JP7434030B2 - Deterioration detection device, deterioration detection system, deterioration detection method, weight measurement device, weight measurement method and program - Google Patents

Description

The present invention relates to a deterioration detection device, a deterioration detection system, a deterioration detection method, a weight measurement device, a weight measurement method, and a program.

Traditionally, bridges are visually inspected about once every five years. In order to further improve the safety of bridges, it is desirable, for example, to constantly monitor bridges, predict the future state of bridges based on the monitoring results, and manage bridges in a planned manner.

Patent Document 1 describes a technique for measuring the strain of a deck slab when a vehicle passes a bridge using a strain meter, and detecting the characteristics of the passing vehicle based on the measured strain. Patent Document 2 discloses that the distance between the axles of the vehicle is calculated by calculating the axle ratio of the vehicle from the strain waveform measured by a strain meter, and comparing the calculated axle ratio with the axle ratio registered in a database. , a technology for identifying vehicle speed and vehicle type is described. Patent Document 3 discloses that a temporary axle load value of a vehicle is calculated based on the distortion of the vertical ribs and horizontal ribs when the vehicle passes, and the temporary axle load value is corrected based on the vehicle weight value calculated based on the strain of the horizontal ribs. The technology to do so is described. Patent Document 4 describes a technique for detecting strain in a floor slab when a vehicle passes through a bridge, and calculating the weight of the vehicle based on the detected strain. Non-Patent Document 1 describes a technique for calculating the deflection characteristics of a bridge by installing an acceleration sensor under a rear wheel spring of a route bus.

JP2006-084404A JP2009-237805A JP2014-228480A JP 2017-106769 Publication

Fumiho Miyamoto et al., “Demonstration experiment of small and medium-sized bridge monitoring system using route buses,” Yamaguchi University Faculty of Engineering Research Report, Vol. 66 No. 2, March 2015

By the way, as bridges deteriorate, the strain that occurs when vehicles pass through them increases. However, it is difficult to easily and continuously measure the extent to which bridges are distorted due to the effects of deterioration without relying on personnel.

The present invention has been made in view of the above, and provides a deterioration detection device, a deterioration detection system, a deterioration detection method, a weight measurement device, a weight measurement method, and a program that easily and continuously detect deterioration of a bridge. The purpose is to

In order to solve the above-mentioned problems and achieve the object, a deterioration detection device according to the present invention detects, from a sensor provided on a bridge, a parameter representing a displacement in the traveling direction of a target portion of the bridge where the sensor is provided. a collection unit that collects time-series data of the bridge; an extraction unit that extracts specific partial data when the specific vehicle passes the bridge from the time-series data; An amplitude calculation unit that calculates an amplitude value of the amount of expansion and contraction of the bridge in the running direction, and a determination unit that determines that the bridge has deteriorated when the amplitude value becomes larger than a preset reference value. .

According to the present invention, deterioration of a bridge can be easily and continuously detected.

FIG. 1 is a diagram showing a deterioration detection system according to a first embodiment. FIG. 2 is a diagram showing the arrangement of sensors when a bridge is viewed from the side. FIG. 3 is a diagram showing the arrangement of sensors when the bridge is viewed from above. FIG. 4 is a diagram showing a sensor and a portion of the main girder of the bridge. FIG. 5 is a diagram showing the displacement detection device together with the first member and the second member. FIG. 6 is a diagram showing the functional configuration of the deterioration detection device. FIG. 7 is a diagram showing an example of time-series data of the amount of expansion and contraction in the traveling direction when a route bus passes a bridge. FIG. 8 is a diagram showing temporal changes in amplitude values and error ranges. FIG. 9 is a diagram showing a functional configuration of a deterioration detection device according to a modification. FIG. 10 is a flowchart showing the process flow of the deterioration detection device. FIG. 11 is a diagram showing a weight measurement system according to the second embodiment. FIG. 12 is a diagram showing the functional configuration of the weight measuring device. FIG. 13 is a diagram showing the relationship between the amplitude value and the weight of the test vehicle. FIG. 14 is a flowchart showing the flow of the related information correction process performed by the weight measuring device. FIG. 15 is a diagram showing the hardware configuration of the deterioration detection device and the weight measurement device.

Embodiments will be described below with reference to the drawings.

(First embodiment)
FIG. 1 is a diagram showing a deterioration detection system 10 according to the first embodiment. The deterioration detection system 10 outputs alarm information when a bridge deteriorates.

The deterioration detection system 10 includes a sensor 20, a transmitter 22, and a deterioration detection device 30.

The sensor 20 is provided at a predetermined target portion of the bridge. The sensor 20 detects a parameter representing a displacement in the traveling direction at the target portion of the bridge where the sensor 20 is installed. In this embodiment, the sensor 20 measures the amount of expansion and contraction in the traveling direction in the target portion of the bridge. The amount of expansion/contraction is, for example, a change in distance of several nanometers to several hundred nanometers between two points with a distance of several tens of centimeters.

Note that the sensor 20 may detect other physical quantities instead of the amount of expansion/contraction in the running direction, as long as it can detect a parameter representing displacement in the running direction. For example, the sensor 20 may be a strain gauge that detects strain in the traveling direction in a target portion of a bridge. Further, for example, the sensor 20 may be a vibration meter that detects the magnitude of the natural frequency in the traveling direction of the target portion of the bridge or the magnitude of the natural frequency in the vertical direction of the target portion of the bridge.

The sensor 20 continuously detects a parameter (for example, the amount of expansion/contraction) representing displacement in the traveling direction of the target portion of the bridge at predetermined time intervals. For example, sensor 20 detects a parameter every few milliseconds. The sensor 20 continuously detects parameters at predetermined time intervals, for example, during a period when the power is turned on. The sensor 20 may continuously detect parameters at predetermined time intervals all the time (for example, 24 hours a day).

The transmitting device 22 transmits the parameters detected by the sensor 20 to the deterioration detecting device 30 via the network. The network may be wired, wireless, or a mixture of wired and wireless. The network is, for example, a LAN (Local Area Network), a VPN (Virtual Private Network), or a WAN (Wide Area Network) in which a LAN is connected via a router. The network may also include the Internet, telephone communication lines, or the like.

The deterioration detection device 30 receives time-series data of parameters representing the displacement in the traveling direction of the target portion of the bridge, which is transmitted from the transmitting device 22 via the network. The deterioration detection device 30 determines whether the bridge has deteriorated based on the received parameter time series data. When the deterioration detection device 30 determines that the bridge has deteriorated, it outputs alarm information to, for example, an administrator or an information processing device held by the administrator.

The deterioration detection device 30 is a computer such as a server device that can be connected to a network. The deterioration detection device 30 may be a single computer, or may be configured by a plurality of computers like a cloud system.

Note that the deterioration detection system 10 may have a configuration that does not include the transmitting device 22. In this case, the deterioration detection device 30 directly acquires from the sensor 20 a parameter representing the displacement in the traveling direction of the target portion of the bridge. Further, in this case, the deterioration detection device 30 may be provided near the sensor 20, that is, near the bridge.

FIG. 2 is a diagram showing the arrangement of the sensors 20 when the bridge is viewed from the side. FIG. 3 is a diagram showing the arrangement of the sensors 20 when the bridge is viewed from above. The sensor 20 is attached, for example, to an end of the bridge rather than the center in the traveling direction. The sensor 20 is attached, for example, to a lower surface of a bridge near an abutment. Thereby, a worker can easily attach the sensor 20 to the bridge even after the bridge is completed. Note that the sensor 20 may be attached to any position in the traveling direction on the bridge. For example, the sensor 20 may be attached to the center of the bridge in the travel direction, although attachment may be difficult depending on the operator.

FIG. 4 is a diagram showing the sensor 20 and a portion of the main girder 54 of the bridge. The sensor 20 measures the amount of change (expansion/contraction amount) in the distance between the first point 62 and the second point 64 on the lower surface 56 of the main girder 54 of the bridge.

The first point 62 and the second point 64 are at the same position in the width direction of the bridge, but at different positions in the traveling direction. The distance between the first point 62 and the second point 64 is, for example, about several tens of centimeters. In the example of FIG. 4, the distance between the first point 62 and the second point 64 is 35 centimeters. The sensor 20 measures the amount of change (expansion/contraction) in the distance between the first point 62 and the second point 64 in the running direction, for example, in units of several nanometers to several hundred nanometers.

The sensor 20 includes a first member 66, a second member 68, and a displacement detection device 70.

The first member 66 is a cantilever beam having a support portion 66a and a beam portion 66b. One end of the support portion 66a is a fixed end 66c fixed to the first point 62. The support portion 66 a extends a predetermined distance downward from the first point 62 in a direction perpendicular to the lower surface 56 of the main beam 54 . The beam portion 66b extends a predetermined distance from the end of the support portion 66a opposite to the fixed end 66c toward the second point 64 in the traveling direction. The end of the beam portion 66b that is not connected to the support portion 66a is a free end 66d that is not connected to any member. In this embodiment, the free end 66d of the first member 66 is located approximately in the vicinity of the center of the line connecting the first point 62 and the second point 64.

The second member 68 is a cantilever beam having a support portion 68a and a beam portion 68b. One end of the support portion 68a is a fixed end 68c fixed to the second point 64. The support portion 68 a extends a predetermined distance downward from the second point 64 in a direction perpendicular to the lower surface 56 of the main beam 54 . The beam portion 68b extends a predetermined distance from the end of the support portion 68a opposite to the fixed end 68c toward the first point 62 in the running direction. The end of the beam portion 68b that is not connected to the support portion 68a is a free end 68d that is not connected to any member. In this embodiment, the free end 68d of the second member 68 is arranged approximately in the vicinity of the center of the line connecting the first point 62 and the second point 64.

Here, the free end 66d of the first member 66 and the free end 68d of the second member 68 are arranged at overlapping positions in the running direction without mechanical interference. Thereby, the free end 66d of the first member 66 and the free end 68d of the second member 68 are arranged at positions facing each other in a direction perpendicular to the lower surface 56 of the main beam 54. When the distance between the first point 62 and the second point 64 changes, the relative positions of the free end 66d of the first member 66 and the free end 68d of the second member 68 shift in the running direction.

Note that the sensor 20 shown in FIG. 4 has a configuration in which both the first member 66 and the second member 68 are cantilever beams. However, the second member 68 may be a cantilever beam, and the first member 66 may not be a cantilever beam. In this case, the second member 68 is arranged at a position where the free end 68d overlaps at least a portion of the first member 66 in the running direction without mechanically interfering with it. Even with such a configuration, when the distance between the first point 62 and the second point 64 changes, the relative position of the free end 68d of the first member 66 and the second member 68 changes in the running direction. It shifts.

The displacement detection device 70 is provided at a portion where the free end 66d of the first member 66 and the free end 68d of the second member 68 are opposed to each other. The displacement detection device 70 detects the relative positional displacement between the free end 66d of the first member 66 and the free end 68d of the second member 68. Then, the displacement detection device 70 outputs the detected displacement as an amount of expansion/contraction between two points in the traveling direction of the bridge.

FIG. 5 is a diagram showing the displacement detection device 70 together with the first member 66 and the second member 68. Displacement detection device 70 includes an optical element 72 and a detector 74.

The optical element 72 is attached to either the free end 66d of the first member 66 or the free end 68d of the second member 68. The detector 74 is attached to the other of the free end 66d of the first member 66 and the free end 68d of the second member 68, to which the optical element 72 is not attached.

The optical element 72 is an optical member whose amount of reflected light (or amount of transmitted light) changes depending on the irradiation position of light with respect to the traveling direction. For example, the optical element 72 is a mirror whose surface is coated with a plurality of light absorbing materials (stripes) at predetermined intervals in the running direction. Further, the optical element 72 may be a diffraction grating in which a plurality of optical slits (stripe) are formed at predetermined intervals in the running direction.

Detector 74 includes a half mirror 76, a light emitting section 78, a light receiving section 80, and a detection circuit 82. The half mirror 76 reflects a part of the irradiated light and transmits the other part.

The light emitting unit 78 irradiates light onto the optical element 72 via the half mirror 76 . The light receiving section 80 receives the light reflected by the optical element 72 via the half mirror 76. The detection circuit 82 outputs a signal representing the displacement of the relative position between the first member 66 and the second member 68 based on the change in the amount of light detected by the light receiving section 80 as an amount of expansion and contraction.

The position of the light irradiated onto the optical element 72 shifts in the running direction in accordance with the shift in the relative positions of the first member 66 and the second member 68 in the running direction. Since stripes are formed in the optical element 72 in the running direction, the amount of reflected light from the optical element 72 increases or decreases depending on the shift of the light irradiation position in the running direction. Specifically, when the position of the light irradiated onto the optical element 72 shifts by the stripe interval, the amount of light reflected by the optical element 72 increases or decreases one cycle. Therefore, for example, the detection circuit 82 can obtain the amount of change in the relative position between the first member 66 and the second member 68 by counting the increase or decrease in the signal output from the light receiving section 80.

Further, the displacement detection device 70 may include two optical elements 72 whose stripes are shifted by 1/4 period from each other, and two light emitting sections 78 and two light receiving sections 80 corresponding to the two optical elements 72. Thereby, the two light receiving sections 80 can output two periodic signals whose phases are shifted by 1/4 period with respect to a change in the relative position between the first member 66 and the second member 68. Therefore, for example, the detection circuit 82 detects, based on the values of the two signals, the direction in which the relative positions of the first member 66 and the second member 68 change, and the direction of change in the relative position of the first member 66 and the second member 68 at intervals shorter than the period of the stripes. The amount of change in the relative position with respect to the second member 68 can be detected.

Furthermore, in the example of FIG. 5, the optical element 72 is configured to reflect light. Alternatively, the optical element 72 may be configured to transmit light. In this case, the amount of transmitted light in the optical element 72 changes depending on the irradiation position of the light with respect to the traveling direction. For example, the optical element 72 may be made of glass or plastic whose surface is coated with a plurality of light absorbing materials (stripes) at predetermined intervals in the running direction. In such a case, the light receiving section 80 receives the light that has passed through the optical element 72.

Further, the detector 74 may have a configuration that does not include the half mirror 76. FIG. 9 is a diagram showing the arrangement of the light emitting section 78 and the light receiving section 80 in the detector 74 that does not include the half mirror 76. Here, it is assumed that the detector 74 is provided on the first member 66. Further, it is assumed that the optical element 72 is provided on the second member 68. The position of the first member 66 facing the center of the optical element 72 in the width direction is defined as P. In such a case, the light emitting section 78 is arranged at a position shifted from P in the width direction by a predetermined distance in the first member 66. Further, the light receiving section 80 is arranged at a position shifted from P by a predetermined distance in the width direction on the opposite side to the light emitting section 78. The light emitting section 78 emits light in a direction toward the center of the optical element 72 in the width direction. The optical element 72 receives light from the light emitting section 78 at a predetermined angle, and reflects the incident light toward the light receiving section 80 . The light receiving unit 80 then receives the light reflected by the optical element 72. Such a detector 74 can have a similar function to the configuration shown in FIG.

The displacement detection device 70 having such a configuration can be attached to the lower surface 56 of the main girder 54 in the bridge. For example, the displacement detection device 70 can be attached from the outside without embedding an expandable member in the bridge like a strain gauge. Thereby, the displacement detection device 70 can be attached to a completed bridge later. Furthermore, the displacement detection device 70 can be installed without reducing the strength of the bridge. Furthermore, the displacement detection device 70 can be easily maintained even after installation.

Further, the displacement detection device 70 having such a configuration uses a cantilever beam to detect a change in the distance between two points using an optical sensor. Thereby, the displacement detection device 70 can accurately detect extremely small expansion and contraction in a bridge using a simple configuration and low-cost members.

FIG. 6 is a diagram showing the functional configuration of the deterioration detection device 30. The deterioration detection device 30 includes a collection section 112, a storage section 114, an extraction section 116, an amplitude calculation section 118, a determination section 119, and an alarm output section 120.

The collection unit 112 collects time-series data of parameters representing displacement in the traveling direction at the target portion of the bridge where the sensor 20 is installed, from the sensor 20 installed on the bridge. In this embodiment, the collection unit 112 acquires time-series data of parameters via the network. Furthermore, in this embodiment, the parameter is the amount of expansion and contraction in the running direction in the target portion. In the parameter time series data, the detected time and the parameter are associated with each other.

The storage unit 114 stores time-series data of parameters collected by the collection unit 112.

The extraction unit 116 extracts specific partial data, which is partial data when the specific vehicle passes a bridge, from the parameter time series data stored in the storage unit 114. For example, the extraction unit 116 extracts partial time series data when a specific vehicle passes a bridge from the parameter time series data, and outputs the extracted partial time series data as specific partial data.

The specific vehicle is, for example, a vehicle that regularly passes a bridge, and passes the bridge at substantially the same speed and with substantially the same weight each time. For example, the specific vehicle is a route bus. Route buses run on a daily basis according to a predetermined timetable. Therefore, the route bus is scheduled to pass the bridge at a predetermined time every day. Furthermore, the specific vehicle may be, for example, a garbage truck. A garbage truck has a travel route and a predetermined time. Therefore, garbage trucks are scheduled to pass the bridge at a predetermined time on the garbage collection day.

The waveform pattern of the amount of expansion and contraction when a specific vehicle passes a bridge is almost the same each time. Therefore, the extraction unit 116 may extract specific partial data from the time-series data of the parameters using, for example, a pre-trained neural network. In this case, the neural network undergoes a learning process using training data showing the waveform pattern of a specific vehicle. Further, the extraction unit 116 may extract specific partial data from the parameter time series data by pattern matching the waveform pattern representing the specific vehicle with the time series data.

Each time the extraction unit 116 extracts the specific portion data, the amplitude calculation unit 118 calculates the amplitude value of the amount of expansion and contraction of the bridge in the running direction when the specific vehicle passes, based on the extracted specific portion data. For example, when the parameter represents the amount of expansion and contraction of the target portion, the amplitude calculation unit 118 calculates the difference between the maximum value and the minimum value in the extracted specific portion data as the amplitude value.

When the parameter is not the amount of expansion/contraction of the target portion, the amplitude calculation unit 118 may output a value that is correlated with the amplitude value of the amount of expansion/contraction of the target portion as the amplitude value. For example, when the parameter is the magnitude of the natural frequency, the amplitude calculation unit 118 may calculate the difference between the maximum value and the minimum value in the extracted specific partial data as the amplitude value.

The determination unit 119 compares the calculated amplitude value with a preset reference value every time the amplitude calculation unit 118 calculates the amplitude value. Then, when the amplitude value becomes larger than the reference value, the determination unit 119 determines that the bridge has deteriorated.

The determination unit 119 may calculate a moving average value of the amplitude values of the most recent predetermined number of samples, and determine that the bridge has deteriorated when the moving average value becomes larger than a reference value. Further, the determination unit 119 executes predetermined filtering processing such as noise removal processing on the amplitude values of the plurality of samples, and if the result of the filtering processing becomes larger than the reference value, the bridge is deteriorated. It may be determined that the Note that the determination unit 119 may have a plurality of different reference values set in advance. The determining unit 119 may determine that the bridge has deteriorated each time the amplitude value becomes larger than the respective reference value.

When it is determined that the bridge has deteriorated, the alarm output unit 120 outputs alarm information indicating that the bridge has deteriorated. Note that when a plurality of different reference values are preset in the determination unit 119, the alarm output unit 120 generates an alarm including level information representing the magnitude of the reference value each time the amplitude value becomes larger than each reference value. Information may also be obtained. Thereby, the alarm output unit 120 can notify the administrator and the like of the level of deterioration of the bridge.

FIG. 7 is a diagram showing an example of time-series data of the amount of expansion and contraction in the traveling direction when a route bus passes a bridge. When a vehicle passes through a bridge, the bridge changes in the direction of travel, in the direction of elongation, extends to the maximum value, then changes in the direction of contraction, and after contracting to the minimum value, changes such as returning to the original state. do.

When vehicles of the same type pass a bridge with approximately the same weight and at approximately the same speed, the waveforms of the amount of expansion and contraction of the target portions of the bridge will be approximately the same if the degree of deterioration of the bridge is the same. For example, when vehicles of the same type pass a bridge with almost the same weight and speed, the amplitude value (the difference between the maximum value and the minimum value) and the change time (the difference between the maximum and minimum values) in the waveform of the amount of expansion and contraction, If the degree of deterioration of the bridge is the same, the period from the time to the change end time will be almost the same. Note that FIG. 7 shows an example in which the sensor 20 is provided at the end of the bridge on the vehicle entry side. The sensor 20 may be provided at the end of the bridge on the vehicle exit side. In this case, the bridge changes in the opposite way to that in FIG. That is, in this case, the bridge changes in the direction of contraction with respect to the traveling direction, shrinks to the minimum value, changes in the direction of extension, and after reaching the maximum value, returns to the original state.

FIG. 8 is a diagram showing temporal changes in amplitude values and error ranges of amplitude values.

Bridges deteriorate over time. When the deterioration of a bridge progresses, the amplitude value of the amount of expansion and contraction increases even when vehicles of the same type pass through the bridge with approximately the same weight and at approximately the same speed. That is, when vehicles of the same type pass a bridge with substantially the same weight and substantially the same speed, the amplitude value of the amount of expansion and contraction of the target portion of the bridge increases as time passes.

Furthermore, even when vehicles of the same type pass through a bridge with substantially the same weight and speed, errors occur in the amplitude value of the amount of expansion and contraction depending on the surrounding environment, measurement conditions, and the like. Furthermore, if the specific vehicle is a route bus, the number of passengers and passing speed also vary depending on the day. The amplitude value of the amount of expansion and contraction calculated when a specific vehicle passes a bridge includes errors due to weight and passing speed.

However, if we refer to the experimental results in Non-Patent Document 1, for example, as shown in FIG. The amount is expected to be sufficiently large. Therefore, when a specific vehicle such as a route bus passes through a bridge, if the amplitude value of the amount of expansion and contraction of the target part becomes larger than a preset reference value, the reference value will be changed to an error in the amplitude value at the start of measurement. If it is set sufficiently larger than the distribution range, it can be said that the bridge has deteriorated since the beginning of the measurement.

Therefore, the deterioration detection device 30 can determine that the bridge has deteriorated when the amplitude value of the amount of expansion and contraction in the traveling direction of the bridge when the specific vehicle passes becomes larger than the reference value.

FIG. 9 is a diagram showing a functional configuration of a deterioration detection device 30 according to a modification.

The deterioration detection device 30 includes one or more of the passage time acquisition unit 122, the passage detection information acquisition unit 124, the scheduled time estimation unit 126, the date acquisition unit 132, the passage speed acquisition unit 134, and the weight acquisition unit 136. Further provision may be made.

If the specific vehicle is scheduled to pass the bridge at the same first time every day, the passing time acquisition unit 122 obtains information indicating the first time, which is the passing time of the specific vehicle, from an external device or the like. For example, when the specific vehicle is a route bus, timetable information of the route bus, etc. may be acquired, and the first time may be calculated based on the acquired timetable information. Then, when the passage time acquisition unit 122 acquires the first time, the extraction unit 116 extracts specific partial data in the time series data of the parameters based on the acquired first time. For example, the extraction unit 116 cuts out a predetermined time range before and after the first time in the time series data of the parameters, and extracts specific partial data from the cut out range. As a result, the extraction unit 116 only needs to perform the extraction process on the partial data during a partial time period in the time series data of the parameters, so that the specific partial data can be extracted with high accuracy with a small amount of processing.

The passage detection information acquisition unit 124 acquires a detection signal detected by a passage detection device that detects that a specific vehicle is passing through a bridge. For example, the passage detection device acquires image data from a camera that images a vehicle passing through a bridge, analyzes the acquired image data, and determines whether a specific vehicle is passing through the bridge. When the passage detection device determines that the specific vehicle is passing the bridge, it provides the deterioration detection device 30 with a detection signal indicating that the specific vehicle is passing the bridge. Further, for example, the passage detection device may be a receiving device that receives identification information for identifying the specific vehicle via a wireless signal from a wireless communication device provided in the specific vehicle. In this case, the passage detection device is provided near the bridge, and when receiving identification information from the specific vehicle, provides the deterioration detection device 30 with a detection signal indicating that the specific vehicle is passing through the bridge.

When the passage detection information acquisition unit 124 receives detection information indicating that a specific vehicle is passing through a bridge from the passage detection device, it provides the extraction unit 116 with time information indicating the time at which the detection information was received. The extraction unit 116 extracts specific partial data in the time series data of the parameters based on the received time information. For example, the extraction unit 116 cuts out a predetermined time range before and after the time indicated by the time information received from the time series data of the parameters, and extracts specific partial data from the cut out range. As a result, the extraction unit 116 only needs to perform the extraction process on the partial data during a partial time period in the time series data of the parameters, so that the specific partial data can be extracted with high accuracy with a small amount of processing.

The scheduled time estimation unit 126 acquires passage information indicating that the specific vehicle has passed a predetermined first position. For example, when the specific vehicle is a route bus, the first position is a bus stop immediately before a bridge on the bus route or a specific bus stop. If the specific vehicle is a route bus, the scheduled time estimation unit 126 receives passage information indicating that the specific vehicle has passed the first position. The passage information is transmitted, for example, from a transmitter provided at a bus stop, a transmitter provided on a route bus, a management device that manages operation information of a route bus, or the like.

When receiving the passage information, the scheduled time estimating unit 126 estimates the scheduled time when the specific vehicle will pass the bridge based on the passing information and the predicted travel time of the specific vehicle from the first position to the bridge. For example, the scheduled time estimating unit 126 calculates, as the scheduled time, the time when the passing information is received plus the predicted travel time.

The scheduled time estimation unit 126 then provides the estimated scheduled time to the extraction unit 116. The extraction unit 116 extracts specific partial data in the time series data of parameters based on the received scheduled time. For example, the extraction unit 116 cuts out a predetermined time range before and after the time indicated by the scheduled time from the parameter time series data, and extracts specific partial data from the cut out range. As a result, the extraction unit 116 only needs to perform the extraction process on the partial data during a partial time period in the time series data of the parameters, so that the specific partial data can be extracted with high accuracy with a small amount of processing.

The date acquisition unit 132 acquires date information indicating a preset date. The date acquisition unit 132 may acquire the day of the week as the date. In this case, the specific vehicle is a vehicle that is scheduled to pass the bridge at the same time every day. The date acquisition unit 132 provides the acquired date information to the amplitude calculation unit 118.

When date information is acquired, the amplitude calculation unit 118 calculates an amplitude value based on specific partial data extracted from the time series data on the date indicated by the acquired date information. For example, the amplitude calculation unit 118 calculates an amplitude value based on specific partial data extracted from time series data on a weekday date, and calculates an amplitude value based on specific partial data extracted from time series data on a holiday date. do not. For example, if the specific vehicle is a route bus, the number of passengers may vary greatly between weekdays and holidays, and as a result, the weight may vary greatly. Further, when the specific vehicle is a route bus, the degree of traffic congestion differs between weekdays and holidays, and the speed at which the vehicle passes through a bridge may vary greatly. Therefore, when the specific vehicle is a route bus, the waveform characteristics of the amplitude value of the expansion/contraction amount may differ greatly between weekdays and holidays.

Therefore, by calculating the amplitude value based on the specific partial data extracted from the time-series data on the preset date, the amplitude calculation unit 118 can calculate the amplitude value when the same type of vehicle has approximately the same weight and approximately the same speed. It is possible to output the amplitude value of the amount of expansion/contraction when passing through. Thereby, the deterioration detection device 30 can accurately determine whether or not the bridge has deteriorated.

The time zone acquisition unit 133 acquires time zone information indicating a preset time zone within a day. The time zone acquisition unit 133 may acquire information such as, for example, from 5:00 a.m. to 7:00 a.m. as the time zone. The time zone acquisition section 133 provides the acquired time zone information to the amplitude calculation section 118.

When the time zone information is acquired, the amplitude calculation unit 118 calculates an amplitude value based on the specific partial data extracted from the time series data in the time zone indicated by the acquired time zone information. For example, the amplitude calculation unit 118 calculates an amplitude value based on specific partial data extracted from time series data in a specified time period, and calculates an amplitude value based on specific partial data extracted from time series data outside the specified time period. Do not calculate the amplitude value based on For example, the degree of traffic congestion varies depending on the time of day, and the speed at which a particular vehicle passes a bridge may vary greatly. Therefore, the waveform characteristics of the amplitude value of the amount of expansion and contraction may vary greatly depending on the time of day.

Therefore, by calculating the amplitude value based on the specific partial data extracted from the time series data in a preset time period, the amplitude calculation unit 118 can calculate the amplitude value when the same type of vehicle has approximately the same weight and approximately the same speed. It is possible to output the amplitude value of the amount of expansion/contraction when passing through. Thereby, the deterioration detection device 30 can accurately determine whether or not the bridge has deteriorated.

The passing speed acquisition unit 134 acquires the speed of a specific vehicle when passing through a bridge. For example, the passing speed acquisition unit 134 may acquire log data measured by a speedometer provided in the specific vehicle. Then, the passing speed acquisition unit 134 may acquire the speed at the time when the specific vehicle passed the bridge from the log data. The passing speed acquisition unit 134 provides the amplitude calculation unit 118 with speed information indicating the acquired speed.

When speed information is acquired, the amplitude calculation unit 118 calculates an amplitude value based on specific partial data extracted from time series data in which the speed of the specific vehicle when passing the bridge is within a preset range. Thereby, the amplitude calculation unit 118 can output the amplitude value of the amount of expansion and contraction when vehicles of the same type pass at approximately the same speed. Therefore, the deterioration detection device 30 can determine with higher accuracy whether or not the bridge has deteriorated.

The weight acquisition unit 136 acquires the weight of a specific vehicle when passing through a bridge. For example, garbage trucks are commonly equipped with scales to measure their own weight. The weight acquisition unit 136 may acquire log data measured by a weight scale provided in a specific vehicle such as a garbage truck. Then, the weight acquisition unit 136 may acquire the weight at the time when the specific vehicle passed the bridge from the log data. Furthermore, when the specific vehicle is a route bus, the weight acquisition unit 136 acquires, for example, the number of passengers at a bus stop immediately before a bridge on the bus route or a specific bus stop, and estimates the weight based on the acquired number of passengers. Good too. Then, the weight acquisition unit 136 provides weight information indicating the acquired weight to the amplitude calculation unit 118.

When the weight information is acquired, the amplitude calculation unit 118 calculates the amplitude value based on the specific partial data extracted from the time series data in which the weight of the specific vehicle when passing the bridge is within a preset range. Thereby, the amplitude calculation unit 118 can output the amplitude value of the amount of expansion and contraction when vehicles of the same type pass with substantially the same weight. Therefore, the deterioration detection device 30 can determine with higher accuracy whether or not the bridge has deteriorated.

FIG. 10 is a flowchart showing the process flow of the deterioration detection device 30. The deterioration detection device 30 executes processing according to the flow shown in FIG. 10, for example.

First, in S11, the deterioration detection device 30 determines whether a route bus, which is a specific vehicle, has passed a bus stop (or a specific bus stop) immediately before a bridge on the bus route. If the previous bus stop has not been passed (No in S11), the deterioration detection device 30 waits for processing in S11. If the previous bus stop has been passed (Yes in S11), the deterioration detection device 30 advances the process to S12.

In S12, the deterioration detection device 30 estimates the scheduled time when the vehicle passes through the bridge. Subsequently, in S13, the deterioration detection device 30 determines whether the time has come a predetermined time before the scheduled time. If the time has not reached the predetermined time before the scheduled time (No in S13), the deterioration detection device 30 waits for processing in S13. If the time is a predetermined time before the scheduled time (Yes in S13), the deterioration detection device 30 advances the process to S14.

In S14, the deterioration detection device 30 turns on the power of the sensor 20. For example, the deterioration detection device 30 provides an instruction signal to the sensor 20 via wireless communication or the like to turn on the power.

Subsequently, in S15, the deterioration detection device 30 receives and stores time-series data of the parameters detected by the sensor 20. For example, the deterioration detection device 30 receives and stores time-series data on the amount of expansion and contraction of a target portion of a bridge.

Subsequently, in S16, the deterioration detection device 30 determines whether the time has come a predetermined time after the scheduled time. If the time has not reached the predetermined time after the scheduled time (No in S16), the deterioration detection device 30 waits for processing in S16. If the time comes a predetermined time after the scheduled time (Yes in S16), the deterioration detection device 30 advances the process to S17.

In S17, the deterioration detection device 30 turns off the power to the sensor 20. For example, the deterioration detection device 30 provides an instruction signal to the sensor 20 via wireless communication or the like to turn off the power.

Subsequently, in S18, the deterioration detection device 30 extracts specific partial data, which is partial data when a route bus, which is a specific vehicle, passes a bridge from the stored parameter time series data. Subsequently, in S19, the deterioration detection device 30 calculates, from the extracted specific portion data, the amplitude value of the amount of expansion and contraction of the bridge in the running direction when the specific vehicle, which is the route bus, passes. For example, when the parameter represents the amount of expansion and contraction of the target portion, the deterioration detection device 30 calculates the difference between the maximum value and the minimum value in the extracted specific portion data as an amplitude value. Subsequently, in S20, the deterioration detection device 30 stores the calculated amplitude value.

Subsequently, in S21, the deterioration detection device 30 determines whether the calculated amplitude value is larger than a reference value. If the amplitude value is not larger than the reference value (No in S21), the deterioration detection device 30 returns the process to S11 and repeats the process from S11. If the amplitude value is larger than the reference value (Yes in S21), the deterioration detection device 30 advances the process to S22.

In S22, the deterioration detection device 30 outputs alarm information indicating that the bridge has deteriorated to, for example, the administrator or an information processing device held by the administrator. When S22 ends, the deterioration detection device 30 ends this flow. Note that the deterioration detection device 30 may increase the reference value by a predetermined amount after S22 and return the process to S11.

As described above, the deterioration detection system 10 according to the first embodiment determines the amount of expansion and contraction of the bridge in the running direction when the specific vehicle passes, based on the specific portion data when the specific vehicle such as a route bus passes the bridge. An amplitude value is calculated, and if the calculated amplitude value becomes larger than a preset reference value, it is determined that the bridge has deteriorated, and alarm information indicating that the bridge has deteriorated is output. Thereby, according to the deterioration detection system 10 according to the first embodiment, deterioration of a bridge can be detected easily and continuously for a long period of time. Therefore, according to the deterioration detection system 10 according to the first embodiment, the condition of the bridge can be constantly monitored at low cost and the bridge can be managed in a planned manner.

(Second embodiment)
Next, a weight measurement system 210 according to a second embodiment will be described. In the description of the second embodiment, the same reference numerals are given to elements having substantially the same configuration as those of the first embodiment, and detailed description thereof will be omitted except for differences.

FIG. 11 is a diagram showing a weight measurement system 210 according to the second embodiment. The weight measurement system 210 accurately measures the weight of a vehicle passing over a bridge while correcting related information according to the deterioration of the bridge.

Weight measurement system 210 includes a sensor 20, a transmitter 22, and a weight measurement device 230.

The weight measuring device 230 receives time-series data of parameters representing the displacement in the traveling direction of the target portion of the bridge, which is transmitted from the transmitting device 22 via the network. The weight measurement device 230 calculates a vehicle amplitude value representing an amplitude value of the amount of expansion/contraction in the travel direction of the bridge when the vehicle passes, based on the received time series data of parameters. Then, the weight measuring device 230 calculates the weight of the vehicle based on the relationship information representing the correspondence between the amplitude value and the weight and the calculated vehicle amplitude value. Furthermore, if the weight measuring device 230 determines that the bridge has deteriorated, it corrects the relationship information representing the correspondence between the amplitude value and the weight.

The weight measuring device 230 is a computer such as a server device that can be connected to a network. The weight measuring device 230 may be one computer, or may be configured by multiple computers like a cloud system.

Note that the weight measurement system 210 may be configured without the transmitter 22. In this case, the weight measuring device 230 directly obtains a parameter representing the displacement in the traveling direction of the target portion of the bridge from the sensor 20. Furthermore, in this case, the weight measuring device 230 may be provided near the sensor 20, that is, near the bridge.

FIG. 12 is a diagram showing the functional configuration of the weight measuring device 230. The weight measurement device 230 includes a collection section 112, a storage section 114, a vehicle extraction section 242, a vehicle amplitude calculation section 244, a related information storage section 246, a weight calculation section 248, an extraction section 116, and an amplitude calculation section. 118 and a correction section 250.

The collection unit 112 and the storage unit 114 have the same functions and configurations as in the first embodiment.

The vehicle extraction unit 242 extracts vehicle partial data, which is partial data when the vehicle passes a bridge, from the parameter time series data stored in the storage unit 114. Here, the vehicle is not limited to a specific vehicle such as a route bus, but may be any type of vehicle.

For example, the vehicle extraction unit 242 extracts partial time series data when a vehicle passes a bridge from the parameter time series data, and outputs the extracted partial time series data as vehicle partial data.

The extraction unit 116 may extract the vehicle partial data from the time series data of the parameters using, for example, a pre-trained neural network. In this case, the neural network undergoes a learning process using training data showing waveform patterns of various types of vehicles. Further, the extraction unit 116 may extract vehicle partial data from the parameter time series data by performing pattern matching between a waveform pattern representing a general vehicle and the time series data.

Every time the vehicle extraction unit 242 extracts vehicle partial data, the vehicle amplitude calculation unit 244 calculates a vehicle amplitude value representing the amplitude value of the amount of expansion and contraction in the traveling direction of the bridge when the vehicle passes, based on the extracted vehicle partial data. calculate. For example, when the parameter represents the amount of expansion and contraction of the target portion, the vehicle amplitude calculation unit 244 calculates the difference between the maximum value and the minimum value in the extracted vehicle portion data as the vehicle amplitude value.

When the parameter is not the amount of expansion/contraction of the target portion, the vehicle amplitude calculation unit 244 may output a value that is correlated with the amplitude value of the amount of expansion/contraction of the target portion as the vehicle amplitude value. For example, when the parameter is the magnitude of the natural frequency, the vehicle amplitude calculation unit 244 may calculate the difference between the maximum value and the minimum value in the extracted vehicle partial data as the vehicle amplitude value.

The relational information storage unit 246 stores relational information representing the correspondence between the amplitude value and the weight of the vehicle.

The amplitude value of the amount of expansion and contraction of the bridge in the traveling direction when the vehicle passes through the bridge is correlated with the weight of the vehicle. More specifically, the amplitude value of the amount of expansion and contraction of the bridge in the traveling direction when the vehicle passes the bridge increases in accordance with the weight of the vehicle. Therefore, an administrator or the like generates in advance relational information representing the correspondence between the amplitude value and the weight of a vehicle passing over the bridge, and stores it in the relational information storage unit 246.

For example, an administrator or the like may generate the relational information by driving test vehicles of various weights on a bridge and measuring the correspondence between the weight of the vehicle and the amplitude value. Additionally, the administrator or the like may further utilize the simulation results to generate related information. Further, the administrator or the like may generate the relational information of the bridge by using the relational information applied to other bridges.

The relational information storage unit 246 may store, as the relational information, a table in which each of the plurality of amplitude values is associated with the corresponding weight. Further, the relational information storage unit 246 may store, as relational information, a function or an arithmetic expression that outputs a weight by inputting an amplitude value.

The weight calculation section 248 calculates the weight of the vehicle every time the vehicle amplitude calculation section 244 calculates the vehicle amplitude value. More specifically, the weight calculation unit 248 calculates the weight of the vehicle based on the relationship information representing the correspondence between the amplitude value and the weight stored in the relationship information storage unit 246 and the calculated vehicle amplitude value. . The weight calculation unit 248 outputs the calculated weight to, for example, an information processing device or a server maintained by an administrator. In this case, the weight calculation unit 248 may also output the time when the vehicle passed the bridge. This allows an administrator or the like to associate vehicles that have passed over the bridge with their weights.

The extraction unit 116 extracts specific partial data, which is partial data when the specific vehicle passes a bridge, from the parameter time series data stored in the storage unit 114.

The amplitude calculation unit 118 calculates a specific vehicle amplitude value representing the amplitude value of the amount of expansion and contraction in the traveling direction of the bridge when the specific vehicle passes, based on the specific part data, every time the extraction unit 116 extracts the specific part data. .

Every time the amplitude calculation unit 118 calculates the specific vehicle amplitude value, the correction unit 250 compares the calculated specific vehicle amplitude value with a preset reference value. Then, when the specific vehicle amplitude value becomes larger than the reference value, the correction section 250 corrects the correspondence stored in the relational information storage section 246.

The correction unit 250 may calculate the moving average value of the specific vehicle amplitude values of the most recent predetermined number of samples, and may correct the related information when the moving average value becomes larger than the reference value. Further, the correction unit 250 performs predetermined filtering processing such as noise removal processing on the specific vehicle amplitude values of a plurality of samples, and when the result of the filtering processing becomes larger than the reference value, The information may be corrected.

Note that the weight measurement device 230 includes the passage time acquisition section 122, passage detection information acquisition section 124, scheduled time estimation section 126, date acquisition section 132, time zone acquisition section 133, passage speed acquisition section 134, and weight shown in FIG. The configuration may further include one or more of the acquisition units 136.

FIG. 13 is a diagram showing the relationship between the weight of the test vehicle and the amplitude value of the amount of expansion and contraction of the bridge. In FIG. 13, the graph with black circles represents the relationship when the deterioration of the bridge is small, and the graph with open squares represents the relationship when the deterioration of the bridge becomes greater than a predetermined reference value.

As the deterioration of the bridge increases, the amplitude value of the amount of expansion and contraction in the traveling direction of the bridge when a vehicle passes through the bridge increases. Therefore, as shown in Fig. 13, the weight of the vehicle and the amount of expansion and contraction of the bridge in the running direction when the vehicle passes, depending on whether the deterioration of the bridge is greater than the standard value or the case where the deterioration is less than the standard value. The relationship with the amplitude value is different. Therefore, for example, the administrator generates first relational information when the deterioration of the bridge is below the reference value and second relational information when the deterioration of the bridge is greater than the reference value, and 246.

Then, when the specific vehicle amplitude value is less than or equal to the reference value, the correction unit 250 causes the first relationship information to be output from the relationship information storage unit 246 to the weight calculation unit 248. Further, when the specific vehicle amplitude value is larger than the reference value, the correction unit 250 causes the related information storage unit 246 to output the second relationship information to the weight calculation unit 248. Thereby, the correction unit 250 can accurately measure the weight of the vehicle regardless of the degree of deterioration of the bridge.

Note that the correction unit 250 may have a plurality of different reference values set in advance. Then, the correction unit 250 may adjust the correction amount of the related information according to the magnitude of the reference value each time the specific vehicle amplitude value becomes larger than the respective reference value. Thereby, the correction unit 250 can appropriately correct the related information according to the level of deterioration of the bridge.

FIG. 14 is a flowchart showing the flow of the related information correction process by the weight measuring device 230. The weight measuring device 230 executes processing according to the flow shown in FIG. 14, as an example.

Note that the processing from S11 to S21 in FIG. 14 is the same as that of the deterioration detection device 30 in FIG. 10. However, in the weight measurement system 210, the power of the sensor 20 is always on in order to measure the weight of a vehicle passing over a bridge. Therefore, if the sensor 20 used to measure weight and the sensor 20 used when a specific vehicle passes are the same, the weight measuring device 230 does not execute the processes of S13, S14, S16, and S17. It's fine. However, in this case, in S18, the weight measuring device 230 cuts out a range from a predetermined time before the scheduled time to a predetermined time after the scheduled time from the time series data of the parameters, and extracts specific partial data from the cut out range. .

In S21, the weight measuring device 230 determines whether the calculated amplitude value is larger than a reference value. If the amplitude value is larger than the reference value (Yes in S21), the weight measuring device 230 advances the process to S31.

In S31, the weight measuring device 230 corrects the correspondence stored in the relational information storage section 246. When S31 ends, the weight measuring device 230 ends this flow. Note that after S31, the weight measuring device 230 may increase the reference value by a predetermined amount and return the process to S11.

The weight measurement system 210 according to the second embodiment as described above calculates a vehicle amplitude value that represents the amplitude value of the amount of expansion and contraction of the bridge in the traveling direction when the vehicle passes, and calculates the correspondence relationship between the amplitude value and the weight of the vehicle. The weight of the vehicle is calculated based on the relationship information representing , and the calculated vehicle amplitude value. Therefore, the weight measurement system 210 can accurately measure the weight of a vehicle passing through a bridge.

Further, the weight measurement system 210 corrects the related information when the specific vehicle amplitude value representing the amplitude value of the amount of expansion/contraction in the traveling direction of the bridge when the specific vehicle passes becomes larger than the reference value. Accordingly, the weight measurement system 210 can correct the related information in response to bridge deterioration.

As described above, according to the weight measurement system 210 according to the second embodiment, it is possible to accurately measure the weight of a vehicle passing through a bridge while correcting related information as the bridge deteriorates.

(Hardware configuration of deterioration detection device 30 and weight measurement device 230)
FIG. 15 is a diagram showing the hardware configuration of the deterioration detection device 30 and the weight measurement device 230. The deterioration detection device 30 and the weight measurement device 230 are realized by, for example, a hardware configuration similar to that of a general computer. The deterioration detection device 30 and the weight measurement device 230 include a CPU (Central Processing Unit) 301, an operating device 302, a display device 303, a ROM (Read Only Memory) 304, a RAM (Random Access Memory) 305, and a storage device. 306, a communication device 307, and a bus 309. Each part is connected by a bus 309.

The CPU 301 uses a predetermined area of the RAM 305 as a work area to execute various processes in cooperation with various programs stored in advance in the ROM 304 or the storage device 306, and controls the operation of each part constituting the deterioration detection device 30 or the weight measurement device 230. Control overall. Further, the CPU 301 operates the operating device 302, the display device 303, the communication device 307, etc. in cooperation with a program stored in advance in the ROM 304 or the storage device 306.

The operating device 302 is an input device such as a touch panel, a mouse, or a keyboard, and receives information inputted by a user as an instruction signal, and outputs the instruction signal to the CPU 301 .

The display device 303 is a display unit such as an LCD (Liquid Crystal Display). The display device 303 displays various information based on display signals from the CPU 301.

The ROM 304 non-rewritably stores programs used to control the deterioration detection device 30 or the weight measurement device 230, various setting information, and the like. The RAM 305 is a volatile storage medium such as SDRAM (Synchronous Dynamic Random Access Memory). RAM305 functions as a work area for CPU301.

The storage device 306 is a rewritable storage device such as a semiconductor storage medium such as a flash memory, or a magnetically or optically recordable storage medium. The storage device 306 stores a program used to control the deterioration detection device 30 or the weight measurement device 230.

A communication device 307 sends and receives data to and from other devices. Further, the communication device 307 may send and receive data to and from a server or the like via a network.

The programs executed by the deterioration detection device 30 and the weight measurement device 230 are stored, for example, on a computer connected to a network such as the Internet, and provided by being downloaded via the network. Further, the programs executed by the deterioration detection device 30 and the weight measurement device 230 may be provided by being pre-installed in a portable storage medium or the like.

The program executed by the deterioration detection device 30 has a module configuration including a collection module, an extraction module, an amplitude calculation module, a determination module, and an alarm output module. The CPU 301 (processor) reads such a program from a storage medium or the like, and loads each of the above modules into the RAM 305 (main storage device). The CPU 301 (processor) functions as the collection section 112, the extraction section 116, the amplitude calculation section 118, the determination section 119, and the alarm output section 120 by executing such programs. Note that part or all of the collection section 112, the extraction section 116, the amplitude calculation section 118, the determination section 119, and the alarm output section 120 may be configured by hardware.

The program executed by the weight measurement device 230 has a module configuration including a collection module, a vehicle extraction module, a vehicle amplitude calculation module, a weight calculation module, an extraction module, an amplitude calculation module, and a correction module. There is. The CPU 301 (processor) reads such a program from a storage medium or the like, and loads each of the above modules into the RAM 305 (main storage device). Then, by executing such a program, the CPU 301 (processor) executes the collection section 112, the vehicle extraction section 242, the vehicle amplitude calculation section 244, the weight calculation section 248, the extraction section 116, the amplitude calculation section 118, and the correction section 250. functions as Note that part or all of the collection section 112, vehicle extraction section 242, vehicle amplitude calculation section 244, weight calculation section 248, extraction section 116, amplitude calculation section 118, and correction section 250 may be configured by hardware.

Although the embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. Embodiments can be modified in various ways.

10 Deterioration detection system 20 Sensor 22 Transmitter 30 Deterioration detection device 54 Main girder 56 Lower surface 62 First point 64 Second point 66 First member 68 Second member 70 Displacement detection device 72 Optical element 74 Detector 76 Half mirror 78 Light emitting part 80 Light receiving section 82 Detection circuit 112 Collection section 114 Storage section 116 Extraction section 118 Amplitude calculation section 119 Judgment section 120 Alarm output section 122 Passage time acquisition section 124 Passage detection information acquisition section 126 Scheduled time estimation section 132 Date acquisition section 133 Time zone acquisition Section 134 Passing speed acquisition section 136 Weight acquisition section 210 Weight measurement system 230 Weight measurement device 242 Vehicle extraction section 244 Vehicle amplitude calculation section 246 Related information storage section 248 Weight calculation section 250 Correction section

Claims (17)

a collection unit that collects time-series data of parameters representing displacement in the traveling direction of a target portion of the bridge where the sensor is installed, from a sensor installed on the bridge;
an extraction unit that extracts specific partial data when a specific vehicle passes the bridge from the time series data;
an amplitude calculation unit that calculates an amplitude value of the amount of expansion and contraction of the bridge in the travel direction when the specific vehicle passes, based on the specific portion data;
a determination unit that determines that the bridge has deteriorated when the amplitude value becomes larger than a preset reference value;
A deterioration detection device comprising: The deterioration detection device according to claim 1, further comprising: an alarm output unit that outputs alarm information indicating that the bridge has deteriorated when it is determined that the bridge has deteriorated. The specific vehicle is a vehicle scheduled to pass the bridge at a preset first time,
The time series data is data in which time and the parameter are associated,
The deterioration detection device according to claim 1 or 2, wherein the extraction unit extracts the specific partial data from a predetermined time range before and after the first time in the time series data. 3. The extraction unit extracts the specific partial data from the time series data based on a detection signal detected by a passage detection device that detects that the specific vehicle is passing through the bridge. Deterioration detection device described. The extraction unit is configured to determine whether the specific vehicle has passed based on passing information indicating that the specific vehicle has passed a predetermined first position and a predicted travel time of the specific vehicle from the first location to the bridge. The deterioration detection device according to claim 1 or 2, wherein a scheduled time of passing through the bridge is estimated, and the specific portion data is extracted based on the estimated scheduled time. The specific vehicle is a vehicle scheduled to pass the bridge at the same time every day,
The deterioration detection device according to any one of claims 1 to 5, wherein the amplitude calculation unit calculates the amplitude value based on the specific partial data extracted from the time series data on a preset date. The deterioration detection device according to any one of claims 1 to 6, wherein the amplitude calculation unit calculates the amplitude value based on the specific partial data extracted from the time series data in a preset time period. . The amplitude calculation unit calculates the amplitude value based on the specific partial data extracted from the time series data in which the speed of the specific vehicle when passing the bridge is within a preset range. 8. The deterioration detection device according to any one of 1 to 7. The amplitude calculation unit calculates the amplitude value based on the specific partial data extracted from the time series data in which the weight of the specific vehicle when passing the bridge is within a preset range. 9. The deterioration detection device according to any one of 1 to 8. The specific vehicle is equipped with a scale for measuring its own weight,
The deterioration detection device according to claim 9, wherein the amplitude calculation unit obtains the weight of the specific vehicle when passing the bridge based on data measured by the weight scale. The deterioration detection device according to any one of claims 1 to 10, wherein the specific vehicle is a route bus. a sensor that is provided at a target portion of a bridge and detects a parameter representing a displacement in the travel direction of the target portion of the bridge;
a collection unit that collects time-series data of the parameters from the sensor;
an extraction unit that extracts specific partial data when a specific vehicle passes the bridge from the time series data;
an amplitude calculation unit that calculates an amplitude value of the amount of expansion and contraction of the bridge in the travel direction when the specific vehicle passes, based on the specific portion data;
a determination unit that determines that the bridge has deteriorated when the amplitude value becomes larger than a preset reference value;
A deterioration detection system comprising: Collecting time-series data of parameters representing displacement in the traveling direction at a target portion of the bridge where the sensor is installed from a sensor installed on the bridge;
extracting specific partial data when a specific vehicle passes the bridge from the time series data;
Based on the specific portion data, calculate the amplitude value of the amount of expansion and contraction of the bridge in the traveling direction when the specific vehicle passes;
A deterioration detection method in which it is determined that the bridge has deteriorated when the amplitude value becomes larger than a preset reference value. A program for causing an information processing device to function as a deterioration detection device,
The information processing device,
a collection unit that collects time-series data of parameters representing displacement in the traveling direction of a target portion of the bridge where the sensor is installed, from a sensor installed on the bridge;
an extraction unit that extracts specific partial data when a specific vehicle passes the bridge from the time series data;
an amplitude calculation unit that calculates an amplitude value of the amount of expansion and contraction of the bridge in the travel direction when the specific vehicle passes, based on the specific portion data;
A program that functions as a determination unit that determines that the bridge has deteriorated when the amplitude value becomes larger than a preset reference value. a collection unit that collects time-series data of parameters representing displacement in the traveling direction at a target portion of the bridge where the sensor is installed, from a sensor installed on the bridge;
a vehicle extraction unit that extracts vehicle partial data, which is partial data when a vehicle passes the bridge, from the time series data;
a vehicle amplitude calculation unit that calculates a vehicle amplitude value representing an amplitude value of an amount of expansion and contraction of the bridge in the traveling direction when the vehicle passes, based on the vehicle partial data;
a weight calculation unit that calculates the weight of the vehicle based on relationship information representing a correspondence between the amplitude value and the weight of the vehicle and the calculated vehicle amplitude value;
an extraction unit that extracts specific partial data that is partial data when a specific vehicle passes the bridge from the time series data;
an amplitude calculation unit that calculates a specific vehicle amplitude value representing an amplitude value of an amount of expansion and contraction of the bridge in the travel direction when the specific vehicle passes, based on the specific portion data;
a correction unit that corrects the relationship information when the specific vehicle amplitude value becomes larger than a preset reference value;
A weight measuring device comprising: Collecting time-series data of parameters representing displacement in the traveling direction at a target portion of the bridge where the sensor is installed from a sensor installed on the bridge;
Extracting vehicle partial data that is partial data when the vehicle passes the bridge from the time series data,
Based on the vehicle partial data, calculate a vehicle amplitude value representing an amplitude value of an amount of expansion and contraction of the bridge in the traveling direction when the vehicle passes;
Calculating the weight of the vehicle based on relationship information representing a correspondence relationship between the amplitude value and the weight of the vehicle and the calculated vehicle amplitude value,
an extraction unit that extracts specific partial data that is partial data when a specific vehicle passes the bridge from the time series data;
Based on the specific portion data, calculate a specific vehicle amplitude value representing an amplitude value of an amount of expansion/contraction of the bridge in the traveling direction when the specific vehicle passes;
A weight measuring method, wherein the related information is corrected when the specific vehicle amplitude value becomes larger than a preset reference value. A program for causing an information processing device to function as a weight measuring device,
The information processing device,
a collection unit that collects time-series data of parameters representing displacement in the traveling direction of a target portion of the bridge where the sensor is installed, from a sensor installed on the bridge;
a vehicle extraction unit that extracts vehicle partial data, which is partial data when a vehicle passes the bridge, from the time series data;
a vehicle amplitude calculation unit that calculates a vehicle amplitude value representing an amplitude value of an amount of expansion and contraction of the bridge in the traveling direction when the vehicle passes, based on the vehicle partial data;
a weight calculation unit that calculates the weight of the vehicle based on relationship information representing a correspondence between the amplitude value and the weight of the vehicle and the calculated vehicle amplitude value;
an extraction unit that extracts specific partial data that is partial data when a specific vehicle passes the bridge from the time series data;
an amplitude calculation unit that calculates a specific vehicle amplitude value representing an amplitude value of an amount of expansion and contraction of the bridge in the travel direction when the specific vehicle passes, based on the specific portion data;
a correction unit that corrects the relationship information when the specific vehicle amplitude value becomes larger than a preset reference value;
A program that makes it work.

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