An unattended intelligent weighing system

Abstract

The application provides an unattended intelligent weighing system, and relates to the field of automobile weighing, and comprises: an entrance module: reminding a vehicle to swipe a card for entering when detecting a vehicle to be entered; a position detection module: monitoring a parking position of the entered vehicle based on a truck scale, comparing a monitoring position result with a standard position result, and determining an abnormal parking position; an indication module: according to an abnormal-indication mapping table, calling indication content matched with the abnormal parking position, and monitoring a position adjustment of an indication behavior of the entered vehicle and weight monitoring in a position adjustment process; and an exit module: when a weight monitoring result meets a preset constraint standard corresponding to the card swiping information, recording a bearing result. Through automatic induction, monitoring and indication, reasonable adjustment of the position of the vehicle is realized, effective weighing of the vehicle is realized, and the weighing error caused by human observation and the excessive human consumption cost are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of automobile weighing technology, and in particular to an unattended intelligent weighing system. Background Technology

[0002] Currently in my country, traditional weighing systems still rely entirely on manual recording of vehicle information, the weight of goods entering and leaving the warehouse, and summary documents. Furthermore, the following issues are prone to occur during the weighing process: First, when weighing vehicles, the confirmation of the vehicle's parking position relies on visual inspection, inevitably leading to human observation errors and positional inaccuracies. Second, from a labor consumption perspective, each weighing point requires continuous shifts, generating substantial fixed labor costs.

[0003] Therefore, this invention proposes an unattended intelligent weighing system. Summary of the Invention

[0004] In view of the many shortcomings of traditional weighing systems, this invention provides an unattended intelligent weighing system that achieves rational adjustment of vehicle position through automated sensing, monitoring and indication throughout the process, thereby achieving effective weighing of vehicles and effectively solving the weighing errors caused by human observation and the excessive labor costs.

[0005] This invention adopts the following technical solution: an unattended intelligent weighing system, comprising:

[0006] Entry module: When the first ground loop detects a vehicle waiting to enter, it prompts the vehicle to swipe its card to enter, and controls the entrance gate to open after the card is successfully swiped;

[0007] Location detection module: Monitors the parking position of incoming vehicles based on the weighbridge, compares the monitored position results with the standard position results, and determines abnormal parking positions;

[0008] Indication module: Based on the abnormality-indication mapping table, retrieve the indication content that matches the abnormal parking location, and monitor the position adjustment behavior of the entering vehicle and the weight during the position adjustment process.

[0009] Exit module: When the weight monitoring result meets the preset constraint standard corresponding to the card swipe information, record the load result, control the entrance gate to close and control the exit gate to open, and record the vehicle's departure time according to the second ground induction coil.

[0010] Preferably, an unattended intelligent weighing system includes an entry module comprising:

[0011] First inductive loop: Detects vehicles and sends a working signal to the license plate recognition unit when a vehicle is detected passing by;

[0012] License plate recognition unit: After receiving the working signal from the first inductive loop, it identifies the license plate information;

[0013] Unattended intelligent unit: Detects whether the license plate information is in the stored database. If it exists, it prompts for automatic card swiping.

[0014] Barrier gate control unit: After a successful automatic card swipe, it controls the opening of the entrance barrier gate and the closing of the exit barrier gate, indicating that the vehicle is allowed to enter.

[0015] Preferably, an unattended intelligent weighing system further includes, in its entry module:

[0016] Recording unit: Records the fluctuation signal of the first inductive loop during operation, and converts the fluctuation signal at different times during operation into fluctuation values ​​to construct a fluctuation curve;

[0017] Matrix construction unit: Determines the peak value, trough value, first time interval between adjacent peak values ​​and trough values, and second time interval between adjacent trough values ​​and peak values ​​of the fluctuation curve, and constructs the fluctuation matrix B;

[0018]

[0019] Among them, f t01 f represents the peak value of the fluctuation at time t01; t0n1 Represents the peak fluctuation at time t0n1; g t02 Represents the trough value of the fluctuation at time t02; g t0n1+1 t02-t01 represents the trough value at time t0n1+1; t02-t01 represents the first time interval; t0n1+1-t0n1 represents the n1st time interval; t02-t03 represents the first time interval; t0n1+1-t0n1+2 represents the n1st time interval.

[0020] Output unit: Inputs the wave matrix into the wave analysis model to obtain the output result;

[0021] Triggering unit: When the output result is related to the detection of a vehicle passing by, the license plate recognition unit is triggered to work.

[0022] Preferably, an unattended intelligent weighing system includes a position detection module comprising:

[0023] Monitoring unit: Cameras positioned diagonally opposite the truck scale: capture a first azimuth view and a second azimuth view of the truck scale, wherein the first azimuth view is the rear azimuth view of the entering vehicle; and the second azimuth view is the front azimuth view of the entering vehicle.

[0024] First distribution unit: Perform position matching analysis between the first orientation map and the first standard survey map to determine the distribution of the first location points based on the first standard survey map;

[0025] Second distribution unit: Perform position matching analysis between the second orientation map and the second standard map to determine the distribution of the second location points based on the second standard map;

[0026] Placement information determination unit: Determines the current placement information of vehicles entering the weighbridge based on the distribution of the first and second location points;

[0027] At the same time, a standard occupancy point that matches the vehicle model of the entering vehicle is obtained from the vehicle database;

[0028] Quantity comparison unit: If the distribution of the total number of positions corresponding to the distribution of the first position point and the distribution of the second position point is within the distribution range of the standard occupancy points, then it is determined that the entering vehicle is fully weighed.

[0029] Otherwise, the abnormal parking location is determined based on the actual occupancy point and the standard occupancy point formed by the distribution of the first and second location points.

[0030] Preferably, an unattended intelligent weighing system includes an entry module comprising:

[0031] First calibration unit: Based on the abnormal parking location, construct an abnormal layout diagram, and perform a first calibration on the abnormal layout diagram according to the tire condition of the front tires and a second calibration on the abnormal layout diagram according to the tire condition of the rear tires.

[0032] Position extension unit: According to the vehicle weighing direction and the distribution trajectory of the first position point, the first position point is extended in the opposite direction. At the same time, according to the distribution trajectory of the second position point and the vehicle weighing direction, the second position point is extended in the positive direction.

[0033] The second calibration unit extends the reverse position into the abnormal layout diagram for a third calibration and extends the positive position into the abnormal layout diagram for a fourth calibration.

[0034] Layout division unit: Based on the first calibration result, the second calibration result, the third calibration result, and the fourth calibration result, the abnormal layout map is divided into layouts to obtain the abnormal sequence of each layout region;

[0035] Content acquisition unit: Based on the anomaly-indicator mapping table, acquire indication content that matches the anomaly sequence;

[0036] Content Adjustment Unit: For all the acquired instruction content, adjust all the instruction content according to the driving behavior habits of the drivers who entered the vehicle, and obtain the sorted instruction content;

[0037] Position adjustment unit: According to the sorted instructions, it sequentially issues instruction commands to the entering vehicles to adjust their positions.

[0038] Preferably, in an unattended intelligent weighing system, the indicating module further includes:

[0039] Process monitoring unit: Real-time monitoring of the positional and weight changes of each indicated item during positional adjustments;

[0040] Coefficient calculation unit: determines the position correction amount based on each indication content according to the position change amount, and at the same time, determines the weight change coefficient according to the weight change amount;

[0041] Standard judgment unit: Determines whether the position correction coefficient and weight change coefficient meet the preset constraint standard.

[0042] Preferably, an unattended intelligent weighing system includes a coefficient calculation unit comprising:

[0043] Correcting collection building blocks: Build location correcting collection:

[0044]

[0045] Among them, w01 j This represents all corrected positions after adjusting the position according to the j-th instruction; w02 j W1 represents the uncorrected position of the j-th instruction content; W1 represents the position correction set. This represents the individual correction coefficient after adjusting the position according to the j-th instruction.

[0046] Correction coefficient calculation unit: Calculates the position correction coefficient X1:

[0047]

[0048] Where, ∑w01 j This represents the total positional correction for all indicated content; ∑w02 j W1 represents the position quantity to be corrected corresponding to all indicated contents. [n1 / 2]，max Indicates all After sorting by size, the sum of the first [n1 / 2] individual correction coefficients is obtained; [] represents the integer part.

[0049] Preferably, in an unattended intelligent weighing system, the coefficient calculation unit further includes:

[0050] Weight set building block: Constructs a set of weight changes;

[0051] G1={g01 j ,j=1,2,...,n1}

[0052] Among them, g01 j G1 represents the weight change after the position is adjusted according to the j-th instruction; G1 represents the set of weight changes.

[0053] Weight coefficient calculation unit: Calculates the weight change coefficient X2;

[0054]

[0055] Where max{G1} represents the maximum weight change in the set of weight changes; g01 n1 This represents the last weight measurement in the set of weight changes.

[0056] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0057] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0058] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0059] Figure 1 This invention provides an unattended intelligent weighing system.

[0060] Figure 2 This is the placement position of the camera in the position detection module of this embodiment of the invention;

[0061] Figure 3 This is a standard monitoring chart in an embodiment of the present invention;

[0062] Figure 4 This is an extended view of the opposite position in an embodiment of the present invention;

[0063] Figure 5 This is a forward position extension diagram in an embodiment of the present invention. Detailed Implementation

[0064] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0065] Example 1:

[0066] This invention provides an unattended intelligent weighing system, such as... Figure 1 As shown, it includes:

[0067] Entry module: When the first ground loop detects a vehicle waiting to enter, it prompts the vehicle to swipe its card to enter, and controls the entrance gate to open after the card is successfully swiped;

[0068] Location detection module: Monitors the parking position of incoming vehicles based on the weighbridge, compares the monitored position results with the standard position results, and determines abnormal parking positions;

[0069] Indication module: Based on the abnormality-indication mapping table, retrieve the indication content that matches the abnormal parking location, and monitor the position adjustment behavior of the entering vehicle and the weight during the position adjustment process.

[0070] Exit module: When the weight monitoring result meets the preset constraint standard corresponding to the card swipe information, record the load result, control the entrance gate to close and control the exit gate to open, and record the vehicle's departure time according to the second ground induction coil.

[0071] In this embodiment, the vehicle detection by the entry module includes: detection of the first inductive loop and detection of the license plate;

[0072] In this embodiment, "vehicles to be entered" refers to the vehicle type identified by the entrance module after detecting the passing vehicles. The vehicle types include different sizes and models of coal mine cars.

[0073] In this embodiment, the vehicle card swiping is done automatically after matching the license plate information with the information in the stored database. Only after the card swiping is successful can the vehicle be weighed. The stored database contains various license plate information that needs to be weighed, mainly to ensure that the vehicle with that license plate has weighing authority.

[0074] In this embodiment, the vehicle's parking position based on the weighbridge refers to the vehicle's position after it has driven to the area where the weighbridge is located and stopped moving.

[0075] In this embodiment, the standard position refers to the range of positions where the weighbridge allows weighing, that is, the vehicle weight is accurate within this range;

[0076] In this embodiment, an abnormal parking location refers to the part of the block where the vehicle parking location does not overlap with the weighbridge detection range. In other words, the vehicle is not completely placed within the accurate weighing range. For example, the vehicle needs to be completely parked in area A, but the vehicle is parked beyond the boundary line of area A, so there will be a non-overlapping part.

[0077] In this embodiment, the anomaly-indication mapping table identifies abnormal locations and then searches for corresponding indications based on those locations. As the vehicle is being moved, the system uses the vehicle's current parking position and its deviation from the standard parking position, as well as its displacement and angle, to guide the driver and guide the vehicle to the standard parking area.

[0078] In this embodiment, the instruction content refers to the movement distance and direction data of the vehicle from the abnormal position to the standard parking position, and the instruction behavior refers to the specific operation performed by the driver based on the instruction content. For example, if the instruction content is to move the vehicle from position 1 to position 2, the instruction behavior from position 1 to position 2 is: first turn the steering wheel half a turn to the left, move forward 0.1 meters, and then straighten the steering wheel.

[0079] In this embodiment, during the position adjustment process, the vehicle gradually returns from the deviated position to the standard range, so there will be a certain change in position. At the same time, due to the change in position, the collected weight will also change to some extent.

[0080] In this embodiment, weight monitoring is the monitoring of the total weight of the vehicle itself during the adjustment process according to the instructions;

[0081] In this embodiment, vehicle location recognition is performed based on a camera capturing images of the vehicle.

[0082] In this embodiment, the preset standard constraint range is based on the vehicle model determined by the entry module. Based on the query data, the final parking position and final weighing weight of the vehicle are constrained to ensure that the parking position and weighing are reasonable.

[0083] The beneficial effects of the above solution are: through automated sensing, monitoring and indication throughout the process, the vehicle position can be rationally adjusted, thereby achieving effective weighing of the vehicle and effectively solving the weighing errors caused by human observation and the excessive manpower costs.

[0084] Example 2

[0085] This invention provides an unattended intelligent weighing system, the entry module of which includes:

[0086] First inductive loop: Detects vehicles and sends a working signal to the license plate recognition unit when a vehicle is detected passing by;

[0087] License plate recognition unit: After receiving the working signal from the first inductive loop, it identifies the license plate information;

[0088] Unattended intelligent unit: Detects whether the license plate information is in the stored database. If it exists, it prompts for automatic card swiping.

[0089] Barrier gate control unit: After a successful automatic card swipe, it controls the opening of the entrance barrier gate and the closing of the exit barrier gate, indicating that the vehicle is allowed to enter.

[0090] Recording unit: Records the fluctuation signal of the first inductive loop during operation, and converts the fluctuation signal at different times during operation into fluctuation values ​​to construct a fluctuation curve;

[0091] Matrix construction unit: Determines the peak value, trough value, first time interval between adjacent peak values ​​and trough values, and second time interval between adjacent trough values ​​and peak values ​​of the fluctuation curve, and constructs the fluctuation matrix B;

[0092]

[0093] Among them, f t01 f represents the peak value of the fluctuation at time t01; t0n1 Represents the peak fluctuation at time t0n1; g t02 Represents the trough value of the fluctuation at time t02; g t0n1+1 t02-t01 represents the trough value at time t0n1+1; t02-t01 represents the first time interval; t0n1+1-t0n1 represents the n1st time interval; t02-t03 represents the first time interval; t0n1+1-t0n1+2 represents the n1st time interval.

[0094] Output unit: Inputs the wave matrix into the wave analysis model to obtain the output result;

[0095] Triggering unit: When the output result is related to the detection of a vehicle passing by, the license plate recognition unit is triggered to work.

[0096] In this embodiment, the first inductive loop coil forms an LC oscillation circuit through a loop coil, a coil lead feeder (L), and a vehicle detector capacitor (C). The inductive loop detector detects the oscillation frequency of this LC oscillation circuit.

[0097] In this embodiment, when a metal vehicle passes over the inductive loop, it causes a change in the spatial medium, resulting in an increase in the oscillation frequency. The change in the oscillation frequency is used to determine whether the vehicle has passed over.

[0098] In this embodiment, the fluctuation signal refers to the change in the oscillation frequency of the inductive loop during operation, based on the reference frequency (i.e., the oscillation frequency of the inductive loop when there are no vehicles).

[0099] In this embodiment, the first inductive coil is equipped with a protection circuit to prevent the capacitor from being damaged by the accumulated charge after multiple operations, which would cause the inductive coil to malfunction.

[0100] In this embodiment, the vehicle model that matches the license plate information is retrieved from the vehicle storage database.

[0101] In this embodiment, the unattended intelligent unit can search for vehicle data in the system through license plate information. When the corresponding data is matched, the unattended intelligent unit automatically swipes the card and enters the detection data into the system for easy retrieval later.

[0102] In this embodiment, the barrier gate control unit can control the entrance barrier gate and the exit barrier gate, including: when the weighing system is not working, the entrance barrier gate is closed and the exit barrier gate is open; when a vehicle enters, the entrance barrier gate is open and the exit barrier gate is closed, allowing the vehicle to enter; after the vehicle is weighed, the entrance barrier gate is closed and the exit barrier gate is open, allowing the vehicle to leave, and indicating that the system is idle;

[0103] In this embodiment, the fluctuation analysis model is trained based on different signals generated by the inductive loop under different loads and the weights that match the signals. Therefore, the fluctuation information measured by the inductive loop for the vehicle model can be obtained, thereby determining whether there is a real vehicle to be entered, and thus controlling whether the barrier gate is opened to ensure the efficiency of weighing.

[0104] In this embodiment, the output result is based on the input fluctuation and fluctuation analysis model, matching the standard waveform with the highest similarity to the input waveform, confirming the corresponding vehicle model and using it as the output result, in order to determine whether the vehicle to be entered is real.

[0105] The beneficial effects of the above technical solution are: by automatically swiping cards and recognizing vehicle models through the entrance module, the manual card swiping process is reduced, the vehicle weighing procedure is simplified, and the weighing efficiency is improved.

[0106] Example 3:

[0107] This invention provides an unattended intelligent weighing system, whose position detection module monitors the vehicle's parking position using a diagonal camera on the weighbridge to confirm whether the vehicle is fully on the scale, including:

[0108] Monitoring unit: Cameras positioned diagonally opposite the truck scale: capture a first azimuth view and a second azimuth view of the truck scale, wherein the first azimuth view is the rear azimuth view of the entering vehicle; and the second azimuth view is the front azimuth view of the entering vehicle.

[0109] First distribution unit: Perform position matching analysis between the first orientation map and the first standard survey map to determine the distribution of the first location points based on the first standard survey map;

[0110] Second distribution unit: Perform position matching analysis between the second orientation map and the second standard map to determine the distribution of the second location points based on the second standard map;

[0111] Placement information determination unit: Determines the current placement information of vehicles entering the weighbridge based on the distribution of the first and second location points;

[0112] At the same time, a standard occupancy point that matches the vehicle model of the entering vehicle is obtained from the vehicle database;

[0113] Quantity comparison unit: If the distribution of the total number of positions corresponding to the distribution of the first position point and the distribution of the second position point is within the distribution range of the standard occupancy points, then it is determined that the entering vehicle is fully weighed.

[0114] Otherwise, the abnormal parking location is determined based on the actual occupancy point and the standard occupancy point formed by the distribution of the first and second location points.

[0115] In this embodiment, the monitoring unit camera is placed in the following position: Figure 2 As shown, the diagonal camera can only detect one side of the vehicle, such as the front and left sides, the rear and right sides. The rear orientation map represents the image data of the rear side of the vehicle observed by the camera, and the front orientation map represents the image data of the front side of the vehicle observed by the camera. The first orientation map and the second orientation map can fully display the area occupied by the vehicle on the weighbridge.

[0116] In this embodiment, the first standard view refers to the front view of the vehicle as observed by the rear-end camera when the vehicle is parked at the standard inspection position on the weighbridge, and the second standard view refers to the rear view of the vehicle as observed by the front-end camera when the vehicle is parked at the standard inspection position on the weighbridge. Figure 3 As shown, a1 is a truck scale, b1 is a shot taken of the front half to obtain a standard monitoring image of the front half, and b2 is a shot taken of the rear half to obtain a standard monitoring image of the rear half.

[0117] In this embodiment, the consistent standard occupancy point refers to the accurately measurable position range of the vehicle on the truck scale, which is generally the middle area of ​​the truck scale.

[0118] In this embodiment, determining whether it is within the corresponding range is mainly to determine the positional relationship between the distributed location points and the standard occupancy points, thereby effectively identifying abnormal parking locations.

[0119] In this embodiment, the first location point and the second location point are determined by matching the positions of the images using the corresponding orientation map and the standard map, and then extracting the overlapping points to determine the distribution of the overlapping points on the standard map.

[0120] In this embodiment, the placement information includes vehicle placement angle deviation and vehicle placement position deviation;

[0121] In this embodiment, the position detection unit camera collects the vehicle's location map while simultaneously capturing images of the weighing vehicle. The video capture records the situation during vehicle weighing.

[0122] The beneficial effects of the above technical solution are: the position detection module detects the vehicle position and effectively ensures that the vehicle can be fully weighed by comparing the standard occupancy point with the actual occupancy point. At the same time, it captures the vehicle weighing image, ensuring the reliability and authenticity of the truck scale detection data.

[0123] Example 4:

[0124] This invention provides an unattended intelligent weighing system, whose indicating module includes:

[0125] First calibration unit: Based on the abnormal parking location, construct an abnormal layout diagram, and perform a first calibration on the abnormal layout diagram according to the tire condition of the front tires and a second calibration on the abnormal layout diagram according to the tire condition of the rear tires.

[0126] Position extension unit: According to the vehicle weighing direction and the distribution trajectory of the first position point, the first position point is extended in the opposite direction. At the same time, according to the distribution trajectory of the second position point and the vehicle weighing direction, the second position point is extended in the positive direction.

[0127] The second calibration unit extends the reverse position into the abnormal layout diagram for a third calibration and extends the positive position into the abnormal layout diagram for a fourth calibration.

[0128] Layout division unit: Based on the first calibration result, the second calibration result, the third calibration result, and the fourth calibration result, the abnormal layout map is divided into layouts to obtain the abnormal sequence of each layout region;

[0129] Content acquisition unit: Based on the anomaly-indicator mapping table, acquire indication content that matches the anomaly sequence;

[0130] Content Adjustment Unit: For all the acquired instruction content, adjust all the instruction content according to the driving behavior habits of the drivers who entered the vehicle, and obtain the sorted instruction content;

[0131] Position adjustment unit: According to the sorted instructions, it sequentially issues instruction commands to the entering vehicles to adjust their positions.

[0132] Process monitoring unit: Real-time monitoring of the positional and weight changes of each indicated item during positional adjustments;

[0133] Coefficient calculation unit: determines the position correction amount based on each indication content according to the position change amount, and at the same time, determines the weight change coefficient according to the weight change amount;

[0134] Standard judgment unit: determines whether the position correction coefficient and weight change coefficient meet the preset constraint standard;

[0135] The coefficient calculation unit includes:

[0136] Correct set building block: Correct set location for build;

[0137]

[0138] Among them, w01 j This represents all corrected positions after adjusting the position according to the j-th instruction; w02 j W1 represents the uncorrected position of the j-th instruction content; W1 represents the position correction set. This represents the individual correction coefficient after adjusting the position according to the j-th instruction.

[0139] Correction coefficient calculation unit: Calculates the position correction coefficient X1:

[0140]

[0141] Where, ∑w01 j This represents the total positional correction for all indicated content; ∑w02 j W1 represents the position quantity to be corrected corresponding to all indicated contents. [n1 / 2]，max Indicates all After sorting by size, the sum of the first [n1 / 2] individual correction coefficients is obtained; [] represents the integer part.

[0142] Weight set building block: Constructs a set of weight changes;

[0143] G1 = g01 j ,j=1,2,...,n1}

[0144] Among them, g01 j G1 represents the weight change after the position is adjusted according to the j-th instruction; G1 represents the set of weight changes.

[0145] Weight coefficient calculation unit: Calculates the weight change coefficient X2;

[0146]

[0147] Where max{G1} represents the maximum weight change in the set of weight changes; g01 n1 This represents the last weight measurement in the set of weight changes.

[0148] In this embodiment, wheel recognition is performed by preprocessing the original image captured by the camera to avoid noise contamination of the original image; a threshold is adaptively selected based on the maximum inter-class variance between the target and the background, and thresholding segmentation and binarization are performed to obtain the effect image; based on shape features, the wheels in the effect image are identified and located through Hough transform.

[0149] In this embodiment, the tire condition includes the deviation between the vehicle direction and the tire angle, and the distance deviation between the tire position and the standard position.

[0150] In this embodiment, the position of the front wheels of the vehicle is first calibrated by the state of the front wheels, and the position of the rear wheels of the vehicle is second calibrated by the state of the rear wheels. Since the tires of the vehicle will have a contact position with the truck scale, the contact direction can be effectively determined. In other words, the purpose of the first and second calibrations is to intuitively display the current state of the tires on the truck scale, which facilitates the subsequent disassembly of the abnormal layout diagram.

[0151] In this embodiment, if the first position point does not coincide with the corresponding standard occupant point, the first position point is calibrated for the third time; if the second position point does not coincide with the corresponding standard occupant point, the second position point is calibrated for the fourth time.

[0152] In this embodiment, the distribution trajectory refers to the distribution of the first and second position points at the points where the azimuth map and the corresponding standard survey map coincide, according to the order of the vehicle from front to back.

[0153] In this embodiment, the positive direction refers to the direction in which the front of the vehicle faces when it is in the standard parking position after being put on the weighbridge; similarly, the negative direction refers to the direction in which the rear of the vehicle faces when it is in the standard parking position after being put on the weighbridge.

[0154] In this embodiment, the direction of the vehicle onto the weighbridge is determined by the forward trajectory of the front wheels from the moment they contact the weighbridge until the vehicle is driven onto the weighbridge.

[0155] In this embodiment, the first location point distribution refers to the position occupancy of the vehicle based on the front half of the weighbridge as captured by the camera. The distribution trajectory refers to the representative trajectory obtained from the first location point distribution, such as the trajectory obtained by connecting the midpoints of the first location point distribution. The distribution trajectory of the second location point distribution is similar in principle to the distribution trajectory of the first location point distribution.

[0156] In this embodiment, the reverse position extension refers to extending the distribution trajectory based on the first position point distribution in the opposite direction to the upward weighing direction. The extension trajectory is determined by extending the trajectory according to the tangent of the first point of the corresponding distribution trajectory and the tangent of the middle point on the trajectory, based on the midpoint angle between the two tangents.

[0157] Positive direction position extension refers to extending the distribution trajectory based on the second position point distribution in the positive direction of the upward pressure. The extended trajectory is determined by the midpoint between the tangent at the last point of the corresponding distribution trajectory and the tangent at the midpoint of the trajectory. Specifically, the positive extension direction is as follows: Figure 4 and 5 As shown.

[0158] After determining the reverse direction position extension, the forward direction position extension, and the calibration based on tire status, an effective partitioning scheme for the abnormal layout map can be retrieved from the calibration combination-partition database to partition the layout map. This database is a pre-defined database set by experts and includes different combinations of calibration and partitioning schemes. Therefore, abnormal sequences can be obtained. An abnormal sequence refers to the mismatch sequence between the position point and the standard point of each partitioned area. For example, position point 1 should be occupied, but it is not actually occupied. That is, the sequence is obtained by combining the position coordinates and whether the corresponding point is occupied.

[0159] In this embodiment, the vehicle moves by operating the steering wheel step by step until it returns to the standard range. In other words, this process is based on matching the abnormal sequence and the mapping table to obtain the instruction content, and then determining the adjustment plan.

[0160] In this embodiment, driving behavior habits refer to the driver's driving habits. For example, if the driver's driving habits are to move forward and backward, and then move left and right, then when planning the scheme, the relevant forward and backward movement instructions can be set first, and then the left and right movement instructions can be set. The ultimate goal is to move the vehicle within the standard range.

[0161] For example, the instruction content is: Content 1 - Content 2 - Content 3 - Content 4. After adjustment according to convention, it becomes: Content 1 - Content 3 - Content 4 - Content 2.

[0162] In this embodiment, the first calibration result, the second calibration result, the third calibration result, and the fourth calibration result are used to divide the abnormal layout map into four parts. Specifically, based on the first calibration result and the second calibration result, the wheels in the abnormal layout map are divided into front and rear parts. Based on the standard parking position, the wheel status of the front and rear wheels of the vehicle is detected as abnormal. Then, based on the third calibration result and the fourth calibration result, the abnormal layout map is divided and detected on the left and right sides of the vehicle. According to the overall placement of the vehicle, the non-overlapping and overlapping parts of the vehicle and the standard detection position are identified.

[0163] In this embodiment, the abnormal sequence refers to arranging the detected abnormal data according to wheel direction abnormal information, vehicle body direction abnormal information, and wheel position abnormal information based on the abnormal layout diagram.

[0164] In this embodiment, the instruction refers to the direction and distance of movement required when an abnormal wheel of the vehicle moves to the standard parking position.

[0165] In this embodiment, driving behavior habits refer to the operating behaviors of the driver on the vehicle, including tire direction control, vehicle forward and reverse movement;

[0166] In this embodiment, the anomaly-indication mapping table identifies the anomaly location and then searches for the corresponding indication content based on the identified anomaly location.

[0167] In this embodiment, the sorted instructions refer to the abnormal vehicle moving from the abnormal position to the standard parking position. The operations that the driver needs to perform are: the first vehicle position adjustment operation based on the initial abnormal position and the standard parking position, the second vehicle position adjustment operation based on the vehicle position after the first operation and the standard parking position, and the Nth vehicle position adjustment operation until the vehicle is completely within the range of the standard parking position.

[0168] In this embodiment, the indicator position adjustment unit includes an LED screen and a voice playback device. The LED unit has a strong visual impact and can effectively remind the driver of the vehicle status and adjust the indicator.

[0169] In this embodiment, the position correction amount includes a distance correction amount and a direction correction amount;

[0170] In this embodiment, the vehicle is detected in real time by a diagonal camera to determine the vehicle's position and ensure that the vehicle is fully weighed without any cheating.

[0171] In this embodiment, multiple edge weighing sensors of the truck scale are arranged in a ring, and a central weighing sensor is set at the middle position of the ring. Based on the changes in the values ​​of the truck scale sensors, the changes in vehicle weight are detected in real time.

[0172] In this embodiment, the correction set building block represents the vehicle abnormal position correction status by calculating the intersection of the corrected position and the uncorrected position, that is, the corrected abnormal position and the position to be corrected.

[0173] The beneficial effects of the above technical solution are: by comprehensively dividing the abnormal layout map into four dimensions, the abnormal sequence of each divided area can be determined, thereby enabling accurate vehicle indication. Furthermore, by effectively calculating the position correction coefficient and weight change coefficient, the parking of the vehicle can be evaluated to ensure that the vehicle is within the standard parking position, thus improving the accuracy of the detection results.

[0174] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An unattended intelligent weighing system, characterized in that, include: Entry module: When the first ground loop detects a vehicle waiting to enter, it prompts the vehicle to swipe its card to enter, and controls the entrance gate to open after the card is successfully swiped; Location detection module: Monitors the parking position of incoming vehicles based on the weighbridge, compares the monitored position results with the standard position results, and determines abnormal parking positions; Indication module: Based on the abnormal-indication mapping table, retrieve the indication content that matches the abnormal parking location, and monitor the position adjustment behavior of the entering vehicle and the weight during the position adjustment process; The indicating module includes: First calibration unit: Based on the abnormal parking location, construct an abnormal layout diagram, and perform a first calibration on the abnormal layout diagram according to the tire condition of the front tires and a second calibration on the abnormal layout diagram according to the tire condition of the rear tires. Position extension unit: According to the vehicle weighing direction and the distribution trajectory of the first position point, the first position point is extended in the opposite direction. At the same time, according to the distribution trajectory of the second position point and the vehicle weighing direction, the second position point is extended in the positive direction. Second calibration unit: extends the reverse position into the abnormal layout diagram for third calibration and extends the positive position into the abnormal layout diagram for fourth calibration; Layout division unit: Based on the first calibration result, the second calibration result, the third calibration result, and the fourth calibration result, the abnormal layout map is divided into layouts to obtain the abnormal sequence of each layout region; Content acquisition unit: Based on the anomaly-indicator mapping table, acquire indication content that matches the anomaly sequence; Content Adjustment Unit: For all the acquired instruction content, adjust all the instruction content according to the driving behavior habits of the drivers who entered the vehicle, and obtain the sorted instruction content; Position adjustment unit: According to the sorted instructions, it sequentially issues instruction commands to the entering vehicles to adjust their positions. Exit module: When the weight monitoring result meets the preset constraint standard corresponding to the card swipe information, record the weighing result, control the entrance gate to close and control the exit gate to open, and record the vehicle's departure time according to the second ground induction coil.

2. The system according to claim 1, characterized in that: The entry module includes: First inductive loop: Detects vehicles and sends a working signal to the license plate recognition unit when a vehicle is detected passing by; License plate recognition unit: After receiving the working signal from the first inductive loop, it identifies the license plate information; Unattended intelligent unit: Detects whether the license plate information is in the stored database. If it exists, it prompts for automatic card swiping. Barrier gate control unit: After a successful automatic card swipe, it controls the opening of the entrance barrier gate and the closing of the exit barrier gate, indicating that the vehicle is allowed to enter.

3. The system according to claim 2, characterized in that: The entry module also includes: Recording unit: Records the fluctuation signal of the first inductive loop during operation, and converts the fluctuation signal at different times during operation into fluctuation values ​​to construct a fluctuation curve; Matrix construction unit: Determines the peak value, trough value, first time interval between adjacent peak values ​​and trough values, and second time interval between adjacent trough values ​​and peak values ​​of the fluctuation curve, and constructs the fluctuation matrix B; in, This represents the peak value of the fluctuation at time t01; This represents the peak value of the fluctuation at time t0n1; This represents the trough value of the fluctuation at time t02; express The trough of fluctuation at any given moment; This indicates the first time interval; This represents the n1th first time interval; Indicates the first second time interval; This represents the n1th second time interval; Output unit: Inputs the wave matrix into the wave analysis model to obtain the output result; Triggering unit: When the output result is related to the detection of a vehicle passing by, the license plate recognition unit is triggered to work.

4. The system according to claim 1, characterized in that: The position detection module includes: Monitoring unit: Cameras positioned diagonally opposite the truck scale: capture a first azimuth view and a second azimuth view of the truck scale, wherein the first azimuth view is the rear azimuth view of the entering vehicle; and the second azimuth view is the front azimuth view of the entering vehicle. First distribution unit: Perform position matching analysis between the first orientation map and the first standard survey map to determine the distribution of the first location points based on the first standard survey map; Second distribution unit: Perform position matching analysis between the second orientation map and the second standard map to determine the distribution of the second location points based on the second standard map; Placement information determination unit: Determines the current placement information of vehicles entering the weighbridge based on the distribution of the first and second location points; At the same time, a standard occupancy point that matches the vehicle model of the entering vehicle is obtained from the vehicle database; Quantity comparison unit: If the distribution of the total number of positions corresponding to the distribution of the first position point and the distribution of the second position point is within the distribution range of the standard occupancy points, then it is determined that the entering vehicle is fully weighed. Otherwise, the abnormal parking location is determined based on the actual occupancy point and the standard occupancy point formed by the distribution of the first and second location points.

5. The system according to claim 4, characterized in that: The indicator module further includes: Process monitoring unit: Real-time monitoring of the positional and weight changes of each indicated item during positional adjustments; Coefficient calculation unit: determines the position correction amount based on each indication content according to the position change amount, and at the same time, determines the weight change coefficient according to the weight change amount; Standard judgment unit: Determines whether the position correction coefficient and weight change coefficient meet the preset constraint standard.

6. The system according to claim 5, characterized in that, The coefficient calculation unit includes: Correcting collection building blocks: Build location correcting collection: in, This represents all corrected positions after adjusting the position according to the j-th instruction. W1 represents the uncorrected position of the j-th instruction content; W1 represents the position correction set. This represents the individual correction coefficient after adjusting the position according to the j-th instruction. Correction coefficient calculation unit: calculates the position correction coefficient. : in, This indicates the total positional correction for all indicated content; This indicates the quantity of positions to be corrected corresponding to all indicated content; Indicates all After sorting by size, get the first The sum is obtained by accumulating the individual correction coefficients; [] indicates the integer symbol.

7. The system according to claim 6, characterized in that, The coefficient calculation unit further includes: Weight set building block: Constructs a set of weight changes; in, G1 represents the weight change after the position is adjusted according to the j-th instruction; G1 represents the set of weight changes. Weight coefficient calculation unit: calculates the weight change coefficient. ; in, This indicates that the maximum weight change in the set of weight changes is obtained; This represents the last weight measurement in the set of weight changes.

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