A method for classifying and segmenting the signal acquisition of a vehicle dynamic weighing sensor

Abstract

The present invention proposes a method for classifying and segmentally collecting and extracting data line segments for signals of vehicle dynamic weighing sensors according to corresponding node times t, using time t as a common parameter, and using the start and end node times t of the state changes of vehicle driving acceleration a and speed V as dividing points. The method is suitable for classifying, segmentally collecting and extracting dynamic weighing signals of vehicles in the field of transportation, and is a method for collecting and extracting more accurately and reasonably classified and segmented basic measurement data line segments for later accurate vehicle weighing weight calculation.

Description

Technical field:

[0001] The present invention relates to a method for classifying and segmentedly collecting and extracting signals of a vehicle dynamic weighing scale body sensor according to different changes in vehicle acceleration and speed states. The method is applicable to the dynamic weighing signals of vehicles in the field of transportation, and is used for classifying, segmentedly collecting and extracting different motion states. The method is a method for collecting and extracting more accurately and reasonably classified and segmented basic measurement data segments for later accurate vehicle weighing weight calculation. Background technology:

[0002] The existing method of dynamic weight charging on the road requires that when the vehicle approaches the toll station, the speed of the vehicle drops from about 80km / h to below V≤10km / h and passes through the dynamic scale. Due to the sudden narrowing of the lane and the various monitors causing certain tension and pressure on the driver, the driver must constantly adjust the speed of the vehicle when passing through the weighing platform area and pass through carefully. Some malicious drivers deliberately "jump the scale" to try to reduce the weighing weight. Due to various factors, when the wheels accelerate or decelerate through the weighing platform, the symmetrical platform has a downward vector setback force that changes direction and size continuously. The existing dynamic weighing data collection method is to use the data of the weighing force P of the vertical sensor readings of all different movement processes of the vehicle, including the vector setback force, without classification and segmentation, for the calculation of the vehicle axle weight and the cumulative overall weight. The result is definitely very error-prone, so 99% of the dynamic axle weight scales formed by this collection method have been eliminated. Summary of the invention:

[0003] The present invention proposes a method for classifying and segmenting the signals of the scale sensor during dynamic weighing of the vehicle using a common time t as a parameter, using the start and end node times t of the state changes of the vehicle's driving acceleration a and speed V, and extracting data line segments according to the corresponding node times t. The method of the present invention is applicable to the data acquisition method of the horizontal and vertical two-dimensional sensor structure scale disclosed in the invention patent: 201510340408.8 and the utility model patent: 2101520423804.2.

[0004] Content of the present invention is:

[0005] A method for classifying and segmented acquisition of vehicle dynamic weighing sensor signals, characterized in that: using time t as a common parameter, using the start and end node times t of the vehicle's driving acceleration a or speed V state change as dividing points, the vehicle dynamic weighing sensor signals are classified and segmentedly acquired according to the corresponding node times t to extract data line segments.

[0006] Its characteristic is that the signal of the vehicle dynamic weighing sensor includes an induction signal and a digital signal after A / D conversion.

[0007] The method is characterized in that: taking time t as a common parameter, using the vehicle acceleration a as 0, that is, the start and end node time t when the vehicle moves at a uniform speed as the dividing point, the signal of the vehicle dynamic scale sensor is classified and segmentedly collected according to the corresponding node time t to extract the data line segment.

[0008] Its characteristics are: using time t as a common parameter, using the vehicle acceleration a as a constant, that is, the start and end node time t of uniformly accelerated motion as dividing points, and classifying and segmenting the signals of the vehicle dynamic scale sensor according to the corresponding node time t to extract data line segments.

[0009] Its characteristics are: using time t as a common parameter, using vehicle acceleration a as a variable, that is, the start and end node time t during speed change movement as a dividing point, and classifying and segmenting the signals of the vehicle dynamic scale sensor according to the corresponding node time t to extract data line segments.

[0010] Its characteristic is that the method described is applicable to the vehicle axle weight scale with two-dimensional horizontal and vertical sensor structure, and the signals of the two-dimensional sensor of the horizontal force F and the vertical weighing force P of the wheel on the scale platform are classified and segmentedly collected according to the corresponding node time t to extract the data line segments.

[0011] Its characteristic is that the method described is applicable to the method of classifying and segmentally collecting the signals of the two-dimensional sensors of the horizontal force F and the vertical weighing force P of the vehicle on the scale platform when the integral vehicle weighing scale with a two-dimensional horizontal and vertical sensor structure is weighed, and extracting data line segments according to the corresponding node time t.

[0012] Its characteristic is that the method described is applicable to the vehicle integral scale and axle weight scale with a traditional one-dimensional vertical weighing force P sensor structure, and the signal of the vehicle wheel weighing force P sensor in the vertical direction of the scale body is classified and segmented according to the corresponding node time t to extract the data line segment. Description of the drawings:

[0013] Attached Figure 1The method of the present invention uses time t as a common parameter and the start and end node time t of the acceleration a data line change to classify and segmentally collect the horizontal force F data curve and the vertical weighing force P data curve measured by the two-dimensional sensor structure axle weight scale. In the figure, the horizontal force F coordinate system is at the top, the vertical weighing force P coordinate system is in the middle, and the acceleration a value state coordinate system is at the bottom. The horizontal time t axes of the three coordinate systems are parallel to each other, and the point O is aligned left and right. The vertical axes of the three coordinate systems are on the same vertical line. t1, t2, and t3 on the t axis of the acceleration a coordinate system represent the start and end node times of the acceleration a state change, respectively. The virtual vertical classification lines L1, L2, and L3 at the time points t1, t2, and t3 represent the method of classifying and segmentally collecting the horizontal force F and vertical weighing force P data curves at the corresponding time points and extracting the line segments between L1 and L2 and L2 and L3 on the classified and segmented F and P data curves.

[0014] Attached Figure 2 It is a program flow chart of the method of the present invention, which includes signal collection from the horizontal force F sensor and vertical weighing force P sensor of the two-dimensional sensor structure scale body and the detection of the vehicle acceleration a detector, to the conversion of the three A / D signals, to the establishment of the F, P, a three-data associated coordinate system synthesis and the real-time data input, and the determination of the start and end node time t of the acceleration a change, to the segmented classification collection of the F and P data corresponding to the node time and the calculation processing of the extracted line segments, to the display of the processed results, the output of the results, the storage of the results and other program flows. Specific implementation method:

[0015] According to the attached Figure 1 and attached Figure 2The schematic design scheme and program flow are applied using computer software programming technology and program design: (1) Programming the data coordinate system of a two-dimensional sensor structure weighing platform with time t as the horizontal axis and the horizontal force F and vertical weighing force P data curves as the vertical axes; (2) Programming the coordinate system with time t as the horizontal axis and the vehicle acceleration a data line as the vertical axis; (3) Align the O points of the above three coordinate systems, with the horizontal time t axis parallel to each other, the horizontal force F coordinate system at the top, the vertical weighing force P coordinate system in the middle, and the acceleration a coordinate system at the bottom, with the three vertical axes aligned up and down. (4) Establish the software and hardware design and programming of the three-in-one related coordinate system model and its synthesis program on the same vertical line; (5) Design and establish the calculation program and interface display program of the three coordinate system synthesis computer for the horizontal force F, vertical weighing force P and acceleration a against time t parameters; (6) Establish the inflection point of the tangent slope mutation of the acceleration a data curve segment, the inflection point of the broken line segment mutation, and the starting and ending points t1, t2, t3...t of various line segment changes. n The computer processing judgment program of the node time t is programmed, wherein the inflection point judgment standard of the sudden change of the tangent slope of the curve segment of the acceleration value a is: when ΔK1 / Δt≥C1, K1 is the slope of the tangent of the curve segment of the value a, t is time, C1 is the average absolute value of the rate of change of the tangent slope of the curve segment of the value a, which is a measurable comparative quantity in specific applications, the inflection point judgment standard of the broken line segment of the acceleration value a is: when ΔK2 / Δt≥C2, K2 is the slope of the broken line segment of the value a, t is time, C2 is the absolute value of the average gradual rate of change of the slope of the broken line segment of the value a, which is a measurable comparative quantity in specific applications, the starting and ending point judgment standard of the line segment of each a value is: when Δa / Δt>C3, a is the acceleration value, t is time, C3 is the average absolute value of the acceleration a data before and after the continuous gradual change that can be measured in the specific application, (7) establish the starting and ending time division points t1, t2, t3...t corresponding to the change of the acceleration a data value n , perform classification and segmentation collection and extraction of weighing measurement data line segments at the same time point on F and P data lines, calculate and process the line segments, and display, output and store the results of the software program programming, (8) according to the attached Figure 2 The program flow design enables the calculation and processing of the above processes to realize automatic calculation program programming of the whole process.

[0016] Attached Figure 1The virtual vertical dividing lines L1, L2, and L3 in the figure are used as examples to segment the measured F and P data lines using three dividing lines relative to the three representative points t1, t2, and t3. In practical applications, the computer program mainly collects the start and end node times t1, t2, t3...t when the acceleration a or speed V data of the vehicle actually changes in the weighing area. n , and its number is determined according to the change of the motion state of the vehicle. The program can be used to directly perform classification and segmented collection and extraction of weighing measurement data line segments at the same time point on the F and P data lines, and the collection, processing and calculation can be performed. In addition, the method of the present invention can also be represented by a power diagram of a coordinate system structure. Specifically, the horizontal axis is the common time t axis, and the vertical axes represent the values ​​and units of acceleration a, horizontal force F and vertical weighing force P respectively. Three different colors are used to distinguish the acceleration a, horizontal force F and vertical weighing force P data lines respectively. Except that the coordinate system program programming is changed from three coordinate systems to one, and the three data systems share one coordinate system, there is a difference, the rest of the computer program programming is basically the same. In addition, for the scale platform that belongs to the traditional one-dimensional structure with only one set of sensors in the vertical direction, there are only two sets of data lines of acceleration a and vertical weighing force P in the coordinate system.

[0017] According to the attached Figure 2 The program flow design represented is from the three signal acquisition access of the horizontal force F and vertical weighing force P sensor measurement of the two-dimensional structure axle weight scale and the detection of the vehicle acceleration a signal detector, to the A / D signal data converter, from the A / D signal data converter to the processor, from the discrimination processing of the start and end node time t of the acceleration a change, to the classification and segmented acquisition of the horizontal force F and vertical weighing force P data lines according to the corresponding time, to the processing program for extracting the data line segments, to the display, output and storage of the calculation results, and the standard hardware wiring connection of the overall computer system, so that the above-mentioned program programming software is matched with the hardware, and is repeatedly debugged, adjusted and improved, and finally the storage, display and output results are judged and accepted.

[0018] If the start and end node times t of the dynamic change of the vehicle speed V are used as dividing points to classify and segmentally collect and extract the F and P data line segments, it is only necessary to replace the data signal detection and collection input of the acceleration a with the data signal collection input of the speed V. The method of the present invention is also applicable to the traditional vehicle integral scale and axle weight scale with only one-dimensional vertical sensor structure, especially including portable axle weight scales. It is only necessary to use the start and end node times t of the change of acceleration a or speed V to classify and segmentally collect and extract the vertical weighing force P data line accordingly. The other implementation methods and program flows are the same. There are many programming methods and tools to implement the above program. Wolfram Mathematica and Excel are more suitable software and tools.

Claims

1. A method for classifying and segmenting vehicle weigh-in-motion sensor signals, characterized in that: With time t as a common parameter, the start and end node time t of the vehicle's acceleration a or speed V state change are used as dividing points, specifically, the start and end node time t when the vehicle's acceleration a is 0, that is, the vehicle is in uniform motion, the start and end node time t when the vehicle's acceleration a is a non-zero constant, that is, uniformly accelerated motion, and the start and end node time t when the vehicle's acceleration a is a variable, that is, non-uniformly accelerated motion. The signal of the vehicle's dynamic weighing sensor is classified and segmented according to the corresponding node time t to extract data line segments.

2. The method according to claim 1, characterized in that: The signal of the vehicle dynamic weighing sensor includes an induction signal and a digital signal after A / D conversion.

3. The method according to claim 1, characterized in that: The method is applicable to the weighing of vehicle axle weight scales with two-dimensional horizontal and vertical vehicle dynamic weighing sensor structures. The signals of the two-dimensional horizontal and vertical vehicle dynamic weighing sensors that collect the horizontal force F exerted by the wheels on the weighing platform and the vertical weighing force P are classified and segmented according to the corresponding node time t to extract data line segments.

4. The method according to claim 1, characterized in that: The method is applicable to the weighing of an integral vehicle weighing scale with a two-dimensional horizontal and vertical vehicle dynamic weighing sensor structure. The signals of the two-dimensional horizontal and vertical vehicle dynamic weighing sensors that collect the horizontal force F and the vertical weighing force P of the vehicle on the weighing platform are classified and segmented according to the corresponding node time t to extract data line segments.

5. The method according to claim 1, characterized in that: The method is applicable to the weighing of vehicle integral scales and axle weight scales with traditional one-dimensional vertical vehicle dynamic weighing sensor structures. The signal of the one-dimensional vertical vehicle dynamic weighing sensor that collects the vertical weighing force of the vehicle wheels on the scale body is classified and segmented according to the corresponding node time t to extract data line segments.

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