission index information, vehicle operation auxiliary information, fuel consumption, urea liquid level change, SCR upstream and downstream emission concentration difference, SCR inlet temperature median of the suspected vehicle when running, urea injection trigger information, operating speed, operating torque, and nitrogen oxide emission concentration; A memory for storing a program of a method for identifying tampering behavior of a heavy-duty diesel vehicle according to any one of claims 1 to 7; The program in the processor memory can be loaded and executed by the processor to implement the heavy-duty diesel vehicle tampering behavior identification method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method for identifying tampering behavior of a heavy-duty diesel vehicle as claimed in any one of claims 1 to 7.

10. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes the method for identifying tampering behavior of heavy-duty diesel vehicles as described in any one of claims 1 to 7.

Images