JPH11101683A - Method for measuring axle load of travel vehicle - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make the static load value of a traveling vehicle estimable precisely in a method for measuring the axle load of a traveling vehicle. SOLUTION: An axle load measuring apparatus 1 comprises an axle load detector 3 buried in the road face 30, a vehicle detector 4, which distinguishes vehicles 2 one by one, an operation processing part 5 to operation-process the signals from the axle load detector 3 and a vehicle detector 4, a printer 14, and an alarming displaying apparatus 15 and the fluctuating axle values of a driving vehicle 2 are measured a large number of times for every prescribed slight sampling time, and made to be fluctuating axle load value data series for every axle 40. The frequencies of the fluctuation components of the driving vehicle 2 are estimated by computing the fluctuating axle load value data series. Then, the frequency is computed to estimate the common phase. Further, the amplitude and the static axle value of fluctuating components of each axle 40 are estimated by using the frequencies and the common phase.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a method for measuring the axle load of a traveling vehicle.

[0002]

2. Description of the Related Art Conventionally, an axle load measuring device for a vehicle used on a highway or the like has sequentially measured each axle load of a running vehicle. Since the running vehicle is vibrating up and down, measuring each axle load means measuring a value in which the dynamic load is added to the axle load value at rest. The conventional axle load measuring device has no means for estimating the axle load value at rest according to the dynamic fluctuation amount.

[0003]

The length of the loading plate of the axle load measuring device is approximately 760 mm in the traveling direction of the vehicle.
In most cases, the distance between load transducers (load cells) is about 660 to 670 mm. The speed at which vehicles pass through toll gates
Assuming that the limit is about 20 km / h and the contact width of the tire is 250 mm, the time (measurement time) in which the tire is completely on the loading plate is about 0.09 seconds. Experience has shown that the frequency of the ground pressure fluctuation (frequency of the fluctuation component) applied to the road surface of the vehicle affecting the measurement is around 3 Hz. Therefore, if the waveform of the fluctuation is a sine wave, only about one third of one cycle can be measured. In the conventional axle load measuring device, the axle load value is estimated from the measurement result of only one axle load, so that it is impossible to estimate the stationary axle load value.

Accordingly, an object of the present invention is to solve the above-mentioned problems and to provide a method for measuring the axle load of a traveling vehicle, which can accurately estimate the static load value of the traveling vehicle.

[0005]

In order to achieve the above object, a method for measuring the axle load of a running vehicle according to the present invention is to measure a variable axle load value of a running vehicle a number of times at predetermined minute sampling times. Then, a variable axle weight value data sequence for each axle is calculated, the variable axle weight value data sequence is calculated to estimate the frequency of the fluctuating component of the running vehicle, and then the vehicle body is calculated based on the frequency. The common phase, which is the phase of the fluctuation component, is estimated, and further, using the frequency and the common phase, the amplitude of the fluctuation component of each axle and the target stationary axle weight value are estimated.

Further, the variable axle weight value of the running vehicle is measured many times at a predetermined minute sampling time to obtain a variable axle weight data sequence for each axle, and the variable axle weight data sequence is calculated. Estimating the frequency of the fluctuation component of the running vehicle, then estimating a common phase which is the phase of the fluctuation component of the vehicle body based on the frequency, and further calculating the common phase to calculate the fluctuation of each axle. The amplitude of the component is estimated, and thereafter, the amplitude is limited for an excessively large amplitude, and then the amplitude of the fluctuation component of each axle is estimated to estimate the stationary axle weight value of the vehicle.

Further, the variable axle weight value of the running vehicle is measured a large number of times at a predetermined minute sampling time to obtain a variable axle weight value data sequence for each axle. The frequency of the fluctuation component of the running vehicle is estimated, and then the frequency is calculated to estimate the phase and amplitude of the fluctuation component and the target stationary axle weight value for each axle.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below in detail based on the illustrated embodiments.

In FIG. 1, reference numeral 1 denotes an axle load measuring device, which is an axle load detector 3 embedded in a road surface 30.
A vehicle detector 4 for discriminating the vehicles 2 one by one, an axle load detector 3 and an arithmetic processing unit 5 for arithmetically processing signals from the vehicle detector 4, a printer 14, and a warning display 15. . The axle load detector 3 includes a load plate (not shown) that detects a load (axle load) received from the wheels 2a for each axle 40, and a load plate that receives the wheels 2a of the vehicle 2.

The arithmetic processing unit 5 receives an A / D converter 6 for receiving a signal from the axle load detector 3 and receives a signal from the A / D converter 6 and a signal from the vehicle detector 4 to determine the number of axles of the vehicle 2. Each of the axles 40 receives signals from the axle number detection means 7, the axle time detection means 8 for detecting the time between axles, the axle number detection means 7, the axle time detection means 8, and the AD converter 6. A load signal preprocessing means 9 for calculating the discrete load signal for each axle 40 to obtain a variable axle weight data string for each axle 40; and a variable axle weight data string calculated by the load signal preprocessing means 9 Frequency estimating means 10 for calculating the frequency of the axle load fluctuation by calculating
A common phase estimating means 11 for estimating a common phase of the vehicle body by calculating an estimated frequency and a variable axle weight value data sequence sent from the frequency estimating means 10, and an estimated common phase and an estimated frequency sent from the common phase estimating means 11 The amplitude / stationary axle weight value estimating means 12 for calculating the amplitude of the axle weight fluctuation and the static axle value by calculating the variable axle value data sequence using the And a post-processing means 13 for calculating a static load value from the weight value (by a calculation method such as a sum of static axle weight values) and determining whether the value exceeds an allowable weight value.

The post-processing means 13 of the arithmetic processing unit 5 includes a printer 14 for printing axle weight values, vehicle weight values, and the like, and a warning indicator for displaying a warning when the static load value exceeds an allowable weight value. 15 and a photographing device 16 for photographing the vehicle 2 exceeding the allowable weight value are electrically connected. The transmission processing means 17 may be electrically connected to the post-processing means 13 and the photographing device 16, and the central monitoring means 18 may be connected to the transmission processing means 17 via a connection line such as a communication line. If you do that,
Centralized management becomes possible.

By the way, the length of the load plate of the axle load measuring device is about 760 mm in the traveling direction of the vehicle 2, and the interval between load transducers (load cells) is almost 660 to 670 mm. The speed at which the vehicle 2 passes through the tollgate is limited to about 20 km / h, and assuming that the contact width of the tire is 250 mm, the time during which the tire is completely on the loading plate (measurement time) is 0.
It will be about 09 seconds. Experience has shown that the frequency of the ground pressure fluctuation (frequency of the fluctuation component) applied to the road surface 30 of the vehicle 2 that affects the measurement is around 3 Hz.
Therefore, if the waveform of the fluctuation is a sine wave, only about one third of one cycle can be measured.

The method for measuring axle weight of a running vehicle according to the present invention is a method for accurately estimating a stationary axle weight value (weight value at rest) from a variable axle weight data string having a variation component of less than one cycle. It is. That is, considering that the variation of the axle weight value of each axle is affected by the vibration of the rigid body, the change of each axle weight measured in a short time with one loading plate is captured for one vehicle. , By estimating the waveform (frequency, phase, amplitude) of the ground pressure applied to the road surface of one vehicle being measured,
This is for estimating the stationary axle weight value.

The method of measuring the axle load of the traveling vehicle will be described with reference to the block diagram of FIG. 1 and the flowchart of FIG. First, the vehicle detector 4 detects the vehicle 2 and the axle load detector 3 starts measuring the axle load value of the running vehicle 2. At this time, measurement is performed many times every predetermined minute sampling time. The load signal preprocessing means 9 extracts only data when the wheel 2a is completely mounted on the load plate of the axle load detector 3, and changes the variable axle load consisting of a large number of discrete axle load value data. Value data string. The number of axles is also counted. If necessary, signal noise is removed using filtering, smoothing, or the like.

Next, the frequency estimating means 10 estimates the frequency of the fluctuation component. To explain this in detail, the respective data of the variation axle load value data string from the load signal pre-processing means _{9, y m (k) m} = 1,2, ..., N k = 0,1,2 ... to. N is the number of axes, m is the axis number, and k is the sampling number for each axis. y _m (k) can be expressed as a sum of the fluctuation component f _m (k) and the stationary axle load value S _m (static component) as follows. y _m (k) = f _m (k) + S _m

Here, it is assumed that f _m (k) is a continuous vibration, f _m (k) is expressed by a constant coefficient difference equation, and its vibration component is estimated. The constant coefficient n-order difference equation of the output of the axle load detector on the m-th axis is expressed by the following equation 1.

[0017]

(Equation 1)

Since the static components S _i ≠ S _j and i ≠ j,
Excluding the influence of the difference, the following equation 2 is obtained.

[0019]

(Equation 2)

Then, parameters {a ₁ , a ₂ ,..., A _n } satisfying the following Expression 3 are applied by the linear least square method.

[0021]

(Equation 3)

According to the parameters {a ₁ , a ₂ ,..., A _n } obtained by the above-mentioned fitting, the fluctuation component f _m (k) of each axis is obtained.
The constant coefficient linear difference equation, which is a feature common to the above, is as shown in the following Expression 4.

[0023]

(Equation 4)

Further, (1-a ₁ · Z ^-1 -a ₂ · Z ^-2 -...- _ap · Z ^-n ) y (k)
= 0, and the characteristic equation of this difference equation is as follows: 1−a ₁ · Z ⁻¹ −a ₂ · Z ⁻² −...− _ap · Z ⁻ⁿ = 0.

The solution of the above-mentioned equation (4) is expressed by P _i , i
= 1,2, ..., when n, the _{(Z-P 1) (Z} -P 2) ... (Z-P n) = 0. Among these solutions, the solution located on the upper half plane of the z-plane is {P _i | P _i = a _i + jb _i , b _i > 0, _i } (1,2, ...,
n)｝, and the phase of this solution is regarded as a frequency component. That is, assuming that the sampling cycle (small sampling time) is T, {ω _i = {P _i / T} is regarded as the frequency of the vibration component of the vehicle body. That is, the frequency of {ω _i = {P _i / T} is calculated and estimated by the frequency estimating means 10 using the above-described calculation method.

The procedure for estimating the frequency of the fluctuation component of the vehicle 2 having three axles 40... Will be briefly described with reference to the graphs shown in FIGS. 3 and 4. As shown in FIG. 1
The graph line 19 indicating the variable axis weight value data sequence of the axis, the graph line 20 corresponding to the next second axis, and the graph line 21 corresponding to the third axis at the rear end are shown in the above-described formula (1). The constant / difference equation is applied to cancel the difference / offset and estimate the frequency as shown in FIG. In addition,
In FIG. 4, reference numeral 22 denotes a graph line of the fluctuation component of the first axis, 23 denotes a graph line of the fluctuation component of the second axis, and 24 denotes a graph line of the fluctuation component of the third axis.

Next, the common phase estimation means 11 estimates the common phase. Here, motion of the vehicle 2 during traveling, because it is in a fluctuation axle load value data string above, taking a common time axis of each vibration component omega _i phase [psi _i is common to each axle 40 Should be. First, an average value and a difference of the variable axle weight data sequence are calculated. Since the magnitude of the amplitude for each axle 40 is proportional to the weight of each axle, the magnitude of the amplitude is adjusted. In other words, to dividing the difference data string as mean S _'m of variation axle load value data string. Strictly speaking, S ′ _m ≠ S _m , but at this point, S _m is unknown. Therefore, considering S ′ _m ≒ S _m , the amplitudes are set to substantially the same height (magnitude). When it is expressed by a mathematical formula, the following mathematical formula 5 is obtained.
become that way.

[0028]

(Equation 5)

[0029] The regression equation of the equation 5 y _m ^d (k) and the following formula 6.

[0030]

(Equation 6)

In equation (6), the accuracy of fitting the regression equation is improved by adding a constraint equation so that S _min = 0. That is, a condition of V _min = S _min is added. However, V _min is a sufficiently small value, and may be set to 0. Then, the normal equation of Expression 6 is constructed, and {A _i , B _i }
Lead. Then, the phase ψ _i becomes ψ _i = tan ^-1 (B _i / A _i ).

The above is the description of the common phase estimation method using only bouncing without pitching. Pitching appears in the running vehicle 2. In order to take this into consideration, the phase ψ _i is estimated by a regression equation that considers pitching instead of Equation 6, considering the bouncing phase and the pitching phase in the equation for estimating the output of the vehicle detector 4 in Equation 6 above. . The regression equation is as follows:

[0033]

(Equation 7)

A normal equation (not shown) is constructed from Equation 7, and {A _i , B _i } and Equation 8 are derived from the normal equation. And the common phase ψ _i taking pitching into account
Is estimated. That is, the common phase ψ _i is calculated and estimated by the common phase estimating means 11 based on the above calculation method.

[0035]

(Equation 8)

The procedure for estimating the common phase of the fluctuation component of the vehicle 2 having three axles 40... Will be briefly described with reference to the graphs shown in FIGS. 4 and 5. As shown in FIG. The difference / offset of the column is canceled, and then, as shown in FIG. 5, the static component (the average value of the variable axle weight data column)
The common phase (phase common to each axis) is estimated by making the heights of the amplitudes substantially the same by restricting in (2). In FIG. 5, 25 is a graph line corresponding to the first axis, 26 is a graph line corresponding to the second axis, and 27 is a graph line corresponding to the third axis.

Next, in the amplitude / stationary axle weight value estimating means 12,
The amplitude of the fluctuation component of each axis is estimated. Up to this point, the frequency and the common phase have been estimated, and (ω _i , ψ _i ), i = 1,
Since 2,..., P are known, the following equation (15)
Is applied by the linear least squares method.

[0038]

(Equation 9)

Specifically, a normal equation (not shown) is constructed from the above equation 9, and the amplitude and the static component of each axle weight are estimated by the normal equation. In other words, the data of the frequency and the common phase sent from the frequency estimating means 10 are applied to the amplitude / stationary axle weight value estimating means 12 by using the linear least squares method with respect to Expression 9.

The procedure for estimating the common phase of the fluctuation component of the vehicle 2 having three axles 40... Will be briefly described with reference to the graph of FIG.
10 is a sine curve having the frequency ω estimated at 10 and the common phase ψ estimated by the common phase estimating means 11, and the first axis (graph line 19) and the second axis (graph line 20) and the static components of the amplitude and the axle load for each of the third axis (graph line 21) are estimated for each axle.

Thereafter, the post-processing means 13 calculates a static load value. That is, since the stationary axle load value S _m is obtained, static load value W is given by the following equation 10.

[0042]

[Equation 10]

The post-processing means 13 outputs the axle load value or the load value to a subsequent device.

As described above, according to the method for measuring the axle load of a running vehicle, the weight of the running vehicle 2 at rest (static load value) can be estimated with high accuracy. Therefore, it is possible to accurately determine the excess of the vehicle weight at a tollgate or the like on an expressway. Further, there is an advantage that a conventionally used component (axle load detector 3) such as a load plate or a load cell for detecting an axle load can be used as it is.

The axle load measurement method described with reference to FIGS. 1 to 6 may not be able to accurately measure the axle load value.

In order to cope with this, once the amplitude of the fluctuation component of each axle 40 represented by Expression 9 is estimated, the amplitude is limited for an excessive amplitude, and then the amplitude of the fluctuation component of each axle 40 is determined. And the stationary axle weight value of the vehicle 2 is estimated.

For example, when the amplitude of the third axis is excessive, the average value S ′ _m obtained by the average value method is used as a substitute for the static component on the basis of the amplitude of the second axis that should take the maximum amplitude.
Is used to add the restriction formula A ₃ = A ₂ · S ′ ₃ / S ′ ₂ to the normal equation to limit the amplitude, and then estimate the amplitude again to estimate the stationary axle weight value. .

When pitching is remarkable, equation 9
In the following equation 11 which is a form of the previous stage of the synthesis of the following equation, A ₃ = A ₂ .S ' ₃ / S' ₂ B ₃ = B ₂ .S ' ₂ / S' ₃ is added to the normal equation, and Re-estimation may be performed. Where A _i is the bouncing amplitude and B _i
Is the pitching amplitude.

[0049]

[Equation 11]

Further, even if the amplitude is limited due to unexpected behavior of the vehicle, the stationary axle weight value may not be reliable. Therefore, in estimating the stationary axle value, the average value S of the variable axle value data sequence is used. It is also preferable to substitute ' _m as it is as a safety measure.

More specifically, if the stationary axle weight obtained along with the estimation of the amplitude satisfies (static axle weight-average value) / average value ≧ R, the average value is adopted as the estimated axle weight value. I just need. Here, R is a constant, for example, R = 0.25
Although it is preferable to set it as a numerical value, a numerical value other than that may be good in some cases.

Next, another embodiment of the method for measuring the axle load of a traveling vehicle according to the present invention will be described. In this case, FIG.
As shown in the flowchart of the first, first create a variable axle weight data string, then estimate the frequency of the variable component,
Next, the frequency is calculated to estimate the phase and amplitude of the fluctuation component and the stationary axle weight value for each axle 40.

In this axle load measuring method, the creation of the fluctuating axle load value data sequence and the estimation of the frequency of the fluctuating component are performed in the same manner as the method described with reference to FIGS. The method of estimating the phase and amplitude of the fluctuation component for each axle 40 will now be described. Assuming that it is already known that the fluctuation component has p frequency components, the estimated value of the output of the axlemeter is assumed. y ′ _m (k)
Is expressed as the following Expression 12 by p sine waves.

[0054]

(Equation 12)

Using the least-squares method, the parameters {A _i , B _i , S _m }, i
= 1, 2,..., P. S _m is a static component (static axle weight value) of the m-th axis. That is, the phase and amplitude of the fluctuation component and the stationary axle weight value are simultaneously estimated for each axis by fitting.

[0056]

(Equation 13)

According to this measuring method, there is no need to consider the relationship between pitching and bouncing of the traveling vehicle, and the calculation can be simplified.

According to the present invention, the present invention can be applied to cases other than the case where the number of axles is three. The number of axles is not limited to two, four and five, but is also an integer of six or more. Can also be applied.

[0059]

The present invention has the following remarkable effects by the above-mentioned structure.

According to the method for measuring the axle load of a traveling vehicle according to the first aspect, the weight of the traveling vehicle 2 at rest (static load value).
Can be estimated with high accuracy. Therefore, it is possible to accurately determine whether the vehicle weight is excessive or the like at a tollgate on an expressway. Also, there is an advantage that a conventionally used component such as a load plate or a load cell for detecting the axle load can be used as it is. Further, the static load value in consideration of the relationship between pitching and bouncing can be estimated.

According to the method for measuring the axle load of a traveling vehicle, the static load value of the traveling vehicle 2 can be estimated with higher accuracy. Therefore, it is possible to more accurately determine whether the vehicle weight is excessive or the like.

According to the method for measuring the axle load of a traveling vehicle according to the third aspect, the weight of the traveling vehicle 2 at rest (static load value).
Can be estimated with high accuracy. Therefore, it is possible to accurately determine whether the vehicle weight is excessive or the like at a tollgate on an expressway. Also, there is an advantage that a conventionally used component such as a load plate or a load cell for detecting the axle load can be used as it is. Further, there is no need to consider the relationship between pitching and bouncing, and the calculation can be simplified.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating an axle load measuring device and devices connected thereto.

FIG. 2 is a flowchart of an embodiment of a method for measuring axle load of a traveling vehicle according to the present invention.

FIG. 3 is a graph illustrating a variable axle weight data string of a three-axis vehicle.

FIG. 4 is a graph illustrating a frequency estimating method.

FIG. 5 is a graph illustrating a method for estimating a common phase.

FIG. 6 is a graph illustrating an amplitude estimation method.

FIG. 7 is a flowchart of another embodiment of the method for measuring the axle load of a traveling vehicle according to the present invention.

[Explanation of symbols]

 2 vehicles 40 axles

Claims (3)

[Claims] 1. A variable axle weight value of a running vehicle 2 is measured a large number of times at a predetermined minute sampling time to obtain a variable axle weight data sequence for each axle 40, and the variable axle weight data sequence is calculated. To estimate the frequency of the fluctuation component of the vehicle 2 traveling, and then estimate the common phase which is the phase of the fluctuation component of the vehicle body based on the frequency, and further use the frequency and the common phase to estimate the common phase. A method for measuring the axle load of a traveling vehicle, comprising estimating an amplitude of a fluctuation component of each axle 40 and a stationary axle load value. 2. A fluctuating axle weight value of a running vehicle 2 is measured a large number of times at a predetermined minute sampling time to obtain a fluctuating axle weight data string for each axle 40, and the fluctuating axle weight data string is calculated. To estimate the frequency of the fluctuation component of the vehicle 2 running, then estimate the common phase which is the phase of the fluctuation component of the vehicle body based on the frequency, and further calculate the common phase to calculate the common phase. Estimating the amplitude of the fluctuation component of the axle 40, thereafter performing amplitude limitation on the excessive amplitude, and then estimating the amplitude of the fluctuation component of each axle 40 to estimate the stationary axle weight value of the vehicle 2 A method for measuring the axle load of a traveling vehicle, comprising: 3. A variable axle weight data sequence for each axle 40 is calculated by measuring a variable axle weight value of the running vehicle 2 many times at predetermined minute sampling times, and the variable axle weight data sequence is calculated. And estimating the frequency of the fluctuating component of the running vehicle 2 and then calculating the frequency to estimate the phase and amplitude of the fluctuating component and the stationary axle weight value for each axle 40. A method for measuring the axle load of a running vehicle.