JP7571526B2 - Axle load measurement device, axle load sensor deterioration estimation method, and axle load sensor deterioration estimation program - Google Patents

Description

This invention relates to a technology for estimating the deterioration of an axle load sensor that measures the axle load of a moving vehicle.

Conventionally, there has been a device that measures the weight of a vehicle traveling on a road. This device processes the measurement signals of multiple (two or more) axle load sensors that are lined up in the direction of vehicle travel and buried in the road to measure the weight of the traveling vehicle (see Patent Documents 1 and 2, etc.). The axle load sensor is a sensor used for each axle of the vehicle to measure the vertical force (axle load) when the wheels attached to that axle pass by.

The axle load is calculated by processing the measurement signals of multiple axle load sensors buried and aligned in the direction of vehicle travel. For example, for each axle, the average value of the axle loads measured by multiple axle load sensors is calculated as the axle load of that axle. In addition, the sum (total) of the axle loads calculated for the vehicle is calculated as the vehicle weight.

In addition, in Patent Documents 1 and 2, axle load sensors with inappropriate measurement accuracy (axle load sensors with degraded measurement accuracy) are detected by comparing measurement signals between axle load sensors.

JP 2020-91205 A JP 2020-91206 A

However, the configurations described in Patent Documents 1 and 2 detect axle load sensors with degraded measurement accuracy by comparing measurement signals between axle load sensors. Therefore, if the degree of degradation in measurement accuracy between axle load sensors is the same, it may not be possible to detect an axle load sensor with degraded measurement accuracy.

The objective of this invention is to provide technology that can detect an axle load sensor whose measurement accuracy has deteriorated without being affected by the degree of deterioration in the measurement accuracy of other axle load sensors.

The axle load measuring device of this invention is configured as follows to achieve the above objective.

The axle load sensor connection unit receives measurement signals from multiple axle load sensors arranged in a row in the vehicle's travel direction. The axle load calculation unit calculates the axle load based on the measurement signals input from the multiple axle load sensors. The deterioration estimation unit estimates deterioration for each axle load sensor based on the waveform of the input measurement signal.

In this configuration, the deterioration of an axle load sensor is estimated based on the waveform of the measurement signal input from that axle load sensor. In other words, the deterioration of an axle load sensor can be estimated without being affected by the degree of deterioration in the measurement accuracy of other axle load sensors. In other words, an axle load sensor with degraded measurement accuracy can be detected without being affected by the degree of deterioration in the measurement accuracy of other axle load sensors.

For example, the deterioration estimation unit may use the timing when the measurement signal of the axle load sensor reaches its peak as the reference timing, and estimate the deterioration by comparing the waveform of the measurement signal before and after this reference timing. The rotational speed of the wheel when passing by the axle load sensor (the passing speed of the wheel) is approximately constant. For this reason, if the axle load sensor has appropriate measurement accuracy, the waveform of the measurement signal when the wheel passes will be approximately symmetrical before and after the timing when it reaches its peak (reference timing). Therefore, the deterioration estimation unit may calculate the similarity between the symmetric waveform of the measurement signal until the reference timing is reached (waveform inverted around the reference timing) and the waveform of the measurement signal after the reference timing is reached, and estimate the degree of deterioration of the measurement accuracy based on the magnitude of this similarity.

The degradation estimation unit may calculate the similarity between the waveform of the measurement signal before the reference timing is reached and the symmetric waveform of the measurement signal after the reference timing is reached, and estimate the degree of degradation of the measurement accuracy based on the magnitude of the similarity.

For example, the deterioration estimation unit may also be configured to estimate deterioration based on whether the lower limit value of the measurement signal of the axle load sensor after the reference timing is equal to or lower than the lower limit threshold.

For example, the deterioration estimation unit may also be configured to estimate deterioration based on whether or not there is an inflection point in the waveform of the measurement signal of the axle load sensor before the reference timing.

For example, the deterioration estimation unit may also be configured to estimate deterioration based on the magnitude of the amplitude of the vibration waveform of the measurement signal of the axle load sensor after the reference timing.

Furthermore, the deterioration estimation unit may be configured to estimate deterioration based on whether the magnitude of the measurement value indicated by the measurement signal when no vehicle has passed for a certain period of time and the measurement signal of the axle load sensor is stable is within an appropriate range.

This invention makes it possible to detect axle load sensors whose measurement accuracy has deteriorated without being affected by the degree of deterioration in the measurement accuracy of other axle load sensors.

1 is a schematic diagram showing a vehicle weight measurement system to which an axle load measurement device according to this embodiment is applied. FIG. 2 is a block diagram showing the configuration of the main parts of the axle load measuring device according to this example. FIG. 4 is a diagram showing a measurement signal of a wheel load sensor. 13 is a flowchart showing a measurement process. 5A to 5C are diagrams showing changes in the measurement signal of a wheel load sensor whose measurement accuracy has deteriorated. 6A to 6C are diagrams showing changes in the measurement signal of a wheel load sensor whose measurement accuracy has deteriorated. 13 is a flowchart showing a deterioration estimation process.

The following describes an embodiment of the invention.

＜1. Application examples＞
Fig. 1 is a schematic diagram showing a vehicle weight measurement system to which an axle load measurement device according to this embodiment is applied. The vehicle weight measurement system shown in Fig. 1 includes an axle load measurement device 1, three axle load sensors 2 to 4, and two vehicle detection sensors 6 and 7. The axle load sensors 2 to 4 and the vehicle detection sensors 6 and 7 are connected to the axle load measurement device 1.

In this example, as shown in FIG. 1, vehicle detection sensor 6, axle load sensor 2, axle load sensor 3, axle load sensor 4, and vehicle detection sensor 7 are arranged (buried) in this order on the road in the direction of travel of vehicle 100. The measurement section for measuring the axle load of vehicle 100 is the section from vehicle detection sensor 6 to vehicle detection sensor 7. Vehicle detection sensor 6 detects vehicles 100 entering the measurement section. Vehicle detection sensor 7 detects vehicles 100 exiting the measurement section.

In this example, the axle load sensor 2 is a pair of wheel load sensors 2R, 2L arranged in the vehicle width direction of the vehicle 100 traveling on the road. Similarly, the axle load sensor 3 is a pair of wheel load sensors 3R, 3L arranged in the vehicle width direction of the vehicle 100 traveling on the road, and the axle load sensor 4 is a pair of wheel load sensors 4R, 4L arranged in the vehicle width direction of the vehicle 100 traveling on the road. The wheel load sensors 2R to 4R are embedded in positions where the right wheels of the vehicle 100 traveling on the measurement section pass. The wheel load sensors 2L to 4L are embedded in positions where the left wheels of the vehicle 100 traveling on the measurement section pass.

The wheel load sensors 2R-4R, 2L-4L are, for example, piezoelectric sensors, and output a measurement signal corresponding to the pressing force when the wheels pass to the axle load measuring device 1. The vehicle detection sensors 6, 7 are, for example, loop coil sensors, and output a change in inductance to the axle load measuring device 1 as a vehicle detection signal (a signal indicating the presence or absence of a vehicle 100).

The vehicle detection sensors 6, 7 may be optical sensors or radio wave sensors that are not buried in the road. The axle load sensors 2-4 may be integrated pairs of wheel load sensors 2R-4R, 2L-4L (the axle load sensors 2-4 may be configured to measure the axle load without measuring the wheel load).

The wheel load sensors 2R to 4R output a measurement signal measuring the wheel load of the right wheel for each axle of the vehicle 100 that has traveled through the measurement section to the axle load measurement device 1. In addition, the wheel load sensors 2L to 4L output a measurement signal measuring the wheel load of the left wheel for each axle of the vehicle 100 that has traveled through the measurement section to the axle load measurement device 1. That is, the wheel load measurement signal by the wheel load sensor 2R, the wheel load measurement signal by the wheel load sensor 3R, and the wheel load measurement signal by the wheel load sensor 4R for the right wheel for each axle of the vehicle 100 that has traveled through the measurement section are input to the axle load measurement device 1. In addition, the wheel load measurement signal by the wheel load sensor 2L, the wheel load measurement signal by the wheel load sensor 3L, and the wheel load measurement signal by the wheel load sensor 4L for the left wheel for each axle of the vehicle 100 that has traveled through the measurement section are input to the axle load measurement device 1.

In the traveling direction of the vehicle 100, the distance L1 between the axle load sensor 2 and the axle load sensor 3 and the distance L2 between the axle load sensor 3 and the axle load sensor 4 are different lengths. The traveling vehicle 100 vibrates due to the complex interaction of various factors such as road surface unevenness, speed, and tire air pressure. If both the distance L1 between the adjacent axle load sensor 2 and the axle load sensor 3 and the distance L2 between the adjacent axle load sensor 3 and the axle load sensor 4 are close to an integer multiple of the vibration wavelength of the vehicle 100, the measurement error of the axle load may become large. For this reason, in this example, even if one of the distance L1 between the adjacent axle load sensor 2 and the axle load sensor 3 or the distance L2 between the adjacent axle load sensor 3 and the axle load sensor 4 is close to an integer multiple of the vibration wavelength of the vehicle 100, the distance L1 and the distance L2 are made different lengths so that the other does not approximate an integer multiple of the vibration wavelength of the vehicle 100.

The axle load measuring device 1 in this example samples the input measurement signal for each wheel load sensor 2R-4R, 2L-4L at a predetermined sampling period and cumulatively stores the acquired measurement values. The sampling period is set to a length that allows acquisition of the waveform of the measurement signal when a wheel passes the wheel load sensors 2R-4R, 2L-4L. The wheel load sensors 2R-4R, 2L-4L output measurement signals at all times, not just when the wheels of the vehicle 100 pass by.

In this example, the axle load measuring device 1 calculates the wheel load of the passing wheel for each of the wheel load sensors 2R-4R and 2L-4L based on the peak value of the measurement signal when the wheel passes.

In this example, the axle load measuring device 1 calculates the sum of the axle loads calculated for each axle of the vehicle 100 as the weight (vehicle weight) of the vehicle 100. The axle load of each axle of the vehicle 100 is the average value of the axle loads (here called individual axle loads) calculated for that axle by each axle load sensor 2 to 4. The individual axle load is the sum of the wheel loads calculated for the left and right wheels attached to the same axle.

As is clear from the above explanation, the axle weight measurement device 1 can also calculate the weight (vehicle weight) of the vehicle 100 without calculating the axle weight, depending on the calculation formula.

The axle load measuring device 1 in this example also estimates the degree of deterioration in the measurement accuracy for each wheel load sensor 2R-4R, 2L-4L based on the waveform of the measurement signal input from that wheel load sensor 2R-4R, 2L-4L. Therefore, it is possible to detect an axle load sensor 2-4 whose measurement accuracy has deteriorated, without being affected by the degree of deterioration in the measurement accuracy of the other axle load sensors 2-4.

In this example, when the measurement accuracy of the axle load sensors 2-4 is degraded, it means that the measurement accuracy of at least one of the wheel load sensors 2R-4R, 2L-4L that make up the axle load sensors 2-4 is degraded.

2. Configuration example
2 is a block diagram showing the configuration of the main parts of the axle load measurement device 1 according to this example. The axle load measurement device 1 according to this example includes a control unit 11, an axle load sensor connection unit 12, a loop coil sensor connection unit 13, an observation database 14 (observation DB 14), and an output unit 15.

The control unit 11 controls the operation of each part of the main body of the axle load measurement device 1 in this example. The control unit 11 also has a measurement value arrangement section 21, a wheel load calculation section 22, an axle load calculation section 23, a vehicle weight calculation section 24, and a deterioration estimation section 25. Details of the measurement value arrangement section 21, the wheel load calculation section 22, the axle load calculation section 23, the vehicle weight calculation section 24, and the deterioration estimation section 25 of the control unit 11 will be described later.

The measurement signals of the connected axle load sensors 2-4 are input to the axle load sensor connection unit 12. Specifically, wheel load sensors 2R-4R and 2L-4L are connected to the axle load sensor connection unit 12, and the measurement signals of the wheel load sensors 2R-4R and 2L-4L are input to the axle load sensor connection unit 12. The axle load sensor connection unit 12 samples the input measurement signals for each of the wheel load sensors 2R-4R and 2L-4L at a predetermined sampling period, and outputs the acquired measurement values (digital values) to the control unit 11.

The measurement signals of the wheel load sensors 2R-4R and 2L-4L when the wheels pass change, for example, as shown in FIG. 3. In FIG. 3, timing t1 is the timing when the tire starts to press the wheel load sensors 2R-4R and 2L-4L, and timing t3 is the timing when the tire stops pressing the wheel load sensors 2R-4R and 2L-4L. Also, in FIG. 3, timing t2 is the timing when the tire pressure reaches its maximum (peak). When the measurement signals of the wheel load sensors 2R-4R and 2L-4L are at their peak, the wheels are riding on the wheel load sensors 2R-4R and 2L-4L (the wheels are barely touching the road surface). The sampling period for the axle load sensor connection unit 12 to sample the measurement signals of the wheel load sensors 2R-4R and 2L-4L is set to the time when the waveform shown in FIG. 3 is obtained from the measurement values.

The vehicle detection sensors 6 and 7 are connected to the loop coil sensor connection section 13. The loop coil sensor connection section 13 detects changes in inductance for each of the vehicle detection sensors 6 and 7, and outputs a vehicle detection signal indicating the presence or absence of a vehicle 100 to the control unit 11.

In the observation DB 14, the measurement values acquired by the axle load sensor connection unit 12 for each of the wheel load sensors 2R-4R and 2L-4L are stored in chronological order. The measurement values of the wheel load sensors 2R-4R and 2L-4L are associated with the measurement time. Data related to the measurement values of the wheel load sensors 2R-4R and 2L-4L are referred to here as measurement value data.

In addition, the observation DB 14 stores the time of entry into and the time of exit from the measured section for each vehicle 100 that traveled through the measured section. The time of entry into the measured section is the time when the vehicle detection signal from the vehicle detection sensor 6 changes from a state in which the vehicle 100 is not detected to a state in which the vehicle 100 is detected. The time of exit from the measured section is the time when the vehicle detection signal from the vehicle detection sensor 7 changes from a state in which the vehicle 100 is detected to a state in which the vehicle 100 is not detected. Data relating to the time of entry/exit of the vehicle 100 into/from the measured section is referred to here as vehicle detection data.

The observation data referred to here includes measurement data and vehicle detection data.

The observation DB14 may be, for example, a hard disk drive (HDD), a solid state drive (SSD), or other storage medium.

The output unit 15 outputs the result of judging whether the measurement accuracy of the axle load sensors 2 to 4 is appropriate, and the axle load, vehicle weight, etc. calculated for the vehicle 100 that has traveled the measurement section to a higher-level device (not shown) as necessary.

Next, we will explain the measurement value arrangement unit 21, wheel load calculation unit 22, axle load calculation unit 23, vehicle weight calculation unit 24, and deterioration estimation unit 25 that the control unit 11 has.

The measurement value arrangement unit 21 arranges the measurement values acquired by the axle load sensor connection unit 12 for each of the wheel load sensors 2R-4R and 2L-4L in chronological order and stores them in the observation DB 14. In addition, the measurement value arrangement unit 21 associates the entry time of the vehicle 100 into the measurement section acquired from the vehicle detection signal by the vehicle detection sensor 6 and the exit time of the vehicle 100 from the measurement section acquired from the vehicle detection signal by the vehicle detection sensor 7 for each vehicle 100 that has traveled through the measurement section, and stores them in the observation DB 14.

The wheel load calculation unit 22 calculates the wheel load of each wheel based on the measurement signal when the wheel passes each of the wheel load sensors 2R to 4R and 2L to 4L. For example, when calculating the wheel load of each wheel based on the peak value α of the measurement signal measured by the wheel load sensors 2R to 4R and 2L to 4L,
Wheel load = f(α)
f(α) is a predetermined function with α as a variable.

The wheel load may be calculated based on the area of the waveform of the measurement signal measured by the wheel load sensors 2R to 4R and 2L to 4L, or may be calculated using other methods.

The axle load calculation unit 23 calculates the axle load for each axle of the vehicle 100. The axle load for each axle is the average value of the individual axle loads calculated for that axle by each of the axle load sensors 2 to 4. The individual axle load is the sum of the wheel loads of the right and left wheels attached to the same axle.

The vehicle weight calculation unit 24 calculates the sum of the axle weights calculated for each axle of the vehicle 100 as the vehicle weight of the vehicle 100.

The deterioration estimation unit 25 estimates the degree of deterioration in measurement accuracy for each wheel load sensor 2R-4R, 2L-4L based on the waveform of the measurement signal input from that wheel load sensor 2R-4R, 2L-4L.

In addition, FIG. 2 shows an example of calculating the wheel load, axle load, and vehicle weight using the measurement value data stored in the observation DB 14 and the vehicle detection data. The axle load measuring device 1 may be configured to temporarily store in memory the measurement values input from the axle load sensor connection unit 12 during the period from when the vehicle 100 enters the measurement section until it leaves, and to calculate the wheel load, axle load, and vehicle weight using the measurement values stored in this memory.

The control unit 11 of the axle load measurement device 1 is composed of a hardware CPU, memory, and other electronic circuits. When the hardware CPU executes the axle load sensor deterioration estimation program of the present invention, it operates as a measurement value arrangement section 21, a wheel load calculation section 22, an axle load calculation section 23, a vehicle weight calculation section 24, and a deterioration estimation section 25. The memory also has an area for expanding the axle load sensor deterioration estimation program of the present invention, and an area for temporarily storing data generated during execution of the axle load sensor deterioration estimation program. The control unit 11 may be an LSI that integrates the hardware CPU, memory, and the like. The hardware CPU is also a computer that executes the axle load sensor deterioration estimation method of the present invention.

<3. Operation example>
The operation of the axle load measurement device of this embodiment will be described below. The axle load measurement device 1 of this embodiment executes an observation data collection process, a measurement process, and a deterioration estimation process.

The observation data collection process is a process of recording observation data (measurement value data and vehicle detection data) in the observation DB 14. As described above, the axle load sensor connection unit 12 outputs to the control unit 11 the measurement values obtained by sampling the input measurement signals at the sampling period for each of the wheel load sensors 2R-4R and 2L-4L. The measurement value arrangement unit 21 arranges the measurement values output by the axle load sensor connection unit 12 for each of the wheel load sensors 2R-4R and 2L-4L in chronological order and stores them in the observation DB 14.

The loop coil sensor connection unit 13 also outputs a vehicle detection signal to the control unit 11 for each vehicle detection sensor 6, 7. The measurement value arrangement unit 21 stores in the observation DB 14 the time when the vehicle 100 entered the measurement section and the time when the vehicle 100 exited the measurement section for each vehicle 100 that traveled through the measurement section in association with each other. The measurement value arrangement unit 21 detects the timing when the vehicle detection signal of the vehicle detection sensor 6 changes from a state where the vehicle 100 is not detected to a state where the vehicle 100 is detected as the time when the vehicle 100 entered the measurement section. The measurement value arrangement unit 21 also detects the timing when the vehicle detection signal of the vehicle detection sensor 7 changes from a state where the vehicle 100 is detected to a state where the vehicle 100 is not detected as the time when the vehicle 100 exited the measurement section.

In this example, the axle load measuring device 1 continuously executes this observation data collection process while performing the measurement process described below.

Next, the measurement process will be described. This measurement process is a process for calculating the axle load and vehicle weight of the vehicle 100 that has traveled through the measurement section. Figure 4 is a flowchart showing this measurement process. The axle load measurement device 1 waits for the vehicle 100 to enter the measurement section and then exit the measurement section (s1, s2). At s1 and s2, it is detected that the vehicle 100 has traveled through the measurement section.

The wheel load calculation unit 22 calculates the wheel load of the passing wheel for each of the wheel load sensors 2R-4R and 2L-4L (s3). The right wheel attached to each axle of the vehicle 100 passes through the wheel load sensors 2R-4R. The left wheel attached to each axle of the vehicle 100 passes through the wheel load sensors 2L-4L. When the vehicle 100 travels through the measurement section, the measurement signals of the wheel load sensors 2R-4R and 2L-4L are arranged in the time axis direction with the same number of waveforms (waveforms shown in Figure 3) as the number of axles of the vehicle 100.

The wheel load calculation unit 22 calculates the wheel load for each waveform of the measurement signal from the wheel load sensors 2R-4R and 2L-4L based on the peak value of the waveform, the area of the waveform, etc. The correspondence between the axles between the wheel load sensors 2R-4R and 2L-4L can be determined by the order in which the waveforms appear.

The axle load calculation unit 23 calculates the individual axle load for each axle of the vehicle 100 that has traveled through the measurement section (s4). For each axle load sensor 2-4, the axle load calculation unit 23 calculates the sum of the wheel loads of the same axle calculated in s3 as the individual axle load. The axle load calculation unit 23 calculates the average of the individual axle loads calculated in s4 as the axle load for each axle of the vehicle 100 that has traveled through the measurement section (s5).

The vehicle weight calculation unit 24 calculates the vehicle weight as the sum of the axle weights of the vehicle 100 that traveled through the measurement section calculated in s5 (s6).

The axle weight measurement device 1 outputs the axle weight calculated in s5 and the vehicle weight calculated in s6, etc. to the higher-level device in the output section 15 (s7), and returns to s1.

The axle load measuring device 1 may also use the wheel load calculated in s3 to determine whether the weight balance of the vehicle 100 in the vehicle width direction is appropriate, and output the determination result to a higher-level device.

Next, the deterioration estimation process will be described. This deterioration estimation process is a process for estimating the degree of deterioration in measurement accuracy for each of the wheel load sensors 2R-4R and 2L-4L. The axle load measurement device 1 executes this deterioration estimation process at a predetermined timing. For example, the axle load measurement device 1 may be scheduled to start the deterioration estimation process at midnight every day, or at midnight every Sunday, or may be set to start at other timing. The axle load measurement device 1 may also be configured to start this deterioration estimation process in response to an input operation by an operator, etc.

When the measurement accuracy of wheel load sensors 2R-4R and 2L-4L is appropriate, the waveform of the measurement signal when a wheel of vehicle 100 passes by has a shape that is approximately symmetrical around the peak, as shown in Figure 3. On the other hand, when the measurement accuracy of wheel load sensors 2R-4R and 2L-4L deteriorates, the waveform of the measurement signal when a wheel of vehicle 100 passes by will have a shape shown in Figures 5(A)-(C), 6(A)-(C), etc., depending on the degree of deterioration. In Figures 5(A)-(C) and 6(A)-(C), the areas where the waveform of the measurement signal has deformed due to deterioration of measurement accuracy are surrounded by dashed lines.

Note that Figures 5(A)-(C) and 6(A)-(C) only show examples of waveforms of measurement signals from wheel load sensors 2R-4R and 2L-4L whose measurement accuracy has deteriorated. The waveforms of measurement signals from wheel load sensors 2R-4R and 2L-4L whose measurement accuracy has deteriorated are not limited to those shown in Figures 5(A)-(C) and 6(A)-(C).

Figure 7 is a flowchart showing the deterioration estimation process. In this example, the deterioration estimation unit 25 determines the wheel load sensors 2R-4R and 2L-4L for which the deterioration of measurement accuracy is to be estimated (s11). The deterioration estimation unit 25 acquires the waveform of the measurement signal at the most recent wheel pass for the wheel load sensors 2R-4R and 2L-4L determined in s11 (s12).

As described above, the observation DB 14 records the measurement values for each wheel load sensor 2R-4R, 2L-4L at a sampling period that allows acquisition of the waveform of the measurement signal when the wheel passes. The deterioration estimation unit 25 estimates the degree of deterioration in the measurement accuracy for the target wheel load sensors 2R-4R, 2L-4L determined in s11 based on the waveform acquired in s12 (s13). The process related to s13 will be described later.

If there are unprocessed wheel load sensors 2R-4R, 2L-4L (s14), the deterioration estimation unit 25 returns to s11. If there are no unprocessed wheel load sensors 2R-4R, 2L-4L, the deterioration estimation unit 25 outputs the estimated degree of deterioration of the measurement accuracy for each of the wheel load sensors 2R-4R, 2L-4L to the higher-level device (s15), and ends this process.

Here, we explain the process of estimating the degree of deterioration in measurement accuracy in step s13.

Estimation process 1
The deterioration estimation unit 25 detects a peak in the waveform of the measurement signal acquired in s12. The deterioration estimation unit 25 calculates the similarity between the waveform obtained by inverting the waveform before the detected peak in the time axis direction and the waveform after the detected peak. The deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy based on the calculated similarity. At this time, the deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy to be smaller as the calculated similarity is larger.

This estimation process makes it possible to estimate the degree of deterioration in the measurement accuracy of wheel load sensors 2R-4R and 2L-4L when the measurement signals have waveforms, for example, as shown in Figures 5(A)-(C) and 6(A)-(C).

The deterioration estimation unit 25 may be configured to calculate the similarity between a waveform obtained by inverting the waveform after the detected peak along the time axis and the waveform before the detected peak.

Estimation process 2
The deterioration estimation unit 25 obtains the minimum value of the measurement value after the wheel passes in the waveform of the measurement signal obtained in s12. The deterioration estimation unit 25 also obtains the average value of the measurement value for a predetermined time (about 1 second) before the wheel passes in the waveform of the measurement signal obtained in s12. The deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy based on the absolute value of the difference between the minimum value after the wheel passes and the average value before the wheel passes. At this time, the deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy to be smaller the smaller the calculated absolute value is.

This estimation process makes it possible to estimate the degree of deterioration in the measurement accuracy of wheel load sensors 2R-4R and 2L-4L when the measurement signals have waveforms, for example, as shown in Figures 5(B) and (C).

Estimation process 3
As in the above-described estimation process 2, the deterioration estimation unit 25 acquires the minimum value of the measurement value after the wheel passes in the waveform of the measurement signal acquired in s12. The deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy based on the acquired minimum value. At this time, the deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy to be greater as the acquired minimum value is smaller.

Estimation process 4
The deterioration estimation unit 25 detects whether there is an inflection point of the measurement value in the period until the measurement value reaches a peak in the waveform of the measurement signal acquired in s12. If there is an inflection point, the deterioration estimation unit 25 calculates the absolute value of the difference between the maximum value and the minimum value at the inflection point. The deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy based on the absolute value of the difference between the maximum value and the minimum value at the inflection point. At this time, the deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy to be greater the larger the calculated absolute value.

This estimation process makes it possible to estimate the degree of deterioration in the measurement accuracy of wheel load sensors 2R-4R and 2L-4L when the measurement signals have waveforms, for example, as shown in Figures 6(A) and (C).

Estimation process 5
The deterioration estimation unit 25 detects whether there is an inflection point of the measurement value in the period after the measurement value reaches a peak in the waveform of the measurement signal acquired in s12. If there is an inflection point, the deterioration estimation unit 25 calculates the absolute value of the difference between the maximum value and the minimum value at the inflection point. The deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy based on the absolute value of the difference between the maximum value and the minimum value at the inflection point. At this time, the deterioration estimation unit 25 estimates the degree of deterioration of the measurement accuracy to be greater the larger the calculated absolute value.

This estimation process makes it possible to estimate the degree of deterioration in the measurement accuracy of wheel load sensors 2R-4R and 2L-4L when the measurement signals have waveforms, for example, as shown in Figures 6(B) and (C).

Estimation process 6
The deterioration estimation unit 25 detects whether or not there is a vibration waveform exceeding a predetermined amplitude in the waveform of the measurement signal acquired in s12 after the wheel passes. If there is a vibration waveform exceeding a predetermined amplitude after the wheel passes, the deterioration estimation unit 25 detects the amplitude, number, and time during which the vibration waveform occurred of the vibration waveform, and estimates the degree of deterioration of the measurement accuracy based on these. At this time, the deterioration estimation unit 25 estimates a greater degree of deterioration of the measurement accuracy as the amplitude of the vibration waveform increases. Furthermore, the deterioration estimation unit 25 estimates a greater degree of deterioration of the measurement accuracy as the number of vibration waveforms increases. Furthermore, the deterioration estimation unit 25 estimates a greater degree of deterioration of the measurement accuracy as the time during which the vibration waveform occurred increases.

This estimation process makes it possible to estimate the degree of deterioration in the measurement accuracy of wheel load sensors 2R-4R and 2L-4L when the measurement signals have waveforms, for example, as shown in Figures 5(B) and (C).

Estimation process 7
The deterioration estimation unit 25 calculates the average value of the measurement values for a predetermined time (about 1 second) before the passage of a wheel. This average value is the measurement value of the wheel load sensors 2R-4R and 2L-4L when no wheels are passing and the measurement signal is stable. The deterioration estimation unit 25 calculates the absolute value of the difference between the calculated average value and a predetermined reference value. The deterioration estimation unit 25 estimates the degree of deterioration of measurement accuracy to be smaller the smaller the calculated absolute value.

This estimation process can estimate the degree of deterioration related to the offset deviation of wheel load sensors 2R-4R and 2L-4L.

The deterioration estimation unit 25 of the axle load measurement device 1 may be configured to execute one or more of the above-mentioned estimation processes 1 to 7. When the deterioration estimation unit 25 executes multiple of the above-mentioned estimation processes 1 to 7, it may estimate the overall degree of deterioration from the individual estimation results.

In this way, the axle load measuring device 1 of this example can estimate the degree of deterioration in the measurement accuracy for each wheel load sensor 2R-4R, 2L-4L from the waveform of the measurement signal of that wheel load sensor 2R-4R, 2L-4L. Therefore, it can detect wheel load sensors 2R-4R, 2L-4L whose measurement accuracy has deteriorated, without being affected by the degree of deterioration in the measurement accuracy of the other wheel load sensors 2R-4R, 2L-4L.

The above-mentioned estimation processes 1 to 6 indicate processes for estimating the degree of deterioration for the waveform of one measurement signal. When estimating the deterioration of wheel load sensors 2R to 4R and 2L to 4L, estimation processes 1 to 6 may be performed for the waveforms of multiple measurement signals to estimate the degree of deterioration overall.

Note that this invention is not limited to the above-described embodiment as it is, and in the implementation stage, the components can be modified to the extent that does not deviate from the gist of the invention. In addition, various inventions can be formed by appropriately combining multiple components disclosed in the above-described embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, components from different embodiments may be appropriately combined.

Furthermore, the correspondence between the configuration according to the present invention and the configuration according to the above-mentioned embodiment can be described as follows.
<Additional Notes>
an axle load sensor connection unit (12) to which measurement signals from a plurality of axle load sensors (2 to 4) arranged in a line in the traveling direction of the vehicle (100) are input;
an axle load calculation unit (23) that calculates an axle load for each axle of the vehicle (100) based on measurement signals input from the plurality of axle load sensors (2 to 4);
and a deterioration estimation unit (25) for estimating deterioration of each of the axle load sensors (2-4) based on the waveform of a measurement signal input from the axle load sensor (2-4).

1...Axle load measuring device 2 to 4...Axle load sensors 2R to 4R, 2L to 4L...Wheel load sensors 6, 7...Vehicle detection sensor 11...Control unit 12...Axle load sensor connection section 13...Loop coil sensor connection section 14...Observation database (observation DB)
15... output section 21... measurement value arrangement section 22... wheel load calculation section 23... axle load calculation section 24... vehicle weight calculation section 25... deterioration estimation section 100... vehicle

Claims (9)

an axle load sensor connection unit to which measurement signals from a plurality of axle load sensors arranged in a line in the traveling direction of the vehicle are input;
an axle load calculation unit that calculates an axle load for each axle of the vehicle based on measurement signals input from the plurality of axle load sensors;
a deterioration estimation unit that estimates deterioration of each of the axle load sensors based on a waveform of a measurement signal input from the axle load sensor ;
The deterioration estimation unit estimates deterioration by comparing the waveform of the measurement signal before and after the reference timing, the timing being determined as a reference timing when the measurement signal of the axle load sensor reaches a peak . The axle load measuring device according to claim 1, further comprising a vehicle weight calculation unit that calculates the weight of the vehicle using the axle load calculated for each axle by the axle load calculation unit. 3. The axle load measuring device according to claim 1, wherein the deterioration estimation unit estimates the deterioration based on a degree of symmetry of a waveform of the measurement signal of the axle load sensor before and after the reference timing. The axle load measuring device according to any one of claims 1 to 3 , wherein the deterioration estimation unit estimates deterioration based on whether a lower limit value of the measurement signal of the axle load sensor after the reference timing is equal to or lower than a lower limit threshold. 5. The axle load measuring device according to claim 1 , wherein the deterioration estimation unit estimates the deterioration based on whether or not there is an inflection point in a waveform of the measurement signal of the axle load sensor before the reference time. The axle load measuring device according to claim 1 , wherein the deterioration estimation unit estimates deterioration based on a magnitude of amplitude of a vibration waveform of a measurement signal of the axle load sensor after the reference timing. The axle load measuring device according to any one of claims 1 to 6, wherein the deterioration estimation unit estimates deterioration based on whether a magnitude of a measurement value indicated by the measurement signal of the axle load sensor when the measurement signal is stable is within an appropriate range . A computer of an axle load measuring device having an axle load sensor connection unit to which measurement signals of a plurality of axle load sensors arranged in a line in a traveling direction of a vehicle are inputted,
an axle load calculation step of calculating an axle load for each axle of the vehicle based on measurement signals input from the plurality of axle load sensors;
a deterioration estimation step of estimating deterioration for each of the axle load sensors based on a waveform of a measurement signal input from the axle load sensor ;
The deterioration estimation step is a step of estimating deterioration by setting a timing at which the measurement signal of the axle load sensor reaches a peak as a reference timing and estimating deterioration by comparing waveforms of the measurement signal before and after this reference timing . A computer of an axle load measuring device having an axle load sensor connection unit to which measurement signals of a plurality of axle load sensors arranged in a line in the traveling direction of a vehicle are inputted,
an axle load calculation step of calculating an axle load for each axle of the vehicle based on measurement signals input from the plurality of axle load sensors;
a deterioration estimation step of estimating deterioration for each of the axle load sensors based on a waveform of a measurement signal input from the axle load sensor ;
The deterioration estimation step is a step of estimating deterioration by setting the timing at which the measurement signal of the axle load sensor reaches a peak as a reference timing and comparing the waveforms of the measurement signal before and after this reference timing .

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