Vehicle overload and over-limit automatic detection device

Abstract

The invention belongs to the technical field of vehicle detection, and particularly relates to a vehicle overload and over-limit automatic detection device, which comprises an axle load detection seat, the axle load detection seat is arranged on the ground, a plurality of traffic trusses are arranged above the axle load detection seat, the plurality of traffic trusses are used for limiting a to-be-detected vehicle, and the plurality of traffic trusses are arranged above the axle load detection seat. A flashing light and a license plate recognition instrument are arranged on the side wall of each traffic truss, a plurality of first axle sensors are installed on the upper surface of the axle load detection seat, and second axle sensors are installed at the positions, corresponding to the first axle sensors, of the upper surface of the axle load detection seat; a weighing sensor is arranged between the first axle sensor and the second axle sensor, the first axle sensor and the second axle sensor can detect the number of axles and the number of axles of a to-be-detected vehicle, and the axle load detection seat further comprises a vehicle overload and overrun dynamic weighing system.

Description

Technical Field

[0001] The invention belongs to the technical field of vehicle detection, in particular to an automatic detection device for vehicle overload and overlimit. Background Art

[0002] Overloaded vehicles are not only prone to traffic accidents, causing harm to people's lives and property, but also easily damaging roads, bridges and other transportation infrastructure. Overloaded transportation seriously damages roads and bridges, shortening the service life of cement pavements by about 40% and asphalt pavements by about 20% to 30%, causing huge economic losses to the country.

[0003] The off-site enforcement system for highway overload and limit violations uses non-stop dynamic weighing to obtain information on overload and limit freight vehicles, implements prior notification and reminders, and takes penalty and enforcement measures afterwards. It transforms the process of overload and limit penalty and enforcement from on-site to an information-based office platform, avoiding the process of on-site weighing, law enforcement and punishment at fixed overload and limit inspection stations, greatly improving management efficiency and saving a lot of manpower, material resources and funds required for the construction and operation of fixed highway overload and limit inspection stations.

[0004] However, at present, some large vehicles have some abnormal behaviors when passing by this measuring equipment, such as repeated reversing and stopping and starting. Such abnormal behaviors will interfere with the measurement and affect the measurement accuracy.

[0005] To this end, the present invention provides a vehicle overload and over-limit automatic detection device. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The technical solution adopted by the present invention to solve its technical problems is: the vehicle overload and overlimit automatic detection device described in the present invention includes an axle weight detection seat, the axle weight detection seat is arranged on the ground, a plurality of traffic frames are installed above the axle weight detection seat, the plurality of traffic frames are used to limit the vehicles to be detected, and the side walls of each traffic frame are provided with flashing lights and license plate recognition devices, a plurality of first wheel axle sensors are installed on the upper surface of the axle weight detection seat, a second wheel axle sensor is installed on the upper surface of the axle weight detection seat and at a position corresponding to the first wheel axle sensor, a weighing sensor is arranged between the first wheel axle sensor and the second wheel axle sensor, and the first wheel axle sensor and the second wheel axle sensor can detect the number of wheel axles and the number of shafts of the vehicle to be detected; the axle weight detection seat also includes a vehicle overload and overlimit dynamic weighing system;

[0008] It should be noted that the first wheel axle sensor and the second wheel axle sensor are connected to the external first ground sensing coil and the second ground sensing coil respectively through a power line and a vehicle overload and overlimit dynamic weighing system.

[0009] Preferably, the vehicle overload and over-limit dynamic weighing system includes a dynamic weighing processing module, a vehicle driving data acquisition module, a driving data analysis module and a feedback module;

[0010] Dynamic weighing processing module: The dynamic weighing processing module is used to weigh the vehicle to be inspected;

[0011] A vehicle driving data acquisition module, the vehicle driving data acquisition module is used to collect driving data of the vehicle to be detected when passing through the axle weight detection seat, the driving data includes data of the vehicle to be detected passing through the first axle sensor and data of the vehicle to be detected passing through the second axle sensor;

[0012] Driving data analysis module: the driving data analysis module is used to analyze the driving data of the vehicle to be tested when passing through the axle weight detection seat;

[0013] Feedback module: The feedback module is used to provide feedback on the analysis results of the driving data analysis module.

[0014] Preferably, the driving data analysis module performs the following driving data analysis process when the vehicle to be tested passes through the axle weight detection seat:

[0015] The vehicle travel data collection module collects data of the vehicle to be detected passing through the first wheel axle sensor and data of the vehicle to be detected passing through the second wheel axle sensor;

[0016] The data of the vehicle to be detected passing through the first axle sensor includes the time point when the first ground sensor coil receives the signal for the first time, that is, the time point when the first axle sensor receives the weighing signal for the first time, that is, when the first ground sensor coil changes from a low level to a high level signal, and the corresponding time point is marked as t1; and also includes the time point when the first ground sensor coil changes from a high level to a low level signal, and the corresponding time point is marked as t2;

[0017] Calculate the first axle deviation value g1 of the vehicle to be tested, and compare and analyze the first axle deviation value g1 of the vehicle to be tested with the first axle time deviation standard value f:

[0018] If the ratio between the first wheel axle deviation value g1 of the vehicle to be detected and the first wheel axle time deviation standard value f is less than 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior;

[0019] If the ratio between the first axle deviation value g1 of the vehicle to be detected and the first axle time deviation standard value f is greater than or equal to 1, the feedback module outputs a repeated detection signal corresponding to the vehicle to be detected.

[0020] Preferably, the specific calculation method of the first wheel axle deviation value g1 of the detection vehicle is:

[0021]

[0022] The first axle time deviation standard value f is the minimum time index of the vehicle passing the first axle sensor (101);

[0023] Preferably, the specific method for establishing the first axle time deviation standard value f is as follows:

[0024] Based on the axles of different vehicles, all the axles of the vehicles are sorted, where the front axle is marked as the first axle and the rear axle is marked as the last axle;

[0025] Step 1: Establish a historical database, which includes the driving data of vehicles with no abnormal behavior passing through the axle load detection seat in the past, and the driving data includes: the data of the first wheel axle of the vehicle with no abnormal behavior passing through the first wheel axle sensor for the first time, that is, the time point T1 when the first ground sensing coil first receives the signal;

[0026] and the data of the last wheel axle of the vehicle without abnormal behavior passing through the first wheel axle sensor for the first time, that is, the time point R1 when the first ground sensing coil changes from a high level to a low level;

[0027] Step 2: Calculate the difference between the time point T1 when the first ground sensing coil receives the signal for the first time and the time point R1 when the first ground sensing coil changes from a high level to a low level, and mark the difference as the first wheel axle evaluation index;

[0028] Step 3: Based on vehicles with different wheelbases, analyze the vehicles, obtain the first axle evaluation index of vehicles with different wheelbases, and establish the first axle evaluation index set of all vehicles with different wheelbases [M1, M2, …, M n ]; where M1 is the first axle evaluation index of a vehicle with wheelbase one, M2 is the first axle evaluation index of a vehicle with wheelbase two, and so on;

[0029] Step 4: Calculate the mean K1 of all first axle evaluation index sets, where the first axle time deviation value is Among them, M i1 is the maximum value in the first axle evaluation index set, M i2 is the minimum value in the first wheel axle evaluation index set, M i1 -M i2 is the correction factor,

[0030] The smaller the value of the first wheel axle time deviation value f is, the greater the abnormal behavior of the vehicle is.

[0031] Preferably, when the feedback module outputs a repeated detection signal corresponding to the vehicle to be detected:

[0032] The data of the vehicle to be detected passing through the second wheel axle sensor includes the time point when the second ground sensor coil first receives the signal, that is, the time point when the second wheel axle sensor first receives the weighing signal, that is, when the second ground sensor coil first changes to a high level signal, and the corresponding time point is marked as q1; and also includes the time point when the first ground sensor coil changes from a high level to a low level signal, and the corresponding time point is marked as b1;

[0033] Calculate the deviation value of the second wheel axle of the vehicle to be tested Compare and analyze the second axle deviation value g2 of the vehicle to be tested with the second axle time deviation standard value h:

[0034] If the ratio between the second wheel axle deviation value g2 of the vehicle to be detected and the second wheel axle time deviation standard value h is less than 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior;

[0035] If the ratio between the second wheel axle deviation value g2 of the vehicle to be detected and the second wheel axle time deviation standard value h is greater than or equal to 1, the feedback module outputs a secondary repeated detection signal corresponding to the vehicle to be detected;

[0036] Preferably, the specific method for establishing the second axle time deviation standard value h is as follows:

[0037] Based on the first axle time deviation value f in the historical database and the first axle evaluation index set of all vehicles with different wheelbases, calculate the second axle time deviation standard value h;

[0038] h=[ff*ω1]; ω1 is the proportional factor coefficient of the time deviation value of the first wheel shaft, and the proportional factor coefficient is used to correct the deviation of various parameters in the calculation process of the formula, so as to make the calculation result more accurate;

[0039] The smaller the standard value h of the second wheel axle time deviation is, the greater the abnormal behavior of the vehicle is;

[0040] Specifically, in a normal vehicle, the wheelbase of the front and rear axles of the vehicle is generally the same, that is, the first axle time deviation value f is generally equal to the second axle time deviation standard value h. However, the distance between the rear axle and the front axle of some vehicles is too small, and the signal time received by the second axle sensor is short, that is, the time from a high level to a low level is short. At this time, a proportional factor coefficient is needed to correct the deviation of the second axle time deviation standard value to improve the detection effect of the vehicle. ω1 is a positive number less than 1. For example, the calculated first axle time deviation value f is 1.3, and ω1 can be taken as 0.354, then the second axle time deviation standard value h = (1.3-1.3*0.354).

[0041] Preferably, when the vehicle feedback module outputs a secondary repeated detection signal corresponding to the vehicle to be detected, the vehicle overload and overlimit dynamic weighing system is also used to obtain speed data of the vehicle to be detected, and the speed data of the vehicle to be detected includes:

[0042] The time point when the first wheel axle sensor first receives the weighing signal, that is, the speed V1 when the first ground sensing coil changes from a low level to a high level signal,

[0043] The time point when the second wheel axle sensor first receives the upper scale signal and the speed V2 when it receives the lower scale signal, that is, when the first ground sensing coil changes from a low level to a high level signal and then changes from a low level to a high level signal; calculate the acceleration abnormality index α1 of the vehicle to be detected,

[0044] The acceleration abnormality index α1 of the vehicle to be detected is compared and analyzed with the acceleration abnormality index threshold of the vehicle to be detected:

[0045] If the ratio of the acceleration abnormality index α1 of the vehicle to be detected to the acceleration abnormality index threshold of the vehicle to be detected is greater than or equal to 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior;

[0046] If the ratio of the acceleration abnormality index α1 of the vehicle to be detected to the acceleration abnormality index threshold of the vehicle to be detected is less than 1, the feedback module outputs a normal weighing signal for the vehicle to be detected.

[0047] Preferably, the vehicle overload and overlimit dynamic weighing system is also used to obtain the weight of the vehicle to be detected. If the first ground sensor coil and the second ground sensor coil both receive signals, or the first ground sensor coil receives a signal but the weight of the vehicle to be detected does not change, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior.

[0048] Preferably, when the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior, the vehicle overload and overlimit dynamic weighing system further includes a data correction unit, which is used to correct the abnormal data indicating that the vehicle to be detected has abnormal behavior, specifically:

[0049] The weighing data of the vehicle to be detected is obtained through the dynamic weighing processing module, wherein the weighing data includes vehicle weight data, vehicle speed data, vehicle axle number data, vehicle tire number data, and vehicle passing time data;

[0050] Sum all the collected weighing data, then divide it by the number of data to get the average value P1, then square the difference between each data point and the average value, sum it up, divide it by the number of data minus one, and then take the square root to get the standard deviation P2;

[0051] Set a standard threshold value, which is the mean value plus or minus three times the standard deviation, that is, the standard threshold value is between (P1-3P2) and (P1+3P2), then compare each weighing data with the threshold value, mark the data points that are not within this threshold range as outliers, and remove the outliers (these outliers are caused by abnormal vehicle behavior), and mark the remaining data as normal values;

[0052] The corrected normal value is then smoothed, such as by using a sliding average filter method, and the corrected and smoothed data are integrated to obtain the weight of the vehicle.

[0053] The beneficial effects of the present invention are as follows:

[0054] The automatic detection device for overload and overlimit of vehicles described in the present invention obtains data of the first axle and the second axle of the vehicle to be detected through the dynamic weighing system for overload and overlimit of vehicles, and analyzes whether the vehicle has abnormal behavior based on the data of the first axle and the second axle. The present invention also improves the detection accuracy of the dynamic weighing system for overload and overlimit by analyzing vehicles with different wheelbases, which is conducive to screening out vehicles with abnormal behavior and re-weighing the vehicles with abnormal behavior, thereby solving the problems of abnormal driving such as repeated reversing, stop-and-go intermittent driving, and deliberate evasion of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The present invention will be further described below in conjunction with the accompanying drawings.

[0056] Figure 1 is a stereogram of the present invention;

[0057] Figure 2 It is a system flow chart of the present invention.

[0058] In the figure: 1. axle weight detection seat; 2. traffic frame; 101. first wheel axle sensor; 102. second wheel axle sensor; 3. weighing sensor. DETAILED DESCRIPTION

[0059] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0060] Embodiment 1

[0061] like Figure 1As shown, an automatic detection device for vehicle overload and overlimit described in an embodiment of the present invention includes an axle weight detection seat 1, which is arranged on the ground, and a plurality of traffic frames 2 are installed above the axle weight detection seat 1, and the plurality of traffic frames 2 are used to limit the vehicles to be detected, and the side walls of each of the traffic frames 2 are provided with flashing lights and license plate recognition devices, and a plurality of first wheel axle sensors 101 are installed on the upper surface of the axle weight detection seat 1, and a second wheel axle sensor 102 is installed on the upper surface of the axle weight detection seat 1 and at a position corresponding to the first wheel axle sensor 101, and a weighing sensor 3 is arranged between the first wheel axle sensor 101 and the second wheel axle sensor 102, and the first wheel axle sensor 101 and the second wheel axle sensor 102 can detect the number of axles and the number of shafts of the vehicle to be detected, and the axle weight detection seat 1 also includes a vehicle overload and overlimit dynamic weighing system;

[0062] It should be noted that the first wheel axle sensor 101 and the second wheel axle sensor 102 are connected to the external first ground sensing coil and the second ground sensing coil through a power line and a vehicle overload and overlimit dynamic weighing system respectively;

[0063] During operation, when it is necessary to weigh the vehicle, the vehicle to be detected is passed through the traffic frame 2 in sequence, so that the vehicle to be detected passes through the first axle sensor 101, the weighing sensor 3 and the second axle sensor 102 in sequence. When the vehicle is driving normally, the first ground sensing coil connected to the first axle sensor 101 has a signal, it is considered that there is a vehicle on the scale, and the first ground sensing coil maintains a high level, and the weighing sensor 3 detects the weight at the same time. When the second ground sensing coil of the second axle sensor 102 has a signal, and the second ground sensing coil is at a high level, as the vehicle continues to drive, the first ground sensing coil changes from a high level to a low level, and the second ground sensing coil changes from a high level to a low level, it is considered that the vehicle has passed normally, and then the vehicle model and weight are judged at the end;

[0064] If the first ground sensing coil maintains a high level and then changes to a low level, the second ground sensing coil does not receive a signal, that is, the first wheel axle sensor 101 only receives an upper scale signal, and at the same time receives a lower scale signal, it indicates that the vehicle has abnormal behavior, that is, repeatedly reversing;

[0065] If the first ground sensing coil maintains a high level and then changes to a low level, the second ground sensing coil changes from a high level to a low level, and the first ground sensing coil changes from a low level to a high level, that is, the first axle sensor 101 changes from an upper scale signal to a lower scale signal, the second axle sensor 102 changes from an upper scale signal to a lower scale signal, and the first axle sensor 101 changes from a lower scale signal to an upper scale signal, then this also indicates that the vehicle has abnormal behavior, that is, repeated reversing;

[0066] If both the first ground sensing coil and the second ground sensing coil have signals, but the weight of the weighing sensor does not change, it indicates that the vehicle is stationary, which indicates that the vehicle is also in abnormal behavior, that is, stop-and-go; the present invention solves some abnormal passing behaviors, such as repeated reversing, stop-and-go intermittent driving and other related abnormal driving, and behaviors of deliberately evading detection.

[0067] like Figure 2 As shown, the vehicle overload and over-limit dynamic weighing system includes a dynamic weighing processing module, a vehicle driving data acquisition module, a driving data analysis module and a feedback module;

[0068] Dynamic weighing processing module: The dynamic weighing processing module is used to weigh the vehicle to be inspected;

[0069] A vehicle driving data acquisition module, the vehicle driving data acquisition module is used to collect driving data of the vehicle to be detected when passing through the axle weight detection seat 1, the driving data includes data of the vehicle to be detected passing through the first axle sensor 101 and data of the vehicle to be detected passing through the second axle sensor 102;

[0070] Driving data analysis module: the driving data analysis module is used to analyze the driving data of the vehicle to be detected when passing through the axle weight detection seat 1;

[0071] Feedback module: The feedback module is used to provide feedback on the analysis results of the driving data analysis module;

[0072] Specifically, when the vehicle to be detected drives above the axle weight detection seat 1, the driving data of the vehicle to be detected when passing through the axle weight detection seat 1 is obtained through the vehicle driving data acquisition module, and the driving data when passing through the axle weight detection seat 1 is transmitted to the driving data analysis module. The driving data analysis module is used to analyze whether the vehicle to be detected has abnormal behavior, and the feedback module outputs a feedback processing signal for the vehicle to be detected with abnormal behavior; finally, the dynamic weighing processing module is used to weigh the vehicle to be detected that does not have abnormal behavior.

[0073] The driving data analysis process of the driving data analysis module when the vehicle to be detected passes through the axle weight detection seat 1 is as follows:

[0074] The vehicle travel data collection module collects data of the vehicle to be detected passing through the first wheel axle sensor 101 and data of the vehicle to be detected passing through the second wheel axle sensor 102;

[0075] The data of the vehicle to be detected passing through the first axle sensor 101 includes the time point when the first ground sensor coil receives the signal for the first time, that is, the time point when the first axle sensor 101 receives the weighing signal for the first time, that is, when the first ground sensor coil changes from a low level to a high level signal, and the corresponding time point is marked as t1; and also includes the time point when the first ground sensor coil changes from a high level to a low level signal, and the corresponding time point is marked as t2;

[0076] Calculate the first axle deviation value g1 of the vehicle to be tested, and compare and analyze the first axle deviation value g1 of the vehicle to be tested with the first axle time deviation standard value f:

[0077] If the ratio between the first wheel axle deviation value g1 of the vehicle to be detected and the first wheel axle time deviation standard value f is less than 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior;

[0078] If the ratio between the first wheel axle deviation value g1 of the vehicle to be detected and the first wheel axle time deviation standard value f is greater than or equal to 1, the feedback module outputs a repeated detection signal corresponding to the vehicle to be detected;

[0079] When the vehicle to be detected passes through the first axle, it is difficult to determine whether the rear wheel or the front wheel of the vehicle continues to pass through the first axle, so the difference between the time points of passing through the first axle twice is calculated to obtain the deviation value g1 of the vehicle to be detected. If the ratio of the deviation value g1 of the vehicle to be detected to the time deviation value f of the first axle is less than 1, that is, the time between the vehicle passing through the first axle is lower than the minimum time of the vehicle passing through the first axle under standard conditions, it indicates that the vehicle has an abnormal behavior signal at this time, that is, the vehicle may have repeated weighing behavior;

[0080] The specific calculation method of the first wheel axle deviation value g1 of the detection vehicle is:

[0081]

[0082] The first axle time deviation standard value f is the minimum time index of the vehicle passing the first axle sensor 101;

[0083] Specifically, when the vehicle to be detected passes through the first axle, it is difficult to determine whether the rear wheel or the front wheel of the vehicle continues to pass through the first axle, so the difference between the time points of passing the first axle twice is calculated to obtain the deviation value g1 of the vehicle to be detected. If the ratio of the deviation value g1 of the vehicle to be detected to the time deviation value f of the first axle is less than 1, that is, the time between the vehicle passing through the first axle is lower than the minimum time for the vehicle to pass through the first axle under standard conditions, it indicates that there is an abnormal behavior signal of the vehicle at this time, that is, the vehicle may have repeated weighing behavior.

[0084] The specific method for establishing the first axle time deviation standard value f is as follows:

[0085] Based on the axles of different vehicles, all the axles of the vehicles are sorted, where the front axle is marked as the first axle and the rear axle is marked as the last axle;

[0086] Step 1: Establish a historical database, which includes the driving data of vehicles with no abnormal behavior passing through the axle load detection seat 1 in the past, and the driving data includes: data of the first wheel axle of the vehicle with no abnormal behavior passing through the first wheel axle sensor 101 for the first time, that is, the time point T1 when the first ground sensing coil first receives the signal;

[0087] and the data of the last wheel axle of the vehicle without abnormal behavior passing through the first wheel axle sensor 101 for the first time, that is, the time point R1 when the first ground sensing coil changes from a high level to a low level;

[0088] Step 2: Calculate the difference between the time point T1 when the first ground sensing coil receives the signal for the first time and the time point R1 when the first ground sensing coil changes from a high level to a low level, and mark the difference as the first wheel axle evaluation index;

[0089] Step 3: Based on vehicles with different wheelbases, analyze the vehicles, obtain the first axle evaluation index of vehicles with different wheelbases, and establish the first axle evaluation index set of all vehicles with different wheelbases [M1, M2, …, M n ]; where M1 is the first axle evaluation index of a vehicle with wheelbase one, M2 is the first axle evaluation index of a vehicle with wheelbase two, and so on;

[0090] Step 4: Calculate the mean K1 of all first axle evaluation index sets, where the first axle time deviation value is Among them, M i1 is the maximum value in the first axle evaluation index set, M i2 is the minimum value in the first wheel axle evaluation index set, M i1 -M i2 is the correction factor;

[0091] The smaller the value of the first wheel axle time deviation value f is, the greater the abnormal behavior of the vehicle is;

[0092] Specifically, in an embodiment of the present invention, due to the different wheelbases of different vehicles, when the vehicle is detected normally, that is, when there is no abnormal behavior detection, the first axle of the vehicle is generally in contact with the first axle, and then the last axle contacts the first axle again. The first axle evaluation index of different wheelbases is obtained by calculation, and the mean K1 of all first axle evaluation index sets is calculated based on the first axle evaluation index of different wheelbases, and the correction coefficient is obtained by subtracting the maximum value in the first axle evaluation index set and the minimum value in the first axle evaluation index set. The square root of the difference between the correction coefficient and the mean K1 is taken to obtain the first axle time deviation value f. Different types of vehicles have different wheelbases. For example, a small car has a shorter wheelbase, while a large truck or bus has a longer wheelbase. The difference in wheelbase will cause different time differences in the vehicle wheels passing through the two sensors.

[0093] Embodiment 2

[0094] When the feedback module outputs a repeated detection signal corresponding to the vehicle to be detected:

[0095] The data of the vehicle to be detected passing through the second axle sensor 102 includes the time point when the second ground sensor coil receives the signal for the first time, that is, the time point when the second axle sensor 102 receives the weighing signal for the first time, that is, when the second ground sensor coil changes to a high level signal for the first time, and the corresponding time point is marked as q1; and also includes the time point when the first ground sensor coil changes from a high level to a low level signal, and the corresponding time point is marked as b1;

[0096] Calculate the deviation value of the second wheel axle of the vehicle to be tested Compare and analyze the second axle deviation value g2 of the vehicle to be tested with the second axle time deviation standard value h:

[0097] If the ratio between the second wheel axle deviation value g2 of the vehicle to be detected and the second wheel axle time deviation standard value h is less than 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior;

[0098] If the ratio between the second wheel axle deviation value g2 of the vehicle to be detected and the second wheel axle time deviation standard value h is greater than or equal to 1, the feedback module outputs a secondary repeated detection signal corresponding to the vehicle to be detected;

[0099] The specific method for establishing the second axle time deviation standard value h is as follows:

[0100] Based on the first axle time deviation value f in the historical database and the first axle evaluation index set of all vehicles with different wheelbases, calculate the second axle time deviation standard value h;

[0101] h=[ff*ω1]; ω1 is the proportional factor coefficient of the time deviation value of the first wheel shaft, and the proportional factor coefficient is used to correct the deviation of various parameters in the calculation process of the formula, so as to make the calculation result more accurate;

[0102] The smaller the standard value h of the second wheel axle time deviation is, the greater the abnormal behavior of the vehicle is;

[0103] Specifically, in a normal vehicle, the wheelbase of the front and rear axles of the vehicle is generally the same, that is, the first axle time deviation value f is generally equal to the second axle time deviation standard value h. However, the distance between the rear axle and the front axle of some vehicles is too small, and the signal time received by the second axle sensor is short, that is, the time from a high level to a low level is short. At this time, a proportional factor coefficient is needed to correct the deviation of the second axle time deviation standard value to improve the detection effect of the vehicle. ω1 is a positive number less than 1. For example, the calculated first axle time deviation value f is 1.3, and ω1 can be taken as 0.354, then the second axle time deviation standard value h = (1.3-1.3*0.354).

[0104] When the vehicle feedback module outputs a secondary repeated detection signal corresponding to the vehicle to be detected, the vehicle overload and overlimit dynamic weighing system is also used to obtain the speed data of the vehicle to be detected, and the speed data of the vehicle to be detected includes:

[0105] The time point when the first wheel axle sensor 101 first receives the weighing signal, that is, the speed V1 when the first ground sensing coil changes from a low level to a high level signal,

[0106] The time point when the second wheel axle sensor 102 first receives the upper scale signal and the speed V2 when it receives the lower scale signal, that is, when the first ground sensing coil changes from a low level to a high level signal and then changes from a low level to a high level signal; calculate the acceleration abnormality index α1 of the vehicle to be detected,

[0107] The acceleration abnormality index α1 of the vehicle to be detected is compared and analyzed with the acceleration abnormality index threshold of the vehicle to be detected:

[0108] If the ratio of the acceleration abnormality index α1 of the vehicle to be detected to the acceleration abnormality index threshold of the vehicle to be detected is greater than or equal to 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior;

[0109] If the ratio of the acceleration abnormality index α1 of the vehicle to be detected to the acceleration abnormality index threshold of the vehicle to be detected is less than 1, the feedback module outputs a normal weighing signal for the vehicle to be detected:

[0110] The vehicle overload and overlimit dynamic weighing system is also used to obtain the weight of the vehicle to be detected. If both the first ground sensing coil and the second ground sensing coil receive signals, or the first ground sensing coil receives a signal but the weight of the vehicle to be detected does not change, the feedback module outputs an abnormal behavior signal corresponding to the vehicle to be detected.

[0111] Embodiment 3

[0112] When the feedback module outputs a signal that the vehicle to be detected has abnormal behavior, the vehicle overload and over-limit dynamic weighing system further includes a data correction unit, which is used to correct the abnormal data of the abnormal behavior of the vehicle to be detected, specifically:

[0113] The weighing data of the vehicle to be detected is obtained through the dynamic weighing processing module, wherein the weighing data includes vehicle weight data, vehicle speed data, vehicle axle number data, vehicle tire number data, and vehicle passing time data;

[0114] Sum all the collected weighing data, then divide it by the number of data to get the average value P1, then square the difference between each data point and the average value, sum it up, divide it by the number of data minus one, and then take the square root to get the standard deviation P2;

[0115] Set a standard threshold value, which is the mean value plus or minus three times the standard deviation, that is, the standard threshold value is between (P1-3P2) and (P1+3P2), then compare each weighing data with the threshold value, mark the data points that are not within this threshold range as outliers, and remove the outliers (these outliers are caused by abnormal vehicle behavior), and mark the remaining data as normal values;

[0116] The corrected normal value is then smoothed, such as by using a sliding average filter method, and the corrected and smoothed data is integrated to obtain the weight of the vehicle (the integral calculation may use a numerical integration method, such as trapezoidal integration or Simpson integration, etc.).

[0117] Trapezoidal integration method: Trapezoidal integration method is a simple numerical integration method, which divides the integration interval into several small intervals and uses a trapezoidal approximation to replace the area under the curve in each small interval.

[0118] Simpson integration method: Simpson integration method is a more accurate numerical integration method. It divides the integration interval into several small intervals and uses a quadratic polynomial to approximate the area under the curve in each small interval.

[0119] In summary, the vehicle overload and overlimit dynamic weighing system obtains data on the first axle and the second axle of the vehicle to be detected, and analyzes whether the vehicle has abnormal behavior based on the data of the first axle and the second axle. The present invention also improves the detection accuracy of the overload and overlimit dynamic weighing system by analyzing vehicles with different wheelbases, which is conducive to screening out vehicles with abnormal behavior and re-weighing vehicles with abnormal behavior, thereby solving abnormal driving problems such as repeated reversing, stop-and-go intermittent driving, and deliberate evasion of detection.

[0120] The threshold is set to facilitate comparison. The threshold depends on the amount of sample data and the number of bases set by technicians in this field for each set of sample data. It does not affect the proportional relationship between the parameter and the quantized value.

[0121] The size of the coefficient is to quantify each parameter to obtain a specific value, which is convenient for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding operating coefficient for each set of sample data by technicians in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value;

[0122] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A vehicle overload and overrun automatic detection device, characterized in that: The invention comprises an axle weight detection seat (1), wherein the axle weight detection seat (1) is arranged on the ground, and a plurality of traffic frames (2) are installed above the axle weight detection seat (1), and the plurality of traffic frames (2) are used to limit the position of the vehicle to be detected, and the side wall of each traffic frame (2) is provided with a flashing light and a license plate recognition device, and a plurality of first wheel axle sensors (101) are installed on the upper surface of the axle weight detection seat (1), and a second wheel axle sensor (102) is installed on the upper surface of the axle weight detection seat (1) and at a position corresponding to the first wheel axle sensor (101), and a weighing sensor (3) is arranged between the first wheel axle sensor (101) and the second wheel axle sensor (102), and the first wheel axle sensor (101) and the second wheel axle sensor (102) can detect the number of wheel axles and the number of shafts of the vehicle to be detected, and the axle weight detection seat (1) also comprises a vehicle overload and overlimit dynamic weighing system; The first wheel axle sensor (101) and the second wheel axle sensor (102) are respectively connected to the external first ground sensing coil and the second ground sensing coil via a power line and a vehicle overload and overlimit dynamic weighing system.

2. The automatic vehicle overload and over-limit detection device according to claim 1 is characterized in that: The vehicle overload and over-limit dynamic weighing system includes a dynamic weighing processing module, a vehicle driving data acquisition module, a driving data analysis module and a feedback module; Dynamic weighing processing module: The dynamic weighing processing module is used to weigh the vehicle to be inspected; A vehicle travel data acquisition module, the vehicle travel data acquisition module being used to acquire travel data of a vehicle to be detected when it passes through an axle weight detection seat (1), the travel data comprising data of the vehicle to be detected passing through a first axle sensor (101) and data of the vehicle to be detected passing through a second axle sensor (102); Driving data analysis module: the driving data analysis module is used to analyze the driving data of the vehicle to be detected when passing through the axle weight detection seat (1); Feedback module: The feedback module is used to provide feedback on the analysis results of the driving data analysis module.

3. The automatic vehicle overload and over-limit detection device according to claim 2 is characterized in that: The driving data analysis module performs the following driving data analysis process when the vehicle to be detected passes through the axle weight detection seat (1): The vehicle travel data collection module collects data of the vehicle to be detected passing through the first wheel axle sensor (101) and data of the vehicle to be detected passing through the second wheel axle sensor (102); The data of the vehicle to be detected passing through the first axle sensor (101) includes the time point when the first ground sensing coil receives the signal for the first time, that is, the time point when the first axle sensor (101) receives the weighing signal for the first time, that is, when the first ground sensing coil changes from a low level to a high level signal, and the corresponding time point is marked as t1; and also includes the time point when the first ground sensing coil changes from a high level to a low level signal, and the corresponding time point is marked as t2; Calculate the first axle deviation value g1 of the vehicle to be tested, and compare and analyze the first axle deviation value g1 of the vehicle to be tested with the first axle time deviation standard value f: If the ratio between the first wheel axle deviation value g1 of the vehicle to be detected and the first wheel axle time deviation standard value f is less than 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior; If the ratio between the first axle deviation value g1 of the vehicle to be detected and the first axle time deviation standard value f is greater than or equal to 1, the feedback module outputs a repeated detection signal corresponding to the vehicle to be detected.

4. The automatic vehicle overload and over-limit detection device according to claim 3 is characterized in that: The specific calculation method of the first wheel axle deviation value g1 of the detection vehicle is: The first axle time deviation standard value f is the minimum time index of the vehicle passing the first axle sensor (101).

5. The automatic vehicle overload and over-limit detection device according to claim 3 is characterized in that: The specific method for establishing the first axle time deviation standard value f is as follows: Based on the axles of different vehicles, all the axles of the vehicles are sorted, where the front axle is marked as the first axle and the rear axle is marked as the last axle; Step 1: Establishing a historical database, the historical database including historical driving data of vehicles without abnormal behavior passing through the axle load detection seat (1), the driving data including: data of the first wheel axle of the vehicle without abnormal behavior passing through the first wheel axle sensor (101) for the first time, that is, the time point T1 when the first ground sensing coil first receives a signal; and data of the first time the last wheel axle of the vehicle without abnormal behavior passes through the first wheel axle sensor (101), that is, the time point R1 when the first ground sensing coil changes from a high level to a low level; Step 2: Calculate the difference between the time point T1 when the first ground sensing coil receives the signal for the first time and the time point R1 when the first ground sensing coil changes from a high level to a low level, and mark the difference as the first wheel axle evaluation index; Step 3: Based on vehicles with different wheelbases, analyze the vehicles, obtain the first axle evaluation index of vehicles with different wheelbases, and establish the first axle evaluation index set of all vehicles with different wheelbases [M1, M2, …, M n [; Where M1 is the first axle evaluation index of a vehicle with wheelbase one, M2 is the first axle evaluation index of a vehicle with wheelbase two, and so on; Step 4: Calculate the mean K1 of all first axle evaluation index sets, where the first axle time deviation value is Among them, M i1 is the maximum value in the first axle evaluation index set, M i2 is the minimum value in the first wheel axle evaluation index set, M i1 -M i2 is the correction factor, The smaller the value of the first wheel axle time deviation value f is, the greater the abnormal behavior of the vehicle is.

6. The automatic vehicle overload and over-limit detection device according to claim 5 is characterized in that: When the feedback module outputs a repeated detection signal corresponding to the vehicle to be detected: The data of the vehicle to be detected passing through the second axle sensor (102) includes the time point when the second ground sensing coil first receives a signal, that is, the time point when the second axle sensor (102) first receives a weighing signal, that is, when the second ground sensing coil first changes to a high-level signal, and the corresponding time point is marked as q1; and also includes the time point when the first ground sensing coil changes from a high-level signal to a low-level signal, and the corresponding time point is marked as b1; Calculate the deviation value of the second wheel axle of the vehicle to be tested Compare and analyze the second axle deviation value g2 of the vehicle to be tested with the second axle time deviation standard value h: If the ratio between the second wheel axle deviation value g2 of the vehicle to be detected and the second wheel axle time deviation standard value h is less than 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior; If the ratio between the second axle deviation value g2 of the vehicle to be detected and the second axle time deviation standard value h is greater than or equal to 1, the feedback module outputs a secondary repeated detection signal corresponding to the vehicle to be detected.

7. The automatic vehicle overload and over-limit detection device according to claim 6 is characterized in that: The specific method for establishing the second axle time deviation standard value h is as follows: Based on the first axle time deviation value f in the historical database and the first axle evaluation index set of all vehicles with different wheelbases, calculate the second axle time deviation standard value h; h=[ff*ω1]; ω1 is the proportional factor coefficient of the time deviation value of the first wheel shaft, and the proportional factor coefficient is used to correct the deviation of various parameters in the calculation process of the formula, so as to make the calculation result more accurate; The smaller the second axle time deviation standard value h is, the greater the abnormal behavior of the vehicle is.

8. The automatic vehicle overload and over-limit detection device according to claim 7 is characterized in that: When the vehicle feedback module outputs a secondary repeated detection signal corresponding to the vehicle to be detected, the vehicle overload and overlimit dynamic weighing system is also used to obtain the speed data of the vehicle to be detected, and the speed data of the vehicle to be detected includes: The time point when the first wheel axle sensor (101) first receives the weighing signal, that is, the speed V1 when the first ground sensing coil changes from a low level to a high level signal; The time point when the second wheel axle sensor (102) first receives the upper scale signal and the speed V2 when the second wheel axle sensor (102) receives the lower scale signal, that is, the speed when the first ground sensing coil changes from a low level to a high level signal and then changes from a low level to a high level signal; calculate the acceleration abnormality index α1 of the vehicle to be detected, The acceleration abnormality index α1 of the vehicle to be detected is compared and analyzed with the acceleration abnormality index threshold of the vehicle to be detected: If the ratio of the acceleration abnormality index α1 of the vehicle to be detected to the acceleration abnormality index threshold of the vehicle to be detected is greater than or equal to 1, the feedback module outputs a signal indicating that the vehicle to be detected has abnormal behavior; If the ratio of the acceleration abnormality index α1 of the vehicle to be detected to the acceleration abnormality index threshold of the vehicle to be detected is less than 1, the feedback module outputs a normal weighing signal for the vehicle to be detected.

9. The automatic vehicle overload and over-limit detection device according to claim 8 is characterized in that: The vehicle overload and overlimit dynamic weighing system is also used to obtain the weight of the vehicle to be detected. If both the first ground sensing coil and the second ground sensing coil receive signals, or the first ground sensing coil receives a signal but the weight of the vehicle to be detected does not change, the feedback module outputs an abnormal behavior signal corresponding to the vehicle to be detected.

10. The automatic vehicle overload and over-limit detection device according to claim 9 is characterized in that: When the feedback module outputs a signal that the vehicle to be detected has abnormal behavior, the vehicle overload and over-limit dynamic weighing system further includes a data correction unit, which is used to correct the abnormal data of the abnormal behavior of the vehicle to be detected, specifically: The weighing data of the vehicle to be detected is obtained through the dynamic weighing processing module, wherein the weighing data includes vehicle weight data, vehicle speed data, vehicle axle number data, vehicle tire number data, and vehicle passing time data; Sum all the collected weighing data, then divide it by the number of data to get the average value P1, then square the difference between each data point and the average value, sum it up, divide it by the number of data minus one, and then take the square root to get the standard deviation P2; Set a standard threshold value, which is the mean value plus or minus three times the standard deviation, that is, the standard threshold value is between (P1-3P2) and (P1+3P2), then compare each weighing data with the threshold value, mark the data points that are not within this threshold range as outliers, remove the outliers, and mark the remaining data as normal values; The corrected normal value is then smoothed, such as by using a sliding average filter method, and the corrected and smoothed data are integrated to obtain the weight of the vehicle.

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