Weight measuring device, measurement accuracy determination method, and measurement accuracy determination program

Abstract

To perform determination on whether the measurement accuracy of a sensors used to measure the weight of a traveling vehicle is appropriate regardless of the presence / absence of travel of a special vehicle.SOLUTION: A plurality of sensors are arranged side by side on a road surface of a measurement section in the travel direction of a vehicle. Each sensor is connected to a sensor connection part and a measurement signal of a load measured by each sensor is input. A ratio calculation unit calculates a ratio of the total weight obtained by totaling the weight according to the load by a tire of the vehicle that has passed through the sensor and the average weight which is the average of the total weight of each sensor as the weight ratio for each sensor for the vehicle that travels in the measurement section. A determination unit determines whether or not the measurement accuracy of the sensor is appropriate on the basis of the weight ratio calculated for the sensor.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a technique for determining whether the measurement accuracy of a sensor used for measuring the weight of a traveling vehicle is appropriate. Background Art

[0002] Conventionally, there have been devices that measure the weight of vehicles traveling on roads. This device processes measurement signals from a plurality (two or more) of axle load sensors arranged in the traveling direction of the vehicle and embedded in the road to measure the weight of the traveling vehicle (see Patent Document 1, etc.). As is well known, an axle load sensor is a sensor used for each axle of a vehicle to measure the vertical force (axle load) when a wheel attached to the axle passes over the sensor.

[0003] The axle load of an axle is calculated by processing measurement signals from a plurality of axle load sensors embedded and arranged in the traveling direction of the vehicle. For example, for each axle, the average value of the axle loads measured by the plurality of axle load sensors for that axle is calculated as the axle load of that axle. Further, the weight of a vehicle is the sum (total) of the axle loads calculated for each axle of the vehicle.

[0004] Further, Patent Document 1 describes a configuration that performs sensitivity correction (a configuration that updates correction coefficients) for each axle load sensor according to the axle load measurement accuracy without interrupting the measurement of the vehicle weight. Specifically, Patent Document 1 has a configuration in which, for each axle load sensor, the correction coefficient for sensitivity correction is updated such that the vehicle weight calculated using measurement data obtained when a predetermined specific vehicle (a vehicle with known vehicle data such as number of axles and gross weight) passes therethrough matches the true value. Prior Art Documents Patent Documents

[0005] Patent Document 1 Japanese Unexamined Patent Publication No. 2010-261825 Summary of the Invention Problems to be Solved by the Invention

[0006] However, the specific vehicle in Patent Document 1 is (1) The vehicle must not have a change in total weight (sum of the axle loads of each axle) depending on the usage conditions. (2) The vehicle must be one of which no other vehicle has similar characteristics in terms of the number of axles, the distance between axles, the axle load, etc. The vehicle must satisfy the following conditions.

[0007] Therefore, vehicles such as trucks and trailers used to carry cargo do not satisfy the conditions in (1) above. Also, ordinary passenger cars (private and company use) do not satisfy the conditions in (2) above. For this reason, the designated vehicle had to be a special vehicle rather than an ordinary vehicle. Patent Document 1 designates a self-propelled crane as the designated vehicle.

[0008] If a particular vehicle is a special type of vehicle, the period between the current operation of that vehicle and the next operation of that vehicle may be long. In the technology described in Patent Document 1, the period for determining whether the measurement accuracy of the axle load sensor has deteriorated is the period between the current operation of that vehicle and the next operation of that vehicle. Therefore, in the technology described in Patent Document 1, situations may arise where it is not possible to determine whether the measurement accuracy of the axle load sensor has deteriorated over a long period of time.

[0009] The objective of this invention is to provide a technology that can determine whether the measurement accuracy of a sensor used to measure the weight of a moving vehicle is appropriate, regardless of whether a special vehicle is in motion or not. [Means for solving the problem]

[0010] The weight measuring device of this invention is configured as follows to achieve the above objective.

[0011] Multiple sensors are arranged on the road surface of the measurement section, aligned in the direction of vehicle travel. Each sensor measures the load (pressure) exerted by the tires of passing vehicles. Each sensor is connected to a sensor connection point, and the measurement signal of the load measured by each sensor is input to it.

[0012] The sensor may be pressed by the tires on both sides of the vehicle's axle, or by the tire on one side of the vehicle's axle.

[0013] The ratio calculation unit calculates a weight ratio for each sensor used by a vehicle that traveled through the measurement section. This ratio is calculated by summing the weights corresponding to the load from the tires of the vehicles that passed through that sensor, and then comparing this total weight with the average weight, which is the average of the total weights from each sensor.

[0014] A moving vehicle vibrates. The load that the tires place on the road surface is affected by this vehicle vibration and fluctuates within a certain range. In other words, the weight calculated from the magnitude of the load on the tires measured by the sensors is also a value affected by the vehicle's vibration. Therefore, the total weight will be a value that is more affected by the vehicle's vibration than the average weight. Also, the average weight will be less affected by the vehicle's vibration as the number of sensors arranged in line with the vehicle's direction of travel increases.

[0015] The determination unit determines whether the measurement accuracy of the sensor is appropriate based on the weight ratio calculated for that sensor.

[0016] For example, the determination unit determines whether the measurement accuracy of a sensor is appropriate based on the shape of the frequency distribution of weight ratios calculated for that sensor. The frequency distribution of weight ratios can be considered as the distribution of load fluctuations due to vehicle vibration. Furthermore, the distribution of load fluctuations due to vehicle vibration is a distribution that approximates a normal distribution with a certain magnitude of variance. Therefore, the measurement accuracy of a sensor can be determined based on the shape of the frequency distribution of weight ratios. In other words, it is possible to determine whether the measurement accuracy of a sensor used to measure the weight of a moving vehicle is appropriate, regardless of whether a special vehicle is running or not.

[0017] For example, the determination unit may be configured to determine whether the sensor's measurement accuracy is appropriate based on the degree of symmetry of the shape of the weight ratio frequency distribution, with respect to the peak frequency. In this case, the determination unit calculates the degree of symmetry of the shape of the weight ratio frequency distribution, and determines whether the sensor's measurement accuracy is appropriate based on whether the calculated degree exceeds a predetermined symmetry threshold.

[0018] Alternatively, the determination unit may be configured to determine whether the sensor's measurement accuracy is appropriate based on the magnitude of the variance in the frequency distribution of weight ratios. In this case, for example, the determination unit may be configured to determine whether the sensor's measurement accuracy is appropriate based on whether the variance in the frequency distribution of weight ratios falls between a predetermined lower threshold and an upper threshold (lower threshold < upper threshold).

[0019] Furthermore, if the sensor is pressed by the tires on both sides of the axle of a vehicle traveling through the measurement section (i.e., if the sensor is a so-called axle load sensor), the average weight can be obtained as the weight of the vehicle traveling through the measurement section.

[0020] Further, when the sensor is a so-called wheel load sensor, the sensors may be arranged in two rows in the vehicle width direction of the vehicle. In this case, the sensors in one row may be arranged at a position pressed by the tire on one side attached to the axle of the vehicle traveling in the measurement section, and the sensors in the other row may be arranged at a position pressed by the tire on the other side attached to the axle of the vehicle traveling in the measurement section.

[0021] Further, when the sensor is a so-called wheel load sensor, the sum of the average weight obtained by the sensors in one row and the average weight obtained by the sensors in the other row may be obtained as the weight of the vehicle that has traveled the measurement section.

Effects of the Invention

[0022] According to the present invention, whether the measurement accuracy of a sensor used for measuring the weight of a traveling vehicle is appropriate can be determined regardless of whether a special vehicle is traveling or not.

Brief Description of Drawings

[0023] [Figure 1] FIG. 1 is a schematic diagram showing a vehicle weight measurement system to which the axle load measurement device according to this example is applied. [Figure 2] FIG. 2 is a block diagram showing the configuration of main parts of the axle load measurement device according to this example. [Figure 3] FIG. 3 is a diagram showing an example of statistical data. [Figure 4] FIGS. 4(A) to 4(C) are diagrams showing examples of histograms of the number of vehicles versus weight ratio. [Figure 5] FIG. 5 is a flowchart showing measurement processing of the axle load measurement device according to this example. [Figure 6] FIG. 6 is a flowchart showing measurement accuracy determination processing of the axle load measurement device according to this example. [Figure 7] FIG. 7 is a schematic diagram showing a modified vehicle weight measurement system. [Figure 8] FIG. 8 is a diagram showing an example of statistical data in the modified example, where FIG. 8(A) shows right-side weight data and FIG. 8(B) shows left-side weight data. [Modes for carrying out the invention]

[0024] The following describes an axial load measuring device according to an embodiment of this invention.

[0025] <1. Application Examples> Figure 1 is a schematic diagram showing a vehicle weight measurement system to which the axle load measuring device according to this example is applied. The vehicle weight measurement system shown in Figure 1 comprises an axle load measuring device 1, three axle load sensors 2-4, and two vehicle detection sensors 6 and 7. The axle load sensors 2-4 and the vehicle detection sensors 6 and 7 are connected to the axle load measuring device 1. In this example, the axle load measuring device 1 corresponds to the weight measuring device as defined in this invention. Also, in this example, the axle load sensors 2-4 correspond to the sensors as defined in this invention.

[0026] As shown in Figure 1, the vehicle detection sensor 6, axle load sensor 2, axle load sensor 3, axle load sensor 4, and vehicle detection sensor 7 are arranged on the road in this order in the direction of travel of the vehicle 100. The measurement section for measuring the axle load of the vehicle 100 is the section from vehicle detection sensor 6 to vehicle detection sensor 7. Vehicle detection sensor 6 detects the vehicle 100 entering the measurement section. Vehicle detection sensor 7 detects the vehicle 100 exiting the measurement section.

[0027] Axle load sensors 2-4 are placed on the road surface in the measurement section and measure the load when pressed by the tires of vehicle 100 traveling through the measurement section. The length of axle load sensors 2-4 in the vehicle width direction is the length that the left and right tires (wheels) attached to the axles of vehicle 100 traveling through this measurement section pass through. In other words, when vehicle 100 travels through the measurement section, axle load sensors 2-4 are pressed by the left and right tires attached to each axle of vehicle 100. To put it another way, axle load sensors 2-4 output a measurement signal to the axle load measuring device 1 that measures the load when pressed by the left and right tires attached to each axle of vehicle 100 traveling through the measurement section. Axle load sensors 2-4 may be embedded in the road surface or partially exposed on the road surface. Axle load sensors 2-4 can be any sensor capable of measuring load and are not limited to sensors using a specific type of element.

[0028] Vehicle detection sensors 6 and 7 are, for example, loop coil sensors, and they output changes in inductance as a vehicle detection signal (a signal indicating the presence or absence of a vehicle 100) to the axle load measuring device 1.

[0029] The vehicle detection sensors 6 and 7 may be optical sensors, radio wave sensors, ultrasonic sensors, etc., that are not embedded in the road. Alternatively, the system may be configured to isolate the vehicle 100 based on the detection output of the axle load sensors 2 to 4. In this case, the vehicle detection sensors 6 and 7 can be made unnecessary.

[0030] The axle load measuring device 1 receives measurement signals from axle load sensor 2, axle load sensor 3, and axle load sensor 4 for each axle of a vehicle 100 that has traveled through the measurement section.

[0031] In the direction of travel of vehicle 100, the distance L1 between axle load sensor 2 and axle load sensor 3, and the distance L2 between axle load sensor 3 and axle load sensor 4 are different lengths. A moving vehicle 100 vibrates due to the complex interplay of various factors such as road surface irregularities, speed, and tire pressure. If both the distance L1 between adjacent axle load sensors 2 and 3, and the distance L2 between adjacent axle load sensors 3 and 4, approximate integer multiples of the vibration wavelength of vehicle 100, the measurement error of the axle load may increase. Therefore, in this example, distances L1 and L2 are set to different lengths so that even if one of the distances, L1 between adjacent axle load sensors 2 and 3, or L2 between adjacent axle load sensors 3 and 4, approximates an integer multiple of the vibration wavelength of vehicle 100, the other does not approximate an integer multiple of the vibration wavelength of vehicle 100.

[0032] In this example, the axle load measuring device 1 stores a measured value corresponding to the input measurement signal for each axle load sensor 2-4. In this example, this measured value is described as the axle load calculated using the input measurement signal. However, this measured value can be any value as long as it corresponds to the input measurement signal. For example, this measured value may be the digital value of the input measurement signal.

[0033] Since the moving vehicle 100 is vibrating, even if the measurement accuracy of the axle load sensors 2-4 is appropriate, there will be variability in the measured axle load values. This variability in the measured axle load values ​​will fall within a certain range if the measurement accuracy of the axle load sensors 2-4 is appropriate (however, depending on the magnitude of the vibration of vehicle 100, it may not fall within a certain range).

[0034] The axle load measuring device 1 calculates the total weight for each of the axle load sensors 2 to 4. Specifically, the axle load measuring device 1 calculates the total weight of axle load sensors 2 as the sum of the axle loads of each axle measured by axle load sensor 2. The axle load measuring device 1 calculates the total weight of axle load sensors 3 as the sum of the axle loads of each axle measured by axle load sensor 3. The axle load measuring device 1 calculates the total weight of axle load sensors 4 as the sum of the axle loads of each axle measured by axle load sensor 4.

[0035] Furthermore, the axle load measuring device 1 calculates the average weight by taking the sum of the weights of each axle load sensor 2 to 4. The axle load measuring device 1 acquires this average weight as the weight of the vehicle 100 that traveled through the measurement section.

[0036] The total weight is the weight of vehicle 100 without considering the effects of vibration. The average weight is the weight of vehicle 100 with the effects of vibration reduced compared to the total weight.

[0037] In this example, there are three axle load sensors placed in the measurement section, but any number of sensors, two or more, is acceptable. The more axle load sensors placed in the measurement section the axle load measuring device 1 can obtain the weight (average weight) of the vehicle 100 with the influence of vehicle vibration reduced.

[0038] The axle load measuring device 1 calculates a weight ratio for each of the axle load sensors 2 to 4, which is the ratio of the total weight of the vehicle 100 measured by that axle load sensor 2 to 4 to the average weight. In this example, the weight ratio is calculated as total weight / average weight, but it may also be calculated as average weight / total weight.

[0039] The axle load measuring device 1 determines whether the measurement accuracy is appropriate for each axle load sensor 2 to 4, based on the shape of the histogram of the weight ratio of each vehicle 100 that traveled through the measurement section during a predetermined period, which is obtained by statistical processing.

[0040] This allows the axle load measuring device 1 to determine whether the measurement accuracy of the axle load sensors 2-4 used to measure the weight of the moving vehicle 100 is appropriate, regardless of whether the special vehicle 100 is in motion or not.

[0041] <2. Example Configuration> Figure 2 is a block diagram showing the configuration of the main parts of the axle load measuring device according to this example. The axle load measuring device 1 according to this example comprises a control unit 11, an axle load sensor connection unit 12, a loop coil sensor connection unit 13, a statistical database 14 (statistical DB 14), and an output unit 15.

[0042] The control unit 11 controls the operation of each part of the axle load measuring device 1 main body according to this example. The control unit 11 also includes an axle load calculation unit 21, a vehicle weight calculation unit 22, a ratio calculation unit 23, and a determination unit 24. Although not specifically shown in the figures, the control unit 11 has a memory with a storage area for storing symmetry thresholds and the like, which will be described later. Details of the axle load calculation unit 21, vehicle weight calculation unit 22, ratio calculation unit 23, and determination unit 24 of the control unit 11 will be described later.

[0043] The axle load sensor connection unit 12 receives the measurement signals from the connected axle load sensors 2 to 4. The axle load sensor connection unit 12 converts the received measurement signals from the axle load sensors 2 to 4 into digital values ​​and outputs them to the control unit 11.

[0044] 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 to the control unit 11 indicating the presence or absence of a vehicle 100.

[0045] The statistical database DB14 stores statistical data for each 100 vehicles that traveled the measurement section, associating the vehicle ID, date of travel, time of travel, axle load, total weight, average weight, and weight ratio (see Figure 3).

[0046] The vehicle ID is the number assigned to vehicle 100 when it travels through the measurement section. The vehicle ID does not identify vehicle 100 specifically. For example, the vehicle ID assigned to vehicle 100 after it has traveled through the measurement section is the previously assigned vehicle ID incremented (+1). Alternatively, the upper digits of the vehicle ID may be the date the vehicle traveled through the measurement section. For example, if the travel date is November 1, 2022, the vehicle ID may be 20221101********. The lower digits ***** of the vehicle ID are the number that is incremented when vehicle 100 travels through the measurement section.

[0047] The running date is the year, month, and day when vehicle 100 traveled through the measurement section.

[0048] The travel time is the time when vehicle 100 traveled through the measurement section. The travel time may be, for example, the time when vehicle 100 entered the measurement section, the time when vehicle 100 exited the measurement section, or a time midway between the time when vehicle 100 entered the measurement section and the time when it exited the measurement section.

[0049] Axle load is the weight (axle load) corresponding to the load measured by each axle load sensor 2-4 (the load from the left and right tires attached to that axle) for each axle of the vehicle 100 that traveled the measurement section. The statistical data in the example shown in Figure 3 is an example where the vehicle 100 that traveled the measurement section had three axles. In the case of a vehicle 100 with two axles, the statistical data does not include data for the third axle. Also, in the case of a vehicle 100 with four or more axles, the statistical data includes data for the fourth axle, fifth axle, etc., depending on the number of axles.

[0050] MA1, shown in Figure 3, is the weight of the first axle of vehicle 100 obtained from the measurement signal of axle load sensor 2. In other words, MA1 is the axle load of the first axle of vehicle 100 as measured by axle load sensor 2. MA2 is the axle load of the second axle of vehicle 100 obtained from the measurement signal of axle load sensor 2, and MA3 is the axle load of the third axle of vehicle 100 obtained from the measurement signal of axle load sensor 2. Similarly, MB1, shown in Figure 3, is the axle load of the first axle of vehicle 100 obtained from the measurement signal of axle load sensor 3, MB2 is the axle load of the second axle of vehicle 100 obtained from the measurement signal of axle load sensor 3, and MB3 is the axle load of the third axle of vehicle 100 obtained from the measurement signal of axle load sensor 3. As shown in Figure 3, MC1 is the axle load of the first axle of the vehicle 100 obtained from the measurement signal of the axle load sensor 4, MC2 is the axle load of the second axle of the vehicle 100 obtained from the measurement signal of the axle load sensor 4, and MC3 is the axle load of the third axle of the vehicle 100 obtained from the measurement signal of the axle load sensor 4.

[0051] The total weight MA is the sum of the axle loads of each axle of vehicle 100 as measured by axle load sensor 2, and can be considered as the weight of vehicle 100 as measured by axle load sensor 2. Similarly, the total weight MB is the sum of the axle loads of each axle of vehicle 100 as measured by axle load sensor 3, and can be considered as the weight of vehicle 100 as measured by axle load sensor 3. The total weight MC is the sum of the axle loads of each axle of vehicle 100 as measured by axle load sensor 4, and can be considered as the weight of vehicle 100 as measured by axle load sensor 4.

[0052] Vehicle 100, which has three axles, is as shown in Figure 3. The total weight MA = MA1 + MA2 + MA3, The total weight MB = MB1 + MB2 + MB3, The total weight MC = MC1 + MC2 + MC3.

[0053] The average weight Mav is the average of the total weight MA, total weight MB, and total weight MC. That is, Average weight Mav=(total weight MA+total weight MB+total weight MC) / 3 That is the case.

[0054] As described above, the total weights MA, MB, and MC are the weights of vehicle 100 measured by individual axle load sensors 2-4, and the average weight Mav is the average value of the weights of vehicle 100 measured by individual axle load sensors 2-4. Therefore, the total weights MA, MB, and MC are the weights of vehicle 100 without considering the effects of vibration. The average weight Mav is the weight of vehicle 100 with reduced effects of vibration compared to the total weights MA, MB, and MC.

[0055] The weight ratio is the ratio of the total weight MA, MB, MC of the vehicle 100 measured by axle load sensors 2-4 to the average weight Mav for each axle load sensor 2-4. Specifically, the weight ratio for axle load sensor 2 is MA / Mav, the weight ratio for axle load sensor 3 is MB / Mav, and the weight ratio for axle load sensor 4 is MC / Mav.

[0056] If the measurement accuracy of axle load sensor 2 is appropriate, the weight ratio (MA / Mav) of axle load sensor 2 can be considered as the magnitude of the influence that the vibration of vehicle 100 had on the weight (MA) of vehicle 100 as measured by axle load sensor 2. Similarly, if the measurement accuracy of axle load sensor 3 is appropriate, the weight ratio (MB / Mav) of axle load sensor 3 can be considered as the magnitude of the influence that the vibration of vehicle 100 had on the weight (MB) of vehicle 100 as measured by axle load sensor 3. Furthermore, if the measurement accuracy of axle load sensor 4 is appropriate, the weight ratio (MC / Mav) of axle load sensor 4 can be considered as the magnitude of the influence that the vibration of vehicle 100 had on the weight (MC) of vehicle 100 as measured by axle load sensor 4.

[0057] The output unit 15 outputs to a higher-level device (not shown) the determination result of whether the measurement accuracy of the axle load sensors 2 to 4 is appropriate, the weight of the vehicle 100 that traveled through the measurement section (the average weight Mav mentioned above), etc.

[0058] Next, the axle load calculation unit 21, vehicle weight calculation unit 22, ratio calculation unit 23, and determination unit 24 of the control unit 11 will be described.

[0059] The axle load calculation unit 21 uses the measurement signals from the axle load sensor 2 to calculate the axle loads of each axle of the vehicle 100 that traveled through the measurement section (MA1 to MA3 shown in Figure 3). The axle load calculation unit 21 also uses the measurement signals from the axle load sensor 3 to calculate the axle loads of each axle of the vehicle 100 that traveled through the measurement section (MB1 to MB3 shown in Figure 3). Furthermore, the axle load calculation unit 21 uses the measurement signals from the axle load sensor 4 to calculate the axle loads of each axle of the vehicle 100 that traveled through the measurement section (MC1 to MC3 shown in Figure 3).

[0060] The vehicle weight calculation unit 22 calculates the total weight (MA, MB, MC shown in Figure 3) and the average weight (Mav shown in Figure 3).

[0061] The ratio calculation unit 23 calculates the weight ratio (MA / Mav, MB / Mav, MC / Mav shown in Figure 3) for each of the axial load sensors 2 to 4.

[0062] The weight ratio may also be Mav / MA, Mav / MB, or Mav / MC.

[0063] The determination unit 24 processes the statistical data recorded in the statistical DB 14 and determines whether the measurement accuracy is appropriate for each of the axle load sensors 2 to 4.

[0064] The determination unit 24 extracts statistical data (target statistical data) of the vehicles 100 used to determine whether the measurement accuracy of the axle load sensors 2 to 4 is appropriate from the statistical DB 14. For example, the target statistical data may be statistical data of vehicles 100 that traveled the measurement section during a set period (e.g., the most recent week, the most recent month), or statistical data of a set number of vehicles (e.g., the most recent 5,000 vehicles, the most recent 10,000 vehicles).

[0065] The determination unit 24 generates a histogram of the number of vehicles 100 relative to the weight ratio for each axle load sensor 2 to 4 (corresponding to the frequency distribution of the weight ratio in this invention). Figures 4(A) to 4(C) show examples of histograms of the number of vehicles relative to the weight ratio. Figure 4(A) is an example of a histogram of the number of vehicles relative to the weight ratio when the measurement accuracy of the axle load sensor is appropriate. Figures 4(B) and 4(C) are examples of histograms of the number of vehicles relative to the weight ratio when the measurement accuracy of the axle load sensor is not appropriate.

[0066] The total weight measured by axle load sensors 2-4 is the weight affected by the vibration of vehicle 100. The frequency distribution of the magnitude of the effect of vehicle 100's vibration on axle load sensors 2-4 approximates a normal distribution with a certain degree of variance. The frequency distribution of the weight ratios for each axle load sensor 2-4 can be considered as the distribution of load fluctuations due to vehicle 100's vibration. Therefore, for axle load sensors 2-4 with appropriate measurement accuracy, the shape of the weight ratio frequency distribution approximates a normal distribution with a certain degree of variance. Conversely, for axle load sensors 2-4 with inadequate measurement accuracy, the shape of the weight ratio frequency distribution does not approximate a normal distribution with a certain degree of variance.

[0067] For example, as shown in Figure 4(A), when the axle load sensor has proper measurement accuracy, the histogram will have a nearly symmetrical shape on the left and right sides, based on the weight ratio where the number of vehicles 100 is at its peak. On the other hand, as shown in Figures 4(B) and (C), when the axle load sensor does not have proper measurement accuracy, the histogram will have an asymmetrical shape on the left and right sides, based on the weight ratio where the number of vehicles 100 is at its peak.

[0068] The measurement accuracy of the axle load sensor does not suddenly drop from the appropriate Level 1 to the inappropriate Level 2, but rather gradually from Level 1 to Level 2. Therefore, even for axle load sensors 2-4 with inappropriate measurement accuracy, the statistical data extracted to generate the frequency distribution of weight ratios includes statistical data from when the measurement accuracy was appropriate. Consequently, for axle load sensors with inappropriate measurement accuracy, the shape of the frequency distribution of weight ratios does not approximate a normal distribution with a certain degree of variance, as shown in Figures 4(B) and (C).

[0069] The determination unit 24 determines whether the measurement accuracy is appropriate for each of the axle load sensors 2 to 4, based on the shape of the frequency distribution of the weight ratios in that axle load sensor 2 to 4.

[0070] The control unit 11 of the axle load measuring device 1 is composed of a hardware CPU, memory, and other electronic circuits. When the hardware CPU executes the measurement accuracy determination program according to this invention, it operates as an axle load calculation unit 21, a vehicle weight calculation unit 22, a ratio calculation unit 23, and a determination unit 24. The memory has an area for deploying the measurement accuracy determination program according to this invention and an area for temporarily storing data generated when the measurement accuracy determination program is executed. The control unit 11 may be an LSI integrating the hardware CPU, memory, etc. Furthermore, the hardware CPU is a computer that executes the measurement accuracy determination method according to this invention.

[0071] <3. Example of operation> In this example, the axle load measuring device 1 performs a measurement process to measure the axle load of a vehicle 100 that has traveled through a measurement section, and a measurement accuracy determination process to determine whether the measurement accuracy of the axle load sensors 2 to 4 is appropriate.

[0072] Figure 5 is a flowchart showing the measurement process of the axle load measuring device in this example. The axle load measuring device 1 waits for the vehicle 100 to enter the measurement section (s1). The control unit 11 detects that the vehicle 100 has entered the measurement section by observing the change in inductance of the vehicle detection sensor 6 connected to the loop coil sensor connection section 13.

[0073] When the axle load calculation unit 21 detects that the vehicle 100 has entered the measurement section, it starts the process of storing the measurement signals from the axle load sensors 2 to 4 connected to the axle load sensor connection unit 12 in memory (s2). The time interval for storing the measurement signals from the axle load sensors 2 to 4 is, for example, several tens of milliseconds to several hundred milliseconds.

[0074] When the axle load calculation unit 21 detects that the vehicle 100 has left the measurement section (s3), it terminates the process of storing the measurement signals from the axle load sensors 2 to 4, which were started in s2, into memory (s4). The axle load calculation unit 21 processes the measurement signals stored in memory for each of the axle load sensors 2 to 4 and calculates the axle load for each axle (s5).

[0075] Each axle load sensor changes its measurement signal when an axle (wheel) of vehicle 100 passes over it. Therefore, the axle load calculation unit 21 can obtain the number of axles of vehicle 100 by counting the points where the measurement signals of axle load sensors 2 to 4 change. The axle load calculation unit 21 can also extract the measurement signals from axle load sensors 2 to 4 when a wheel of each axle passes over it and calculate the axle load (for example, MA1 to MA3, MB1 to MB3, MC1 to MC3 shown in Figure 3).

[0076] The vehicle weight calculation unit 22 calculates the total weight MA, MB, and MC of each axle load sensor 2 to 4, and the average weight Mav, for the vehicle 100 that passed through the measurement section (s6). The total weight MA of axle load sensor 2 is the sum of the axle loads of each axle of the vehicle 100 measured by axle load sensor 2 for the vehicle 100 that passed through the measurement section. The total weight MB of axle load sensor 3 is the sum of the axle loads of each axle of the vehicle 100 measured by axle load sensor 3 for the vehicle 100 that passed through the measurement section. The total weight MC of axle load sensor 4 is the sum of the axle loads of each axle of the vehicle 100 measured by axle load sensor 4 for the vehicle 100 that passed through the measurement section.

[0077] Furthermore, the average weight Mav is the average of the total weights MA, MB, and MC of each axis load sensor 2-4.

[0078] The ratio calculation unit 23 calculates the weight ratio for each of the axle load sensors 2 to 4 (s7). The axle load measuring device 1 generates the statistical data shown in Figure 3 for the vehicle 100 that traveled through the measurement section, stores the generated statistical data in the statistical DB 14 (s8), and returns to s1.

[0079] In this example, the axle load measuring device 1 generates statistical data as shown in Figure 3 for each vehicle 100 that travels through the measurement section. The statistical DB 14 stores the statistical data generated for each vehicle 100 that passes through the measurement section.

[0080] Furthermore, the axle load measuring device 1 may output the weight of the vehicle 100 (average weight Mav calculated in s6) at the output unit 15 each time the vehicle 100 travels through the measurement section.

[0081] Furthermore, the statistical data stored in the statistical database 14 can be used as useful information for determining whether or not road repair work is necessary.

[0082] Next, the measurement accuracy determination process for the axle load measuring device 1 in this example will be explained. This measurement accuracy determination process determines whether the measurement accuracy of the axle load sensors 2 to 4 is appropriate. Figure 6 is a flowchart showing the measurement accuracy determination process.

[0083] The determination unit 24 determines whether it is the timing to determine the measurement accuracy of the axle load sensors 2 to 4 (s11). The determination timing may be, for example, 0:00 AM on Mondays every week, 0:00 AM on the 1st of every month, 0:00 AM on the 1st of every month, or when the number of vehicles 100 that have traveled through the measurement section since the end of the previous measurement accuracy determination process reaches a set number (500 or 1000 vehicles), or at a timing instructed by the administrator, or at any other timing.

[0084] When the determination unit 24 determines that it is time for a determination, it extracts the target statistical data from the statistical data stored in the statistical DB 14 (s12). For example, the determination unit 24 may extract the statistical data of vehicles 100 that have traveled the measurement section in the last week or last month as the target statistical data, or it may extract the statistical data of the last 5,000 vehicles or the last 10,000 vehicles 100 as the target statistical data.

[0085] The determination unit 24 determines the axle load sensor to be determined to determine whether the measurement accuracy is appropriate (s13). In s13, one of the axle load sensors 2 to 4 connected to the axle load sensor connection part 12 of the axle load measuring device 1, which has not been determined to determine whether the measurement accuracy is appropriate in this measurement accuracy determination process (undetermined axle load sensor 2 to 4), is determined to be the axle load sensor to be determined.

[0086] The determination unit 24 generates a frequency distribution of weight ratios for the axis load sensors to be determined in s13 (s14). In s14, the frequency distribution of weight ratios is generated using the target statistical data extracted in s12.

[0087] The determination unit 24 determines whether the frequency distribution of weight ratios generated in s14 for the axis load sensor to be determined can be considered a normal distribution (s15).

[0088] In s15, for example, the degree of symmetry between the distribution shape on the left and the distribution shape on the right, which are divided using the peak (the weight ratio with the maximum number of vehicles 100) in the frequency distribution generated in s14 as the reference (center), is calculated. The determination unit 24 calculates the degree of symmetry between the distribution shape on the left and the distribution shape on the right, for example, by determining the similarity between the distribution shape on the left and the left-side inverted distribution shape on the left. If the calculated degree of symmetry exceeds a predetermined symmetry threshold, the determination unit 24 determines that the frequency distribution of weight ratios generated in s14 can be considered a normal distribution. Conversely, if the calculated degree of symmetry does not exceed a predetermined symmetry threshold, the determination unit 24 determines that the frequency distribution of weight ratios generated in s14 cannot be considered a normal distribution.

[0089] Furthermore, the determination unit 24 determines the variance δ of the frequency distribution generated in s14. 2 The variance δ calculated here is used to calculate the variance δ. 2 If the value falls between a predetermined upper threshold and a predetermined lower threshold, the frequency distribution of weight ratios generated in s14 can be considered to be a normal distribution. Conversely, the determination unit 24 may determine that the calculated variance δ 2 If the value is not between a predetermined upper threshold and a predetermined lower threshold, it is determined that the frequency distribution of weight ratios generated in s14 cannot be considered a normal distribution.

[0090] The determination unit 24 is variance δ 2 Alternatively, the standard deviation δ can be calculated, and the frequency distribution of weight ratios generated in s14 can be considered a normal distribution based on the standard deviation δ. Furthermore, the kurtosis, skewness, etc., of the frequency distribution of weight ratios can be used to determine whether this frequency distribution can be considered a normal distribution.

[0091] Furthermore, the determination unit 24 determines that the degree of symmetry of the distribution shape described above exceeds the symmetry threshold, and that the variance δ 2The configuration may be such that if the value falls between a predetermined upper threshold and a predetermined lower threshold, the frequency distribution of weight ratios generated in s14 can be considered a normal distribution. In other words, the determination unit 24 determines that the degree of symmetry of the distribution shape described above does not exceed the symmetry threshold, or the variance δ 2 The system may be configured to determine that the frequency distribution of weight ratios generated in s14 cannot be considered a normal distribution if the value is not between a predetermined upper threshold and a predetermined lower threshold. Furthermore, the system may also add kurtosis, skewness, etc., to the frequency distribution of weight ratios to determine whether this frequency distribution can be considered a normal distribution.

[0092] If the determination unit 24 determines that the frequency distribution of weight ratios can be considered a normal distribution, it determines that the measurement accuracy of the axle load sensor being evaluated is appropriate (s16). Conversely, if the determination unit 24 determines that the frequency distribution of weight ratios cannot be considered a normal distribution, it determines that the measurement accuracy of the axle load sensor being evaluated is inappropriate (s17).

[0093] The determination unit 24 determines whether there are any undetermined axle load sensors whose measurement accuracy has not been determined (s18). If there are any undetermined axle load sensors, the determination unit 24 returns to s13 and repeats the above process. If there are any undetermined axle load sensors, the determination unit 24 associates the current determination result, which determines whether the measurement accuracy is appropriate, for each axle load sensor 2 to 4, outputs it to the higher-level device (s19), and returns to s1.

[0094] Thus, the axle load measuring device 1 in this example can determine whether the measurement accuracy of the axle load sensors 2 to 4 used to measure the weight of a moving vehicle 100 is appropriate, regardless of whether or not a special vehicle is in motion.

[0095] Furthermore, it is possible to periodically determine whether the measurement accuracy of the axle load sensors 2-4 is appropriate, or to perform this determination at times specified by the administrator.

[0096] <4. Variation> Next, a modified vehicle weight measurement system will be described. Figure 7 is a schematic diagram showing a modified vehicle weight measurement system.

[0097] This modified vehicle weight measurement system differs from the above example in that the axle load sensor 2 consists of a pair of wheel load sensors 2R and 2L, the axle load sensor 3 consists of a pair of wheel load sensors 3R and 3L, and the axle load sensor 4 consists of a pair of wheel load sensors 4R and 4L.

[0098] Axle load sensor 2 consists of a pair of wheel load sensors 2R and 2L arranged in the width direction of a vehicle 100 traveling on a road. Similarly, axle load sensor 3 consists of a pair of wheel load sensors 3R and 3L arranged in the width direction of a vehicle 100 traveling on a road, and axle load sensor 4 consists of a pair of wheel load sensors 4R and 4L arranged in the width direction of a vehicle 100 traveling on a road. Wheel load sensors 2R to 4R are positioned where the right-side tire of the vehicle 100 passes. Wheel load sensors 2L to 4L are positioned where the left-side tire of the vehicle 100 passes. Wheel load sensors 2R to 4R and 2L to 4L are, for example, piezoelectric sensors, and output a measurement signal to the axle load measuring device 1 corresponding to the pressing force when the tire passes over them.

[0099] The axle load measuring device 1 in this modified example has the same configuration as in the example above, as shown in Figure 2. However, it differs from the example above in that wheel load sensors 2R~4R and 2L~4L are connected to the axle load sensor connection section 12.

[0100] Furthermore, this modified axle load measuring device 1 stores the right-side weight data and the left-side weight data in pairs in the statistical DB 14 as statistical data for each vehicle 100. Figure 8(A) shows the right-side weight data, and Figure 8(B) shows the left-side weight data.

[0101] The pair of right-side weight data and left-side weight data have the same vehicle ID, date of travel, and time of travel. The vehicle ID, date of travel, and time of travel for the right-side weight data and left-side weight data are the same as in the example above.

[0102] Right-side weight data is generated based on the measurement signals from wheel load sensors 2R to 4R. Left-side weight data is generated based on the measurement signals from wheel load sensors 2L to 4L. The wheel load in the right-side weight data is the weight (wheel load) corresponding to the load measured by each wheel load sensor 2R to 4R (the load from the right-side tire attached to that axle) for each axle of vehicle 100 that traveled the measurement section. The right-side weight data in the example shown in Figure 8(A) and the left-side weight data in the example shown in Figure 8(B) are examples where vehicle 100 that traveled the measurement section had three axles. In the case of vehicle 100 with two axles, the right-side weight data and left-side weight data do not include data for the third axle. In the case of vehicle 100 with four or more axles, the right-side weight data and left-side weight data include data for the fourth axle, fifth axle, etc., depending on the number of axles.

[0103] RMA1, shown in Figure 8(A), is the wheel load of the right tire on the first axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 2R. In other words, RMA1 is the wheel load of the right tire on the first axle of vehicle 100, as measured by the wheel load sensor 2R. Similarly, RMA2 is the wheel load of the right tire on the second axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 2R, and RMA3 is the wheel load of the right tire on the third axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 2R. Likewise, RMB1, shown in Figure 8(A), is the wheel load of the right tire on the first axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 3R, RMB2 is the wheel load of the right tire on the second axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 3R, and RMB3 is the wheel load of the right tire on the third axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 3R. As shown in Figure 8(A), RMC1 is the wheel load of the right tire on the first axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 4R; RMC2 is the wheel load of the right tire on the second axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 4R; and RMC3 is the wheel load of the right tire on the third axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 4R.

[0104] The right total weight RMA is the sum of the wheel loads of the right-side tires on each axle of vehicle 100 as measured by wheel load sensor 2R, and can be considered as the right-side weight of vehicle 100 as measured by wheel load sensor 2R. Similarly, the right total weight RMB is the sum of the wheel loads of the right-side tires on each axle of vehicle 100 as measured by wheel load sensor 3R, and can be considered as the right-side weight of vehicle 100 as measured by wheel load sensor 3R. The right total weight RMC is the sum of the wheel loads of the right-side tires on each axle of vehicle 100 as measured by wheel load sensor 4R, and can be considered as the right-side weight of vehicle 100 as measured by wheel load sensor 4R.

[0105] Vehicle 100, which has three axles, is as shown in Figure 8(A), The total weight RMA on the right is RMA1 + RMA2 + RMA3, The total weight on the right is RMB = RMB1 + RMB2 + RMB3. The total weight on the right, RMC, is RMC1 + RMC2 + RMC3.

[0106] The right-hand average weight RMav is the average of the right-hand total weight RMA, right-hand total weight RMB, and right-hand total weight RMC. That is, Right average weight RMav =(Right total weight RMA+Right total weight RMB+Right total weight RMC) / 3 That is the case.

[0107] As described above, the right total weights RMA, RMB, and RMC are the weights on the right side of vehicle 100 measured by individual wheel load sensors 2R to 4R, and the right average weight RMav is the average value of the right side weights of vehicle 100 measured by individual wheel load sensors 2R to 4R. Therefore, the right total weights RMA, RMB, and RMC are the weights on the right side of vehicle 100 without considering the effects of vibration. The right average weight RMav is the weights on the right side of vehicle 100 with reduced effects of vibration compared to the right total weights RMA, RMB, and RMC.

[0108] The right-side weight ratio is the ratio of the total right-side weight RMA, RMB, and RMC of vehicle 100 measured by wheel load sensors 2R to 4R to the average right-side weight RMav. Specifically, the right-side weight ratio for wheel load sensor 2R is RMA / RMav, the right-side weight ratio for wheel load sensor 3R is RMB / RMav, and the right-side weight ratio for wheel load sensor 4R is RMC / RMav.

[0109] If the measurement accuracy of wheel load sensor 2R is appropriate, the right-side weight ratio (RMA / RMav) of wheel load sensor 2R can be considered as the magnitude of the effect of vehicle vibration on the right-side weight (RMA) of vehicle 100 as measured by wheel load sensor 2R. Similarly, if the measurement accuracy of wheel load sensor 3R is appropriate, the right-side weight ratio (RMB / RMav) of wheel load sensor 3R can be considered as the magnitude of the effect of vehicle vibration on the right-side weight (RMB) of vehicle 100 as measured by wheel load sensor 3R. Furthermore, if the measurement accuracy of wheel load sensor 4R is appropriate, the right-side weight ratio (RMC / RMav) of wheel load sensor 4R can be considered as the magnitude of the effect of vehicle vibration on the right-side weight (RMC) of vehicle 100 as measured by wheel load sensor 4R.

[0110] Furthermore, LMA1 shown in Figure 8(B) is the wheel load of the left tire on the first axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 2L. In other words, LMA1 is the wheel load of the left tire on the first axle of vehicle 100, measured by the wheel load sensor 2L. Similarly, LMA2 is the wheel load of the left tire on the second axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 2L, and LMA3 is the wheel load of the left tire on the third axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 2L. Likewise, LMB1 shown in Figure 8(B) is the wheel load of the left tire on the first axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 3L, LMB2 is the wheel load of the left tire on the second axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 3L, and LMB3 is the wheel load of the left tire on the third axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 3L. As shown in Figure 8(B), LMC1 is the wheel load of the left tire on the first axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 4L; LMC2 is the wheel load of the left tire on the second axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 4L; and LMC3 is the wheel load of the left tire on the third axle of vehicle 100, obtained from the measurement signal of the wheel load sensor 4L.

[0111] The left total weight LMA is the sum of the wheel loads of the left-side tires on each axle of vehicle 100 as measured by wheel load sensor 2L, and can be considered as the weight of the left side of vehicle 100 as measured by wheel load sensor 2L. Similarly, the left total weight LMB is the sum of the wheel loads of the left-side tires on each axle of vehicle 100 as measured by wheel load sensor 3L, and can be considered as the weight of the left side of vehicle 100 as measured by wheel load sensor 3L. The left total weight LMC is the sum of the wheel loads of the left-side tires on each axle of vehicle 100 as measured by wheel load sensor 4L, and can be considered as the weight of the left side of vehicle 100 as measured by wheel load sensor 4L.

[0112] Vehicle 100, which has three axles, is as shown in Figure 8(B), The total weight on the left, LMA = LMA1 + LMA2 + LMA3, The total weight on the left is LMB = LMB1 + LMB2 + LMB3, The total weight on the left, LMC = LMC1 + LMC2 + LMC3.

[0113] The left-hand average weight LMav is the average of the left-hand total weights LMA, LMB, and LMC. That is, Left average weight LMav =(Left total weight LMA+Left total weight LMB+Left total weight LMC) / 3 That is the case.

[0114] As described above, the left total weights LMA, LMB, and LMC are the weights of the left side of vehicle 100 measured by individual wheel load sensors 2L to 4L, while the left average weight LMav is the average of the weights of the right side of vehicle 100 measured by individual wheel load sensors 2L to 4L. Therefore, the left total weights LMA, LMB, and LMC are the weights of the left side of vehicle 100 without considering the effects of vibration. The left average weight LMav is the weight of the left side of vehicle 100 with reduced effects of vibration compared to the left total weights LMA, LMB, and LMC.

[0115] The left-side weight ratio is the ratio of the total left-side weight LMA, LMB, and LMC of vehicle 100 measured by wheel load sensors 2L to 4L to the average left-side weight LMav. Specifically, the weight ratio for wheel load sensor 2L is LMA / LMav, the weight ratio for wheel load sensor 3L is LMB / LMav, and the weight ratio for wheel load sensor 4L is LMC / LMav.

[0116] If the measurement accuracy of wheel load sensor 2L is appropriate, the left-side weight ratio (LMA / LMav) of wheel load sensor 2L can be considered as the magnitude of the effect of vehicle vibration on the left-side weight (LMA) of vehicle 100 as measured by wheel load sensor 2L. Similarly, if the measurement accuracy of wheel load sensor 3L is appropriate, the left-side weight ratio (LMB / LMav) of wheel load sensor 3L can be considered as the magnitude of the effect of vehicle vibration on the left-side weight (LMB) of vehicle 100 as measured by wheel load sensor 3L. Furthermore, if the measurement accuracy of wheel load sensor 4L is appropriate, the left-side weight ratio (LMC / LMav) of wheel load sensor 4L can be considered as the magnitude of the effect of vehicle vibration on the left-side weight (LMC) of vehicle 100 as measured by wheel load sensor 4L.

[0117] In this modified axle load measuring device 1, the axle load calculation unit 21 uses the measurement signal from the wheel load sensor 2R to calculate the wheel load of the right-side tire of each axle of the vehicle 100 that traveled through the measurement section (RMA1 to RMA3 shown in Figure 8(A)). The axle load calculation unit 21 also uses the measurement signal from the wheel load sensor 2L to calculate the wheel load of the left-side tire of each axle of the vehicle 100 that traveled through the measurement section (LMA1 to LMA3 shown in Figure 8(B)).

[0118] Furthermore, the axle load calculation unit 21 uses the measurement signal from the wheel load sensor 3R to calculate the wheel load of the right-side tire of each axle of the vehicle 100 that traveled through the measurement section (RMB1 to RMB3 shown in Figure 8(A)). In addition, the axle load calculation unit 21 uses the measurement signal from the wheel load sensor 3L to calculate the wheel load of the left-side tire of each axle of the vehicle 100 that traveled through the measurement section (LMB1 to LMB3 shown in Figure 8(B)).

[0119] Furthermore, the axle load calculation unit 21 uses the measurement signal from the wheel load sensor 4R to calculate the wheel load of the right-side tire of each axle of the vehicle 100 that traveled through the measurement section (RMC1 to RMC3 shown in Figure 8(A)). The axle load calculation unit 21 also uses the measurement signal from the wheel load sensor 4L to calculate the wheel load of the left-side tire of each axle of the vehicle 100 that traveled through the measurement section (LMC1 to LMC3 shown in Figure 8(B)).

[0120] The vehicle weight calculation unit 22 calculates the total weight on the right (RMA, RMB, RMC shown in Figure 8(A)), the total weight on the left (LMA, LMB, LMC shown in Figure 8(B)), the average weight on the right (RMav shown in Figure 8(A)), and the average weight on the left (LMav shown in Figure 8(B)). In this example, the vehicle weight calculation unit 22 also obtains the sum of the average weight on the right (RMav) and the average weight on the left (LMav) of the vehicle 100 that traveled the measurement section (RMav + LMav) as the weight of the vehicle 100.

[0121] Furthermore, this modified axle load measuring device 1 can determine the uneven loading state of the vehicle 100 by comparing the right average weight RMav with the left average weight LMav.

[0122] The ratio calculation unit 23 calculates the right weight ratio (RMA / RMav, RMB / RMav, RMC / RMav shown in Figure 8(A)) for each wheel load sensor 2R to 4R, and the left weight ratio (LMA / LMav, LMB / LMav, LMC / LMav shown in Figure 8(B)) for each wheel load sensor 2L to 4L.

[0123] As in the example above, the right weight ratio may be RMav / RMA, RMav / RMB, RMav / RMC, and the left weight ratio may be LMav / LMA, LMav / LMB, LMav / LMC.

[0124] The determination unit 24 processes the statistical data recorded in the statistical DB 14 and determines whether the measurement accuracy is appropriate for each wheel load sensor 2R to 4R and 2L to 4L.

[0125] The determination unit 24 extracts statistical data (target statistical data) of the vehicles 100 used to determine whether the measurement accuracy of the wheel load sensors 2R to 4R and 2L to 4L is appropriate from the statistical DB 14. For example, the target statistical data may be statistical data of the vehicles 100 that traveled the measurement section during the set period, as in the example above, or it may be statistical data of the set number of vehicles.

[0126] The determination unit 24 generates a histogram of the number of vehicles 100 relative to the right weight ratio for each wheel load sensor 2R to 4R. The determination unit 24 also generates a histogram of the number of vehicles 100 relative to the left weight ratio for each wheel load sensor 2L to 4L.

[0127] As explained in the example above, in a wheel load sensor with appropriate measurement accuracy, the shape of the frequency distribution of weight ratios (right weight ratio or left weight ratio) approximates a normal distribution with a certain degree of variance. Conversely, in a wheel load sensor with inadequate measurement accuracy, the shape of the frequency distribution of weight ratios (right weight ratio or left weight ratio) does not approximate a normal distribution with a certain degree of variance.

[0128] The determination unit 24 determines whether the measurement accuracy is appropriate for each wheel load sensor 2R to 4R and 2L to 4L, based on the shape of the frequency distribution of weight ratios in that wheel load sensor 2R to 4R and 2L to 4L.

[0129] The axle load measuring device 1 in this modified example also performs the measurement process shown in Figure 5 and the measurement accuracy determination process shown in Figure 6, similar to the example described above. However, in this modified example, the processing for axle load sensors 2-4 in the example described above is replaced with processing for wheel load sensors 2R-4R and 2L-4L.

[0130] In this modified axle load measuring device 1, as in the example above, it is possible to determine whether the measurement accuracy of the axle load sensors 2-4 (wheel load sensors 2R-4R, 2L-4L) used to measure the weight of the moving vehicle 100 is appropriate, regardless of whether or not a special vehicle is in motion. Furthermore, the determination of whether the measurement accuracy of the wheel load sensors 2R-4R, 2L-4L is appropriate can be performed periodically or at times specified by the administrator.

[0131] Furthermore, this modified axle load measuring device 1 can also determine the uneven distribution of load on the vehicle 100 by comparing the right average weight RMav with the left average weight LMav.

[0132] Furthermore, the above example is a configuration in which the measurement accuracy of axle load sensors 2-4 (wheel load sensors 2R-4R, 2L-4L) is determined by whether the frequency distribution can be considered to be a normal distribution. The axle load measuring device 1 may also determine whether the measurement accuracy of axle load sensors 2-4 (wheel load sensors 2R-4R, 2L-4L) is appropriate by determining whether the weight ratio X, which is the peak in the frequency distribution, is between a predetermined upper limit ratio Y (for example, Y=1.1) and a lower limit ratio Z (for example, Z=0.9). Specifically, the determination unit 24, Upper limit ratio Y>weight ratio X>lower limit ratio Z If this is the case, it may be determined that the measurement accuracy is appropriate. In other words, the determination unit 24, Upper limit ratio Y>weight ratio X>lower limit ratio Z Otherwise, it may be determined that the measurement accuracy is inadequate.

[0133] Furthermore, the determination unit 24 may use both whether the frequency distribution described above is a normal distribution and the weight ratio X which is the peak in the frequency distribution to determine whether the measurement accuracy of the axle load sensors 2 to 4 (wheel load sensors 2R to 4R, 2L to 4L) is appropriate.

[0134] Furthermore, the above modified example may be configured to calculate the right weight ratio by dividing the total right weight measured by wheel load sensors 2R to 4R by the sum of the right average weight RMav and the left average weight LMav (RMav + LMav) for each wheel load sensor 2R to 4R. Similarly, the above modified example may be configured to calculate the left weight ratio by dividing the total left weight measured by wheel load sensors 2L to 4L by the sum of the right average weight RMav and the left average weight LMav (RMav + LMav) for each wheel load sensor 2L to 4L.

[0135] Furthermore, in this modified example as well, the measurement accuracy may be determined using 2 to 4 units of axial load sensors, similar to the example above. Specifically, each of MA1, MA2, MA3, MB1, MB2, MB3, MC1, MC2, and MC3 shown in Figure 3 can be used. MA1=RMA1+LMA1, MA2=RMA2+LMA2, MA3=RMA3+LMA3, MB1=RMB1+LMB1, MB2=RMB2+LMB2, MB3=RMB3+LMB3, MC1=RMC1+LMC1, MC2=RMC2+LMC2, MC3=RMC3+LMC3, Use the value calculated by [method].

[0136] In this case, similar to the example above, the total weight and weight ratio can be calculated for each of the axial load sensors 2 to 4 to determine whether the measurement accuracy is appropriate.

[0137] Furthermore, if there are axle load sensors 2-4 that are determined to have inadequate measurement accuracy, the frequency distribution described above may be generated for the pair of wheel load sensors that make up those axle load sensors 2-4, and the wheel load sensors with inadequate measurement accuracy may be identified. Alternatively, for example, the total weight on the right and the total weight on the left may be compared between the axle load sensors 2-4 that are determined to have inadequate measurement accuracy and the other axle load sensors 2-4 (axle load sensors 2-4 that are determined to have appropriate measurement accuracy), and the wheel load sensors with inadequate measurement accuracy may be identified. In addition, wheel load sensors with inadequate measurement accuracy may be identified using methods other than those described above for axle load sensors 2-4 that are determined to have inadequate measurement accuracy.

[0138] Furthermore, in the example described above, the statistical data was assumed to include total weight (in the modified example, total weight on the right, total weight on the left), weight ratio (in the modified example, weight ratio on the right, weight ratio on the left), and average weight (in the modified example, average weight on the right, average weight on the left). However, it is also possible to configure the system to omit these. In this case, the measurement accuracy determination process should be configured to calculate the total weight (in the modified example, total weight on the right, total weight on the left), weight ratio (in the modified example, weight ratio on the right, weight ratio on the left), and average weight (in the modified example, average weight on the right, average weight on the left) for each target statistical data extracted in s12. By configuring the system in this way, the storage capacity of the statistical DB14 can be reduced.

[0139] Furthermore, some of the components shown in Figure 2 (for example, the determination unit 24 and the ratio calculation unit 23) may be provided in a higher-level device, and the axle load measuring device 1 and the higher-level device may work together to perform the above processing. Also, the statistical data may be configured so that it does not include any of the items related to the vehicle ID, driving date, or driving time mentioned above.

[0140] Furthermore, this invention is not limited to the embodiments described above, and the components can be modified and implemented in practice without departing from the gist of the invention. Various inventions can also be formed by appropriately combining the multiple components disclosed in the embodiments. For example, some components may be removed from all the components shown in the embodiments. Furthermore, components from different embodiments may be combined as appropriate. Also, the measurement process shown in Figure 5 and the measurement accuracy determination process shown in Figure 6 are merely examples, and the order of each step may be changed as appropriate.

[0141] Furthermore, the correspondence between the configuration of this invention and the configuration of the embodiment described above can be described as follows. <Note> A sensor connection unit (12) receives measurement signals of the load from the tires of a passing vehicle (100), which are measured by multiple sensors (2-4) arranged in line with the direction of travel of the vehicle (100) on the road surface of the measurement section, For a vehicle (100) that has traveled through the measurement section, a ratio calculation unit (23) calculates the weight ratio by summing the weights corresponding to the load from the tires of the vehicle (100) that have passed through each of the sensors (2-4), and the average weight which is the average of the sums of the weights from each sensor (2-4). A weight measuring device (1) comprising: a determination unit (24) that determines whether the measurement accuracy of the sensors (2-4) is appropriate based on the weight ratio calculated for the sensors (2-4). [Explanation of symbols]

[0142] 1... Axle load measuring device 2-4... Axle load sensor 2R~4R, 2L~4L... Wheel load sensor 6, 7... Vehicle detection sensors 11…Control Unit 12... Axle load sensor connection part 13... Loop coil sensor connection part 14…Statistical database (Statistical DB) 15…Output section 21...Axle load calculation section 22... Vehicle weight calculation unit 23...Ratio calculation unit 24…Judgment section 100...vehicles

Claims

1. A sensor connection unit receives measurement signals of the load from the tires of passing vehicles, measured by multiple sensors arranged in line with the direction of vehicle travel on the road surface of the measurement section. For vehicles that have traveled through the measurement section, a ratio calculation unit calculates a weight ratio for each sensor by summing the weights corresponding to the load from the tires of the vehicles that have passed through that sensor, and the average weight which is the average of the sums of the total weights from each sensor. A weight measuring device comprising: a determination unit that determines whether the measurement accuracy of the sensor is appropriate based on the weight ratio calculated for the sensor.

2. The weight measuring device according to claim 1, wherein the determination unit determines whether the measurement accuracy of the sensor is appropriate based on the shape of the frequency distribution of the weight ratio calculated for the sensor.

3. The weight measuring device according to claim 2, wherein the determination unit determines whether the measurement accuracy of the sensor is appropriate based on the degree of symmetry of the shape of the frequency distribution of the weight ratio with respect to the peak of the frequency.

4. The weight measuring device according to claim 3, wherein the determination unit determines whether the measurement accuracy of the sensor is appropriate based on whether the degree of symmetry of the shape of the frequency distribution of the weight ratio exceeds a predetermined symmetry threshold.

5. The weight measuring device according to claim 2, wherein the determination unit determines whether the measurement accuracy of the sensor is appropriate based on the magnitude of the variance in the frequency distribution of the weight ratio.

6. The weight measuring device according to claim 5, wherein the determination unit determines whether the measurement accuracy of the sensor is appropriate based on whether the variance of the frequency distribution of the weight ratio is between a predetermined lower threshold and an upper threshold.

7. The weight measuring device according to any one of claims 1 to 6, wherein the sensor is pressed by the tires on both sides attached to the axle of a vehicle traveling through the measurement section.

8. The weight measuring device according to claim 7, further comprising an acquisition unit that acquires the average weight as the weight of a vehicle that traveled the measurement section.

9. The aforementioned sensors are arranged in two rows in the vehicle width direction. The sensor in one row is pressed by the tire on one side that is attached to the axle of the vehicle traveling through the measurement section. The weight measuring device according to any one of claims 1 to 6, wherein the sensor in the other row is pressed by the tire on the other side, which is attached to the axle of a vehicle traveling through the measurement section.

10. The weight measuring device according to claim 9, further comprising an acquisition unit that acquires the sum of the average weight measured by the sensor in one of the rows and the average weight measured by the sensor in the other row as the weight of the vehicle that traveled the measurement section.

11. A ratio calculation step involves processing measurement signals of the load from the tires of a passing vehicle, which are input to the sensor connection unit and measured by multiple sensors arranged in line with the direction of travel of the vehicle on the road surface of the measurement section, and for a vehicle that has traveled through the measurement section, calculating the ratio of the total weight, which is the sum of the weights corresponding to the load from the tires of the vehicle that passed each sensor, to the average weight, which is the average of the total weights of each sensor, as the weight ratio. A measurement accuracy determination method, in which a computer performs a determination step of determining whether the measurement accuracy of the sensor is appropriate based on the weight ratio calculated for the sensor.

12. A ratio calculation step involves processing measurement signals of the load from the tires of a passing vehicle, which are input to the sensor connection unit and measured by multiple sensors arranged in line with the direction of travel of the vehicle on the road surface of the measurement section, and for a vehicle that has traveled through the measurement section, calculating the ratio of the total weight, which is the sum of the weights corresponding to the load from the tires of the vehicle that passed each sensor, to the average weight, which is the average of the total weights of each sensor, as the weight ratio. A measurement accuracy determination program that causes a computer to perform a determination step of determining whether the measurement accuracy of the sensor is appropriate, based on the weight ratio calculated for the sensor.

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