Derivation method, derivation device, derivation system, program

Abstract

To calculate the number of movable bodies that constitute a movable body traveling in a structure with a lower load.SOLUTION: An acquisition step for acquiring time sequence data which includes the physical quantity generated at a prescribed observation point in a structure in response to the travel of a formation movable body formed by one or more movable bodies in the structure; a time derivation step for deriving the entry time and the exit time of the formation movable body relative to the structure on the basis of the time sequence data; and a number derivation step for deriving the number of movable bodies included in the formation movable body on the basis of the time sequence data, the entry time and the exit time: are included.SELECTED DRAWING: Figure 19

Description

Technical Field

[0001] The present invention relates to a derivation method, a derivation device, a derivation system, and a program.

Background Art

[0002] In recent years, many social infrastructures have deteriorated over time, and there is a need for a method for diagnosing the condition of structures that make up social infrastructures such as railway bridges. Patent Document 1 discloses a method for investigating and evaluating the structural performance of a railway bridge that enables the structural performance of a bridge to be suitably investigated and evaluated using observation data of the acceleration response of the bridge during train travel. The method for investigating the structural performance of the railway bridge in Patent Document 1 formulates a theoretical analysis model of the dynamic response of the railway bridge during train travel, assuming the train as a moving load train and the bridge as a simple beam, measures the acceleration of the bridge during train travel, and estimates unknown parameters of the theoretical analysis model from the acceleration data by an inverse analysis method. Further, Patent Document 2 discloses a method for obtaining the impact coefficient (dynamic response component) of a bridge using the vertical acceleration response of a running train, particularly when passing through the bridge.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] There are cases where a formation moving body formed by one or more moving bodies, such as a railway train, moves on a structure such as a bridge. In such a case, for the purpose of generating a motion model of the structure for diagnosis or the like, there is a desire to know how many moving bodies are formed in the formation moving body that moves the structure. In Patent Document 1, the amount of calculation in the inverse analysis method for obtaining unknown parameters becomes enormous. Also, in Patent Document 2, it was not possible to determine how many moving bodies are formed in the moving body that moves the structure. Thus, in Patent Documents 1 and 2, it was not possible to determine, with a lower load, how many moving bodies are formed in the moving body that moves the structure.

Means for Solving the Problem

[0005] The derivation method for solving the above problem includes: an acquisition step of acquiring time-series data including a physical quantity generated at a predetermined observation point in the structure as a response caused by a formation moving body formed by one or more moving bodies moving the structure; a time derivation step of deriving, based on the time-series data, the entry time and the exit time of the formation moving body with respect to the structure; and a number derivation step of deriving, based on the time-series data, the entry time, the exit time, and the number of the moving bodies included in the formation moving body. The derivation device for solving the above problem includes: an acquisition unit that acquires time-series data including a physical quantity generated at a predetermined observation point in the structure as a response caused by a formation moving body formed by one or more moving bodies moving the structure; a time derivation unit that derives, based on the time-series data, the entry time and the exit time of the formation moving body with respect to the structure; and a number derivation unit that derives, based on the time-series data, the entry time, the exit time, and the number of the moving bodies included in the formation moving body. The derivation system for solving the above problems is a derivation system comprising a derivation device and a sensor, wherein the derivation device includes an acquisition unit that acquires time-series data including a physical quantity that occurs at a predetermined observation point in the structure as a response to the movement of a structured moving body formed by one or more moving bodies and that is measured via the sensor; a time derivation unit that derives the entry time and the exit time of the structured moving body with respect to the structure based on the time-series data; and a number derivation unit that derives the number of moving bodies included in the structured moving body based on the time-series data, the entry time, and the exit time. The program for solving the above problems causes a computer to execute an acquisition step of acquiring time-series data including a physical quantity that occurs at a predetermined observation point in the structure as a response to the movement of a structured moving body formed by one or more moving bodies; a time derivation step of deriving the entry time and the exit time of the structured moving body with respect to the structure based on the time-series data; and a number derivation step of deriving the number of moving bodies included in the structured moving body based on the time-series data, the entry time, and the exit time.

Brief Description of the Drawings

[0006]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

Figure 15

Figure 16

Figure 17

Figure 18

Figure 19

Embodiments for Carrying Out the Invention

[0007] Here, embodiments of the present invention will be described in the following order. (1) Configuration of the derivation system: (1-1) Overview of the derivation system: (1-2) Deflection model: (1-3) Verification experiment: (1-4) Details of elements: (2) Derivation process: (3) Other embodiments:

[0008] (1) Configuration of the derivation system: (1-1) Overview of the derivation system: FIG. 1 is a block diagram showing an example of the configuration of the derivation system 10 according to the present embodiment. The derivation system 10 is a system that derives the number of railway vehicles included in the railway train 6 based on time-series data including physical quantities at a predetermined observation point on the bridge 5 on which the railway train 6 formed of one or more railway vehicles moves. The railway train 6 is an example of a formation moving body. Each of the railway vehicles included in the railway train 6 is an example of a moving body. The bridge 5 is an example of a structure on which the moving body moves. Each railway vehicle of the railway train 6 moves on the bridge 5 via wheels provided on the axles. The wheels are an example of the contact part between the railway vehicle and the bridge. In the present embodiment, each of the railway vehicles formed in the railway train 6 is a railway vehicle having the same structure. As shown in FIG. 1, the derivation system 10 includes a measurement device 1, at least one sensor device 2 provided in the superstructure 7 of the bridge 5, and a server device 3.

[0009] The measurement device 1 calculates the deflection displacement of the superstructure 7 due to the running of the railway train 6 based on the acceleration data output from each sensor device 2. The measurement device 1 is installed, for example, on the abutment 8b. The measurement device 1 and the server device 3 can communicate with each other via a communication network 4 such as a wireless network of a mobile phone and the Internet. The measurement device 1 transmits information on the displacement of the superstructure 7 due to the running of the railway train 6 to the server device 3. The server device 3 derives the number of railway vehicles formed in the railway train 6 based on the transmitted displacement data.

[0010] In this embodiment, the bridge 5 is a railway bridge, such as a steel bridge, a truss bridge, an RC bridge (where RC is the abbreviation for Reinforced-Concrete), etc. Also, in this embodiment, the bridge 5 is a structure to which BWIM (Bridge Weigh In Motion) can be applied. BWIM is a technology that regards the bridge as a "scale" and measures the weight, number of axles, etc. of a moving object passing over the bridge by measuring the deformation of the bridge. A bridge that can analyze the weight of a moving object passing through from responses such as the deformation and strain of the bridge is considered a structure to which BWIM can be applied. Therefore, it is possible to measure the weight of a moving object moving on the bridge by means of a BWIM system that applies the physical process between the action on the bridge and the response. The measurement of the weight of the moving object is carried out by previously measuring the correlation coefficient between displacement and load and deriving the load of the moving object passing through from the measurement result of the displacement of the bridge when the moving object passes through, using the correlation coefficient.

[0011] The bridge 5 includes a superstructure 7, which is the part where the moving object moves, and a substructure 8 that supports the superstructure 7. Fig. 2 is a cross-sectional view of the superstructure 7 cut along the line A-A in Fig. 1. As shown in Figs. 1 and 2, the superstructure 7 includes a bridge floor 7a that includes a floor slab F, main girders G, cross girders (not shown), etc., bearings 7b, rails 7c, sleepers 7d, and ballast 7e. Also, as shown in Fig. 1, the substructure 8 includes bridge piers 8a and abutments 8b. The superstructure 7 is a structure spanned between adjacent abutments 8b and bridge piers 8a, between two adjacent abutments 8b, or between two adjacent bridge piers 8a. Hereinafter, the abutments 8b and the bridge piers 8a are collectively referred to as support parts. In this embodiment, one set of support parts and the bridge girder part of the superstructure 7 spanned between this one set of support parts are collectively regarded as one bridge girder. That is, a simple beam-like structure supported at both ends by two support parts is regarded as one bridge girder. Therefore, the bridge 5 shown in Fig. 1 includes two bridge girders. Hereinafter, each bridge girder included in the bridge 5 is referred to as a unit bridge girder. The measuring device 1 and the sensor device 2 are connected, for example, by wire or wirelessly, and communicate via a communication network such as CAN (Controller Area Network).

[0012] The sensor device 2 is used for measuring a predetermined physical quantity that is used to derive the displacement (flexure) at the observation point set on the upper structure 7. In the present embodiment, this predetermined physical quantity is acceleration. Also, in the present embodiment, the sensor device 2 is installed at this observation point. Further, the sensor device 2 includes an acceleration sensor such as a crystal acceleration sensor or a MEMS (Micro Electro Mechanical Systems) acceleration sensor. The sensor device 2 outputs acceleration data for deriving the displacement of the upper structure 7 due to the movement of the railway train 6, which is a moving body, at the observation point.

[0013] In the present embodiment, the sensor device 2 is installed at the central portion in the longitudinal direction of the upper structure 7, specifically, at the central portion in the longitudinal direction of the main girder G. However, the sensor device 2 only needs to be able to detect the acceleration for calculating the displacement of the upper structure 7, and its installation position is not limited to the central portion of the upper structure 7. Note that if the sensor device 2 is provided on the floor slab F of the upper structure 7, it may be damaged by the running of the railway train 6, and the measurement accuracy may be affected by the local deformation of the bridge floor 7a. Therefore, in the examples of FIGS. 1 and 2, the sensor device 2 is provided on the main girder G of the upper structure 7.

[0014] The floor slab F, the main girder G, etc. of the upper structure 7 are deflected in the vertical direction by the load from the railway train 6 running on the upper structure 7. Each sensor device 2 measures the acceleration of the deflection of the floor slab F and the main girder G due to the load of the railway train 6 running on the upper structure 7.

[0015] (1-2) Flexure model: Here, the flexure model of the bridge when a railway train moves on one bridge will be described. Here, the model is information such as an equation showing the correspondence between predetermined information and an estimation result. In the present embodiment, the flexure model of the bridge is an equation based on the structure of the bridge, as described below.

[0016] Also, hereinafter, the number (number of units) of railway vehicles formed in the railway train moving on the bridge will be denoted as N. The entry time, which is the time when the railway train enters the bridge, is ti Let it be so. Here, the entry of the railway train onto the bridge means that the wheels of one axle of the railway vehicle C1 (the first railway vehicle from the head of the railway train) have entered the bridge. Also, hereinafter, the exit time, which is the time when the railway train exits the bridge, is denoted as t o Let it be so. Here, the exit of the railway train from the bridge means that the wheels of the rearmost axle of the railway vehicle C N (the rearmost railway vehicle of the railway train) have exited the bridge. Also, hereinafter, the period during which the railway train passes through the bridge (the period from time t i to time t o ) is denoted as t s Let it be so. Hereinafter, N, t i , t o , t s are collectively referred to as observation information.

[0017] Also, hereinafter, the length of the bridge in the traveling direction of the railway train, which is the bridge length, is denoted as L B Let it be so. Also, the distance from the end of the longitudinal direction of the bridge on the side from which the railway train enters to the observation point is denoted as L x Let it be so. Figure 3 shows L B and L x . Hereinafter, the end of the longitudinal direction of the bridge on the side from which the railway train enters is referred to as the entry end. Also, hereinafter, the end of the longitudinal direction of the bridge on the side in the direction where the railway train exits is referred to as the exit end. Also, the length of the railway vehicle in the traveling direction of the m-th railway vehicle from the head of the railway train is denoted as L c (m). Hereinafter, L c (1) to L c (N) are collectively referred to as L c . Also, the m-th railway vehicle from the head of the railway train is denoted as C m . Also, the number of axles in the railway vehicle C m is denoted as a r (m). Hereinafter, a r (1) to a r (N) are collectively referred to as a r . Hereinafter, the a m axles in the railway vehicle C r (m) are the axles of the railway vehicle C mStarting from the beginning in order, the first axis, the second axis, the third axis, ···, a r is set as the (m)-axis. Also, the distance from the front end in the traveling direction of the railway vehicle C m to the first axis is set as L a (a w (m, 1)). Here, a w (α, β) indicates the β-th axle from the leading axle of the α-th railway vehicle in the train. Also, the distance between the (n - 1)-th axle (n: an integer of 2 or more) and the n-th axle in the railway vehicle C m is set as L a (a w (m, n)). That is, for β of 2 or more, L a (a w (α, β)) indicates the distance between the β-th axle and the (β - 1)-th axle in the train C α . Also, L a (a w (α, 1)) indicates the distance between the first axle and the front end in the traveling direction of the train C α . Hereinafter, L α (a a (1, 1)) to L w (a a (a w (N, a r (N))) are collectively referred to as L a . Each of L a indicates the position of the corresponding axle in the corresponding railway vehicle. For example, L a (a w (m, 1)) indicates that in the railway vehicle C m , the first axle exists at a distance of L a (a w (m, 1)) behind the tip. Also, L a (a w (m, 2)) indicates that in the railway vehicle C m , the second axle exists at a distance of L a (a w (m, 2)) behind the first axle. Here, in the train, railway vehicles with the same 4-axle configuration are assembled. That is, a r (m) (m = 1, 2, ···, N) is 4. In FIG. 4, the L in the railway vehicle C m ​c (m), L a (a w (m, 1)), L a (a w (m, 2)), L a (a w (m, 3)), L a (a w (m, 4)) is shown. Hereinafter, L B , L x , L c , a r , L a are collectively regarded as environmental information.

[0018] t s is obtained as the difference between t o and t i as shown in the following formula (1).

[0019]

Equation

[0020] Also, the total number of wheels T of a railway train ar is obtained by the following formula (2).

[0021]

Equation

[0022] The distance from the first axle of the leading railway vehicle C1 of a railway vehicle to the nth axle of the mth railway vehicle C m of the railway vehicle is represented as D wa (a w (m, n)). D wa (a w (m, n)) is obtained from the following formula (3).

[0023]

Equation

[0024] From the first axle of the leading railway vehicle C1 of a railway vehicle to the last railway vehicle C of the railway vehicleN The last axis a r The distance to (N) is D wa (a w (N, ar(N))). D wa (a w (N, a r (N)) is used to calculate the average speed v of a railway train passing through the bridge a which is expressed by the following formula (4).

[0025] [Number]

[0026] The following formula (5) holds from formula (3) and formula (4).

[0027] [Number]

[0028] Subsequently, the deflection generated in the bridge when a load is applied to the bridge will be described. Figure 5 shows a schematic diagram of the bridge. Figure 5 shows a situation where a load P is applied to the bridge. Here, the distance between the position where the load P is applied on the bridge and the entrance end is represented by a. Also, the distance between the position where the load P is applied on the bridge and the exit end is represented by b. In this case, the bending moment at the position where the load P is applied on the bridge is expressed by the following formula (6).

[0029] [Number]

[0030] Figure 6 shows the bending moment at each position of the bridge due to the load P. As shown in Figure 6, the bending moment generated in the bridge by the load P is 0 at the entrance end, and increases proportionally as it approaches the position where the load P is applied from the entrance end. At the position where the load P is applied, it becomes the value shown in Equation (6). Also, the bending moment generated in the bridge by the load P decreases proportionally as it approaches the exit end from the position where the load P is applied, and becomes 0 at the exit end. Therefore, the bending moment at any position X in the bridge is represented by the following Equation (7).

[0031]

Number

[0032] In Equation (7), x represents the distance from the entrance end in the traveling direction of the railway train to the position X. Also, Ha in Equation (7) is the value shown by the following Equation (8).

[0033]

Number

[0034] There is a relationship shown by the following Equation (9) between the deflection w of the bridge at any position X and the bending moment.

[0035]

Number

[0036] In Equation (9), E is the Young's modulus of the bridge. Also, I in Equation (9) is the second moment of inertia of the bridge. Also, θ in Equation (9) is the angle formed by the horizontal line and the deflected bridge at the position X. From Equation (7) and Equation (9), the following Equation (10) holds.

[0037]

Number

[0038] By integrating both sides of Equation (10) twice with respect to x, the following Equation (11) representing the deflection w at position X is obtained.

[0039]

Number

[0040] g1 and g2 in Equation (11) are constant terms. Here, since the bridge is supported at the entrance end and the exit end, no deflection occurs at the positions of the entrance end and the exit end. That is, in Equation (11), when x = 0 and x = L B both sides become zero. Therefore, g1 and g2 are as shown in the following Equations (12) and (13).

[0041]

Number

[0042]

Number

[0043] From Equations (11), (12), and (13), the following Equation (14) representing the deflection w at position X is obtained.

[0044]

Number

[0045] When the load P is applied at the center of the longitudinal direction of the bridge, the maximum deflection among the deflections generated in the bridge due to the application of the load P occurs at the center of the longitudinal direction of the bridge. Let this maximum deflection be w 0.5l and find the equation representing w 0.5l When the load P is applied at the center of the longitudinal direction of the bridge, a = b = 0.5L B Also, since the position X for which the deflection is sought is the center of the longitudinal direction of the bridge, x = 0.5L B In this case, since x <= a, from Equation (8), H abecomes 0. x = 0.5L B a = b = 0.5L B H a Substituting H = 0 into Equation (14), the deflection w 0.5l The following Equation (15) representing it is obtained.

[0046] [Number]

[0047] w 0.5l is used to normalize the deflection at any position in the bridge represented by Equation (14). When the position of the load P exists on the entrance end side of the position X, that is, when x > a, from Equation (8), H a becomes 1, and Equation (14) is expressed as the following Equation (16).

[0048] [Number]

[0049] a = L B Let it be r. Here, r is a real number between 0 and 1. b = L B - a, so b = L B (1 - r). Substituting a = L B r, b = L B (1 - r) into Equation (16) and dividing by w 0.5l for normalization, the normalized deflection w std at the position X when x > a is obtained as the following Equation (17).

[0050] [Number]

[0051] Similarly, when the position of the load P exists on the exit end side of the position X, that is, when x <= a, from Equation (8), H a becomes 0, and Equation (14) is expressed as the following Equation (18).

[0052]

Number

[0053] a = L B Let r be. Here, r is a real number between 0 and 1. b = L B Since it is -a, b = L B is expressed as (1 - r). Substitute a = L into Equation (18) B r, b = L B (1 - r) and divide by w 0.5l to normalize. The normalized deflection w at position X when x <= a is obtained as the following Equation (19). std is obtained as follows.

[0054]

Number

[0055] Substitute L for x in Equation (17) and Equation (19) x to obtain the normalized deflection w at the observation point of the deflection, which is expressed as the following Equation (20) as a function of r. std is expressed as follows.

[0056]

Number

[0057] The function R(r) in Equation (20) is the function shown in the following Equation (21).

[0058]

Number

[0059] Here, using Equation (20) and Equation (21), find the function that shows the time change of the deflection generated at the observation point due to the load applied to the bridge through the wheels of any one axle a w (m, n). First, let t be the period it takes for a wheel of one axle of a railway train to reach the observation point from the entry end. xn Let it be so. t xn is obtained from L x and v a by the following formula (22).

[0060]

Number

[0061] Also, let t ln be the period it takes for a wheel of a railway train to cross a bridge, that is, the period it takes to reach the exit end from the entry end. ln Let it be so. t ln is obtained from L B and v a by the following formula (23).

[0062]

Number

[0063] Also, let t o (m, n) be the time when the wheel of the n -th axle a w (m, n) of the m -th railway vehicle of the railway train reaches the entry end. o Let it be so. t o (m, n) is obtained from t i and v a and D wa (a w (m, n)) by the following formula (24).

[0064]

Number

[0065] From formula (22), L x is expressed as in the following formula (25).

[0066]

Number

[0067] Also, from Equation (23), L B is expressed as in the following Equation (26).

[0068]

Equation

[0069] Axle a w (m, n) is the position of the load point. Therefore, the position of axle a w (m, n) is at a distance of a = L B r in the direction from the entry end to the exit end. Also, if the variable indicating time is t, the distance of a w (m, n) from the entry end at time t o is equal to the distance the railway vehicle has traveled from (m, n) to time t. Therefore, the following Equation (27) holds.

[0070]

Equation

[0071] From Equation (27), r is expressed as in the following Equation (28).

[0072]

Equation

[0073] Using Equations (25), (26), and (28) to replace L x , L B , r, as a model showing the time change of the deflection generated at the observation point by the load applied to the bridge through the wheels of axle a w (m, n), the function w std (a w (m, n), t) is obtained. The function R(t) in Equation (29) is the function shown in the following Equation (30).

[0074]

Equation

[0075] [Number]

[0076] Observation information and environmental information (t i , t o , N, L B , L x , L c (1)~L c (N), a r (1)~a r (N), L a (a w (1, 1))~L a (a w (N, a r (N)))) are known, and using these information, w std (a w (m, n), t) can be obtained. For example, from t i , t o , t s is obtained using Equation (1). t s , N, a r , L a , L c , v a is obtained using Equation (5). v a and L B and L x , t xn , t ln are obtained using Equations (22) and (23). L a , L c , ti, t o (m, n) is obtained using Equations (3) and (24). Then, substituting the obtained t xn , t ln , t o (m, n) into Equations (29) and (30), the function w of t std (a w (m, n), t) can be obtained.

[0077] w std (a wAn example of the change in the deflection amount at the observation point indicated by (m, n, t) is shown in FIG. 7. The horizontal axis of the graph in FIG. 7 is time, and the vertical axis indicates the deflection amount. Also, as one railway vehicle C m moves, a r set of wheels for each of the a m (m) axles will move across the bridge. Therefore, the function C std (m, t) as a model showing the time change in the deflection amount generated at the observation point due to the movement of one railway vehicle C std (a w (m, n, t)) is obtained as the sum of the following equation (31).

[0078]

Equation

[0079] a r When a(m) is 4, that is, when the railway vehicle C m has a four-axle configuration, the state of the change in the deflection amount at the observation point indicated by the function C std (m, t) is shown in FIG. 8. The horizontal axis of the graph in FIG. 8 is time, and the vertical axis indicates the deflection amount. Also, the solid-line graph in FIG. 8 shows C std (m, t), and each of the dotted-line graphs shows w std (a w (m, n, t)) for each axle.

[0080] Also, as the railway train moves, N railway vehicles move across the bridge. Therefore, the function T std (t) as a model showing the time change in the deflection amount generated at the observation point due to the movement of one railway train is obtained as the sum of C std (m, t) for each railway vehicle as shown in the following equation (32).

[0081]

Equation

[0082] When N is 16, that is, when 16 railway vehicles are assembled in a railway train, the function T std The state of change in the deflection amount at the observation point indicated by (t) is shown in FIG. 9. The horizontal axis of the graph in FIG. 9 represents time, and the vertical axis represents the deflection amount. Also, the solid line graph in FIG. 9 represents T std (t), and each dotted line graph represents C for each railway vehicle std (m, t). As shown in the graph of FIG. 9, it can be seen that the waveform is the sum of the deflections for each passing railway vehicle, and vibrations occur at the period when consecutive vehicles pass over the bridge The above is the explanation of the deflection model in the bridge

[0083] (1 - 3) Verification experiment: The inventors obtained the deflection amount T std (t) under the condition that the observation information and the environmental information are the values shown below. That is, N = 4, t i = 7.21 [seconds], t o = 8.777 [seconds], t s = 1.567 [seconds], L B = 25 [m], L x = 12.5 [m], L c each = 25 [m], a r each = 4, m = 1 to N for each L a (a w (m, 1)) = 2.5 [m], m = 1 to N for each L a (a w (m, 2)) = 2.5 [m], m = 1 to N for each L a (a w (m, 3)) = 15 [m], m = 1 to N for each L a (a w (m, 4)) = 2.5 [m].

[0084] The deflection amount T std (t) at this time is shown in FIG. 10. The horizontal axis of the graph in FIG. 10 represents time, and the vertical axis represents the deflection amount. Also, the inventors performed a fast Fourier transform (FFT) on the obtained T std (t) to obtain the intensity of each frequency component included in T std (t).std (t) is shown in FIG. 11. The horizontal axis of the graph in FIG. 11 represents frequency, and the vertical axis represents the intensity of the component corresponding to the frequency. Then, the inventors determined the frequency T of the vibration generated in the bridge according to the movement of consecutive railway vehicles std from the FFT result of T std of the fundamental frequency F of (t) f was obtained. Here, the fundamental frequency is the frequency of the lowest-frequency component contained in the signal. Specifically, the inventors identified the peak corresponding to the lowest frequency from the FFT result of T std (t), excluding the side lobes generated by the influence of the window function used in the FFT, and determined the frequency corresponding to the identified peak as the fundamental frequency F f The inventors obtained the fundamental frequency of 3.1 Hz from the graph of FIG. 11.

[0085] The inventors determined the wave number ν of the fundamental frequency F f contained in the passing period ts using the following formula (33). That is, the wave number ν is derived as the product of ts and F f In this case, ν = 1.567 × 3.1 = 4.8577. Here, the number N of railway vehicles in the moving railway train is 4. The inventors found that the wave number ν of the fundamental frequency F

[0086]

Equation

[0087] contained in the passing period ts becomes a value about 1 higher than N. Hereinafter, this feature is referred to as the first feature. Therefore, the inventors determined that the number N of railway vehicles included in the railway train is the fundamental frequency F f contained in the passing period ts fIt was found that this can be calculated using the following equation (34), where the wave number ν minus 1 is rounded to an integer. The round function returns the rounded value of its argument. Furthermore, the method of rounding to an integer is not limited to rounding, and other methods such as rounding down or rounding up may be used depending on the characteristics of the bridge being observed.

[0088]

number

[0089] Furthermore, the inventors used the following equation (35) to calculate the fundamental frequency F f From the fundamental period T f asked for.

[0090]

number

[0091] The inventors then calculated the fundamental period T f The deflection amount T std By taking a moving average of (t), low-pass filtering is performed to attenuate frequency components above the fundamental frequency. std The low-pass filter processing may be another FIR filter that attenuates frequency components above the fundamental frequency. std (t) to T std_lp (t)=T std_lp Let t be (kΔT), where k is a variable that indicates the number of observations when the amount of deflection is periodically observed at the observation point. In other words, if the data period (time resolution) of the amount of deflection observation is ΔT, then t = kΔT. As shown in the following equation (36), the fundamental period T f From and ΔT, the moving average interval k adjusted to the time resolution of the data is calculated. mf is obtained.

[0092]

number

[0093] k mf is used to obtain T std_lp (t) by the following formula (37).

[0094]

Equation

[0095] The inventors subtracted T std (t) from the deflection amount T std_lp (t) to perform a high-pass filter process that attenuates components with frequencies below the fundamental frequency on T std (t). The high-pass filter process may be a process of applying another FIR filter that attenuates components with frequencies below the fundamental frequency. The T std (t) subjected to the high-pass filter process is denoted as T std_hp (t). Specifically, as shown in the following formula (38), the inventors obtained T std (t) by subtracting T std_lp (t) from T std_hp (t).

[0096]

Equation

[0097] The obtained T std_hp (t) is superimposed on T std (t) and shown in FIG. 12. The graph in FIG. 12 has the horizontal axis indicating time (t = kΔT) and the vertical axis indicating the deflection amount. The solid line graph in FIG. 12 indicates T std_hp (k), and the dotted line graph indicates T std (t). From the graph in FIG. 12, the number of positive peaks of T s (t) during the passing period t i (the period from time t o to time t std_hp ) is 6. Here, the positive peak means T std_hpAmong the peaks of (t), it is a peak convex upward with respect to the bridge. Also, during the passing period t s the T at std_hp The number of negative peaks of (t) is five. Here, a negative peak means a peak of T std_hp (t) that is convex downward with respect to the bridge. From this, the inventors found that during the passing period t s the T at std_hp (t) has a feature that the number of positive peaks (6) is two more than the number N (4) of railway vehicles included in the railway train, and the number of negative peaks (5) is one more than N (4). Hereinafter, this feature is referred to as the second feature.

[0098] The inventors verified whether the first feature and the second feature hold while changing the observation information and the environmental information to various values. As a result, the inventors found that when L c / 2 < L B < 3L c / 2 is satisfied, the first feature and the second feature hold. The derivation system 10 of the present embodiment performs a process of deriving the number of railway vehicles configured in the railway train 6 from the displacement (deflection) of the bridge observed via the sensor device 2 based on the first feature and the second feature.

[0099] (Details of elements (1 - 4)) Here, with reference to FIG. 13, details of each of the measuring device 1, the sensor device 2, and the server device 3 of the derivation system 10 will be described. In the present embodiment, the environmental information for each of the railway train 6 and the unit bridge girder is known. That is, the bridge length L of the unit bridge girder B , the distance L from the entrance end of the unit bridge girder to the observation point x , the vehicle length L of each railway vehicle of the railway train 6 c , the number of axles a in each railway vehicle of the railway train 6 r , the L of each railway vehicle of the railway train 6 a are known. Specifically, L B = 25 [m], L x = 12.5 m, L c (1) to L c(N) Each is = 25 [m], a r (1) ~ a r (N) Each is = 4, L a (a w (1, 1)) ~ L a (a w (N, 1)) Each is = 2.5 [m], L a (a w (1, 2)) ~ L a (a w (N, 2)) Each is = 2.5 [m], L a (a w (1, 3)) ~ L a (a w (N, 3)) Each is = 15 [m], L a (a w (1, 4)) ~ L a (a w (N, 4)) Each is = 2.5 [m]. Also, in this embodiment, the derivation system 10 derives based on the data measured by the measuring device 1 for the observation information (the number N of railway vehicles configured in the railway train 6, the time t when the railway train 6 enters the unit bridge girder i , the time t when the railway train 6 exits the unit bridge girder o , the period t during which the railway train 6 passes through the unit bridge girder s ). The number N of railway vehicles configured in the railway train 6 is 16.

[0100] The measuring device 1 measures the deflection at the observation point via the sensor device 2. In this embodiment, the measuring device 1 is installed on the abutment 8b, but it may be installed at other positions. The measuring device 1 includes a control unit 100, a storage unit 110, and a communication unit 120. The control unit 100 includes a processor such as a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), etc. The control unit 100 realizes each function of the measuring device 1 by expanding various programs recorded in the ROM or the like into the RAM and executing them via the CPU. The storage unit 110 stores various programs, measured deflection data, etc. The communication unit 120 includes a circuit used for wired or wireless communication with an external device.

[0101] The sensor device 2 detects acceleration as a predetermined physical quantity at the observation point. The sensor device 2 includes a control unit 200, an acceleration sensor 210, a storage unit 220, and a communication unit 230. The control unit 200 includes a processor such as a CPU, a ROM, a RAM, etc. The control unit 200 realizes each function of the sensor device 2 by expanding various programs recorded in the ROM etc. into the RAM and executing them via the CPU.

[0102] The acceleration sensor 210 is an acceleration sensor such as a crystal acceleration sensor or a MEMS acceleration sensor that can detect accelerations generated in the respective axial directions of three mutually orthogonal axes. In the present embodiment, in order to detect the acceleration in the vertical direction more accurately, one axis of the acceleration sensor 210 is arranged to be parallel to the vertical direction. However, there may be a case where the installation location of the sensor device 2 in the superstructure 7 is inclined. Even when one of the three detection axes of the acceleration sensor 210 is not installed in alignment with the vertical direction, the measuring device 1 synthesizes the accelerations of the three axes to detect the acceleration in the vertical direction.

[0103] The control unit 200 of the sensor device 2 periodically detects the acceleration in the vertical direction at the observation point on the bridge 5 via the acceleration sensor 210, and transmits the detected acceleration data to the measuring device 1. The control unit 100 of the measuring device 1 measures the vertical deflection of the bridge 5 at the observation point at the acceleration detection time based on the acceleration data transmitted from the sensor device 2. In the present embodiment, the control unit 100 obtains the vertical deflection of the bridge 5 at the observation point by performing double integration with respect to time on the acceleration indicated by the data transmitted from the sensor device 2. Then, the control unit 100 transmits the measured deflection data to the server device 3. In the present embodiment, the sensor device 2 detects acceleration at a predetermined period ΔT. Therefore, the measuring device 1 measures the time-series data of the deflection at the ΔT period. That is, the measured time-series data is data of discrete values of the displacement measured at the ΔT period, and each discrete value is data associated with the measurement time.

[0104] The server device 3 derives the number of railway vehicles included in the railway train 6 based on the deflection of the observation points measured by the measuring device 1. The server device 3 is an example of a derivation device. The server device 3 includes a control unit 300, a storage unit 310, and a communication unit 320. The control unit 300 includes a processor such as a CPU, a ROM, a RAM, etc. The control unit 300 realizes the functions of the acquisition unit 301, the time derivation unit 302, and the number derivation unit 303 by expanding various programs recorded in the ROM, etc. into the RAM and executing them via the CPU. The storage unit 310 stores various programs, data of the detected deflection, etc. The communication unit 320 includes a circuit used for wired or wireless communication with an external device.

[0105] The acquisition unit 301 is a function of acquiring time-series data of the deflection that occurs at the observation points as a response when the railway train 6 moves over each of the bridge girders of the bridge 5. The control unit 300 acquires, from the measuring device 1, the time-series data of the deflection that occurs at the observation points by the function of the acquisition unit 301. Hereinafter, the time-series data of the deflection acquired by the function of the acquisition unit 301 is denoted as u(t). An example of u(t) is shown in FIG. 14. The horizontal axis of the graph in FIG. 14 indicates time, and the vertical axis indicates the amount of deflection.

[0106] The time derivation unit 302 is a function of deriving the entry time and the exit time of the railway train 6 with respect to a unit bridge girder based on the time-series data acquired by the acquisition unit 301. The control unit 300 executes an FFT on u(t) by the function of the time derivation unit 302. The result of executing an FFT on u(t) shown in FIG. 14 is shown in FIG. 15. The horizontal axis of the graph in FIG. 15 indicates frequency, and the vertical axis indicates the intensity of the component of the corresponding frequency. Then, the control unit 300 detects a peak from the FFT result. The control unit 300 identifies the peak corresponding to the minimum frequency excluding the peaks of the side lobes generated by the influence of the window function used in the FFT among the detected peaks. The control unit 300 derives the frequency corresponding to the identified peak as the fundamental frequency F of u(t). In the example of FIG. 15, the derived fundamental frequency F is 3.01 Hz. f as. f is 3.01 Hz.

[0107] The control unit 300 applies a low-pass filter that attenuates components with a frequency higher than the fundamental frequency F as follows. First, based on the acquired fundamental frequency F f , the control unit 300 applies a low-pass filter. First, the control unit 300 f , based on the acquired fundamental frequency F f , derives the reciprocal of F f to derive the period T f . The control unit 300 derives the interval k mf using Equation (36) based on the derived T mf and the predetermined period ΔT. For each value of u(t), the control unit 300 applies a low-pass filter to u(t) by taking the moving average within the derived interval k lp . Let u lp (t) = u mf (kΔT). Here, k is a variable indicating which observation it is in the case where the deflection amount is periodically observed at the observation point. The control unit 300 derives u lp (t) using the following Equation (39) based on the derived interval k lp . u

[0108]

Equation

[0109] This low-pass filter may be a FIR filter that satisfies the condition of attenuating components with a frequency higher than the fundamental frequency F f . Then, the control unit 300 identifies two consecutive data points in u lp (t) that sandwich a predetermined threshold value C L relating to the deflection amount. Here, the statement that two consecutive data points in u lp (t) sandwich C L means that the range is sandwiched by the values of two consecutively measured displacement data points included in u lp (t), that is, the range that is greater than or equal to the smaller value and less than or equal to the larger value of these displacement data points includes C Lindicates that it is included. This threshold value C L is the value of the deflection that occurs in the bridge in response to the entry of a railway train into the bridge. For example, it is the value of the deflection of the observation point of the bridge when the railway vehicle is arranged such that the wheels of one axle at the front of the railway vehicle are placed near the entry end. Also, this threshold value C L may be other values as long as it can detect the entry of a railway train into the bridge. For example, it may be the amount of deflection of the observation point of the bridge when a predetermined weight is applied near the entry end. Also, the threshold value C L may be a value such as a predetermined ratio (e.g., 10%, 1%, etc.) of the maximum value of the amount of deflection of the observation point of the bridge when the railway train passes over the bridge. Also, the threshold value C L is u lp It may be set to the value of any data included in (t).

[0110] In FIG. 16, u lp (t) and the threshold value C L are shown. The horizontal axis of the graph in FIG. 16 indicates time (t = kΔT), and the vertical axis indicates the amount of deflection. The solid line graph in FIG. 16 shows u lp (t), and the dotted line graph shows u(t). In the portion surrounded by the dotted circle in FIG. 16, u lp (k) and the threshold value C L intersect. Also, in FIG. 17, an enlarged view of the intersection point of u lp (t) and C L (the left dotted circle portion in the graph of FIG. 16) is shown. The horizontal axis of the graph in FIG. 17 indicates time, and the vertical axis indicates the amount of deflection. Each of the black dots in FIG. 17 shows the discrete value data included in u lp (t). In the example of FIG. 17, it is shown that the data k - 1 and the data k included in u lp (t) sandwich the threshold value C L . The control unit 300 identifies the later of the two times corresponding to two consecutive data that sandwich the specified C L . In the example of FIG. 17, the control unit 300 identifies the time kΔT corresponding to the data k. In the example of FIG. 16, the control unit 300 is C LAs two consecutive pieces of data sandwiching [a certain value], identify the two pieces of data in the circular portion of the dotted line on the right side in FIG. 16, and among the two times corresponding to the identified two pieces of data, identify the later one.

[0111] Then, the control unit 300 sets the earlier of the identified times as the entry time t i of the railway train 6 onto the unit bridge girder. o Also, the control unit 300 sets the later of the identified times as the exit time t i of the railway train 6 from the unit bridge girder. o In the example of FIG. 16, the control unit 300 derives that the entry time t lp = 7.2 [s] and the exit time t i = 12.795 [s]. Thus, in this embodiment, the control unit 300 sets the time associated with any data included in u o (t) as the entry time t

[0112] Thus, in this embodiment, the control unit 300 sets the later of the two times corresponding to two consecutive pieces of data sandwiching C lp included in u L (t) as the entry time t i , the entry time t o . However, the control unit 300 may derive other times as the entry time t i , the entry time t o . For example, the control unit 300 identifies two consecutive pieces of data sandwiching a predetermined threshold value C lp relating to the deflection amount from u L (t), and sets a time that is after one of the times corresponding to the identified two pieces of data and before the other time, and included in the period between them, as the entry time t i and the entry time t o . In the example of FIG. 17, the control unit 300 sets a time that is after the time (k - 1)ΔT corresponding to the data k - 1 and before the time kΔT corresponding to the data k (for example, the time (k - 1)ΔT, the time corresponding to the point where u lp (t) and C L intersect, etc.) as the entry time t iIt may be derived as such. Further, the control unit 300 interpolates between each data included in u lp (t) to obtain a curve, and determines the time corresponding to the intersection point between the obtained curve and C L as t i and t o It may be obtained as such.

[0113] Also, for two consecutive data sandwiching C lp included in u L , it is conceivable that one of them becomes equal to C L . For example, in the example of FIG. 17, it is conceivable that the value of data k becomes equal to C L . In that case, the control unit 300 selects any one of the two pairs: the pair of the data equal to C L and the previous data, and the pair of the data equal to C L and the next data, as two consecutive data sandwiching C L . In the example of FIG. 17, when data k is equal to C L , the control unit 300 selects any one of the two pairs: the pair of data k-1 and data k, and the pair of data k and data k+1, as two consecutive data sandwiching C L . The control unit 300 determines the time within the period between the two times corresponding to the two data included in the selected pair as t i or t o It may be derived as such.

[0114] In this embodiment, the control unit 300 determines the time associated with any data included in u lp (t) as the entry time t i and the exit time t o . Thereby, the control unit 300 can easily acquire and utilize the data of u i (t) corresponding to each measurement time within the ΔT interval including the entry time t o by referring to u lp (t). On the other hand, the control unit 300 determines the time not associated with any data included in u lp (t) as the entry time t lp and the exit time t i, exit time t o When derived as, t i , t o For each measurement time of the ΔT interval including, u lp (t) data is obtained by resampling etc. from the original u lp (t), increasing the processing effort.

[0115] The control unit 300 uses u with vibration components above the fundamental frequency attenuated lp (t) to derive the entry time and exit time, reducing the influence of vibration components above the fundamental frequency and enabling more accurate derivation of the entry time and exit time. However, the control unit 300 may not derive u lp (t). In that case, the control unit 300 may use u(t) instead of u lp (t) to derive t i , t o and may derive.

[0116] The number derivation unit 303 is a function that derives the number of railway vehicles included in the railway train 6 based on u(t), which is the time series data acquired by the function of the acquisition unit 301, and the entry time t i and the exit time t o . The control unit 300, based on the function of the number derivation unit 303, derives, as the first candidate value, a value that is a candidate for the number of railway vehicles included in the railway train 6 based on the first feature. The control unit 300 uses Equation (1) based on t i and t o to derive the passing period t s during which the railway train 6 passes through the unit bridge girder. Then, the control unit 300 uses Equation (33) based on the derived t s and the fundamental frequency F f derived based on u(t) to derive the wave number ν of the fundamental frequency F s included in the passing period t f . The control unit 300 uses Equation (34) based on the derived ν to derive, as the first candidate value, the number N of railway vehicles included in the railway train 6. Here, ti = 7.2 [s], t o = 12.795 [s], F f Since it is = 3.01 [Hz], the control unit 300 derives the first candidate value as round((12.795 - 7.2) × 3.01 - 1) = round(15.84) = 16.

[0117] Also, the control unit 300 derives, as the second candidate value and the third candidate value, values that are candidates for the number of railway vehicles included in the railway train 6 based on the second feature. The control unit 300 subtracts u lp (t) from u(t) to perform a high - pass filter process that attenuates components of frequencies below the fundamental frequency on u(t), and derives u hp (t), which is u(t) subjected to the high - pass filter process. Also, the control unit 300 may multiply u(t) by a high - pass filter, which is a FIR filter that attenuates components of frequencies below the fundamental frequency, to derive u hp (t). And the control unit 300 determines, from the data in the period of u hp (t) from t i to t o the number of positive peaks. The control unit 300 derives, as the second candidate value, the value obtained by subtracting 2 from the number of identified positive peaks. Also, the control unit 300 determines, from the data in the period of u hp (t) from t i to t o the number of negative peaks. The control unit 300 derives, as the third candidate value, the value obtained by subtracting 1 from the number of identified negative peaks. u hp (t) obtained by performing a high - pass filter process on u(t) shown in FIG. 14 is shown in FIG. 18. The horizontal axis of FIG. 18 represents time, and the vertical axis represents the amount of deflection. The solid - line graph in FIG. 18 shows u hp (t), and the dotted - line graph shows u(t). In the example of FIG. 18, in the period t s of u hpThe number of positive peaks of (t) is 18, and the number of negative peaks is 17. Therefore, the control unit 300 derives 18 - 2 = 16 as the second candidate value. Also, the control unit 300 derives 17 - 1 = 16 as the third candidate value.

[0118] The control unit 300 compares the first candidate value, the second candidate value, and the third candidate value, and determines the final estimated value of N based on the comparison result. When the first candidate value, the second candidate value, and the third candidate value are equal, the control unit 300 determines this equal value as the estimated value of N. Also, when not all of the first candidate value, the second candidate value, and the third candidate value are equal, and the second candidate value and the third candidate value are equal, the control unit 300 determines the second candidate value or the third candidate value as the estimated value of N. Passing period t s u in hp Since the number of positive peaks of u(t) and the number of negative peaks are correlated, when the second candidate value and the third candidate value are equal, the reliability of the second candidate value and the third candidate value is considered to be higher than that of the first candidate value. Also, when not all of the first candidate value, the second candidate value, and the third candidate value are equal, and the second candidate value and the third candidate value are not equal, among the second candidate value and the third candidate value, (F f ×t s - 1), the closer value is determined as the estimated value of N. In this way, when the second candidate value and the third candidate value are not equal due to the influence of noise or the like, the control unit 300 uses (F f ×t s - 1) as a positive value, and determines the closer value between the second candidate value and the third candidate value to (F f ×t s - 1) as the estimated value of N. However, when the second candidate value and the third candidate value are not equal, the control unit 300 may determine the first candidate value as the estimated value of N. In this way, based on the comparison results of the first candidate value, the second candidate value, and the third candidate value, the control unit 300 can determine the final estimated value of N, thereby deriving N with higher accuracy. Here, since the first candidate value = the second candidate value = the third candidate value = 16, the control unit 300 determines the final value of N to be 16. Here, since the number N of railway vehicles of the railway train 6 is 16, it is confirmed that the control unit 300 has derived the number N of railway vehicles of the railway train 6.

[0119] As described above, with the configuration of this embodiment, the derivation system 10 can derive the number of railway vehicles included in the railway train 6 moving on the bridge 5 from the time-series data of the displacement (deflection) of the observation point on the bridge 5 based on the first feature and the second feature. Also, for the first candidate value, the derivation system 10 obtained it using equations (33) and (34). Further, the derivation system 10 performs high-pass filter processing on u(t) and obtains the second candidate value and the third candidate value respectively using the number of peaks in u hp (t). In this way, the derivation system 10 can obtain each of the first candidate value, the second candidate value, and the third candidate value with a smaller amount of calculation and a lower load compared to the case of obtaining the number of railway vehicles included in the railway train 6 by the inverse analysis method. In this way, the derivation system 10 can obtain the number of railway vehicles configured in the railway train 6 with a lower load.

[0120] (2) Derivation process: Using FIG. 19, the derivation process of the number of railway vehicles of the railway train 6 executed by the server device 3 will be described. The server device 3 starts the process of FIG. 19 in response to the displacement data at the observation point being transmitted from the measurement device 1, but may also start the process of FIG. 19 at an arbitrary timing such as a specified timing. In S100, the control unit 300 acquires the time-series data u(t) of the deflection generated at the observation point from the measurement device 1 by the function of the acquisition unit 301. S100 is an example of an acquisition step.

[0121] In S105, the control unit 300 executes an FFT on u(t) acquired in S100 by the function of the time derivation unit 302. The control unit 300 detects peaks from the FFT result. The control unit 300 identifies the peak corresponding to the minimum frequency excluding the peaks of the side lobes caused by the influence of the window function used in the FFT among the detected peaks. The control unit 300 derives the frequency corresponding to the identified peak as the fundamental frequency F f of u(t).

[0122] In S110, the control unit 300, by the function of the time derivation unit 302, based on the fundamental frequency F f , derives the reciprocal of F f in the same manner as in Equation (35) to derive the period T f . The control unit 300 derives the interval k f using Equation (36) based on the derived T mf and the predetermined period ΔT. The control unit 300 applies a low-pass filter to u(t) by taking the moving average of each value of u(t) in the derived interval k mf . The control unit 300 derives u mf (t) using Equation (39) based on the derived interval k lp .

[0123] Then, the control unit 300 obtains the time when u lp (t) intersects with a predetermined threshold value C L relating to the amount of deflection. The control unit 300 derives the earlier one of the obtained times as the entry time t i of the railway train 6 into the unit bridge girder. Also, the control unit 300 derives the later one of the obtained times as the exit time t o of the railway train 6 from the unit bridge girder. S110 is an example of the time derivation step.

[0124] In S115, the control unit 300, by the function of the number derivation unit 303, based on t i and t o , uses Equation (1) to derive the passing period t s during which the railway train 6 passes through the unit bridge girder.Derive it. Then, the control unit 300 derives the derived t s and the fundamental frequency F derived based on u(t) f and, based on these, uses Equation (33) to calculate the fundamental frequency F s contained in the passing period t f to derive the wave number ν. Based on the derived ν, the control unit 300 uses Equation (34) to derive the number N of railway vehicles included in the railway train 6 as the first candidate value.

[0125] In S120, the control unit 300 performs a high-pass filter process on u(t) to attenuate the components of frequencies lower than the fundamental frequency by subtracting u lp (t) derived in S110 from u(t), and derives u hp (t), which is u(t) subjected to the high-pass filter process. Then, the control unit 300 determines the number of positive peaks from the data for the period from t hp to t i in u o (period t s ). The control unit 300 derives, as the second candidate value, the value obtained by subtracting 2 from the determined number of positive peaks. Also, the control unit 300 determines the number of negative peaks from the data for the period t hp in u s . The control unit 300 derives, as the third candidate value, the value obtained by subtracting 2 from the determined number of negative peaks.

[0126] In S125, the control unit 300 determines, by the function of the number derivation unit 303, whether all of the first candidate value, the second candidate value, and the third candidate value are equal. If the control unit 300 determines that all of the first candidate value, the second candidate value, and the third candidate value are equal, the process proceeds to S130. If the control unit 300 determines that all of the first candidate value, the second candidate value, and the third candidate value are not equal, the process proceeds to S135.

[0127] In S130, the control unit 300 determines, by the function of the number derivation unit 303, the first candidate value (= the second candidate value, the third candidate value) as the final estimated value of the number N of the railway vehicles of the railway train 6. In S135, the control unit 300 determines, by the function of the number derivation unit 303, whether or not the second candidate value and the third candidate value are equal. When the control unit 300 determines that the second candidate value and the third candidate value are equal, the process proceeds to S145. Also, when the control unit 300 determines that the second candidate value and the third candidate value are not equal, the process proceeds to S140.

[0128] In S140, the control unit 300 determines, by the function of the number derivation unit 303, the value closer to (Ff × ts - 1) among the second candidate value and the third candidate value as the estimated value of N. In S145, the control unit 300 determines, by the function of the number derivation unit 303, the second candidate value (= the third candidate value) as the final estimated value of the number N of the railway vehicles of the railway train 6. S115 to S145 are an example of the number derivation step.

[0129] (3) Other embodiments: The above embodiments are an example for implementing the present invention, and various other embodiments can also be adopted. The method of deriving the number of railway vehicles of a railway train from the displacement at the observation point as in the above embodiments can also be realized as an invention of a program and an invention of a method.

[0130] Furthermore, a configuration in which the functions of the server device 3 are realized by a plurality of devices may be adopted. Each function of the server device 3 may be distributed and implemented in a plurality of devices. Also, each function of the server device 3 may be implemented in other devices. For example, each function of the acquisition unit 301, the time derivation unit 302, and the number derivation unit 303 may be implemented in the measurement device 1. A configuration in which the server device 3 is distributed and exists in a plurality of devices may also be possible. Furthermore, the above embodiments are examples, and embodiments in which some configurations are omitted or other configurations are added may be adopted.

[0131] In the above-described embodiment, the derivation system 10 derives the number of railway vehicles included in a railway train 6 formed by railway vehicles that are one or more moving bodies. However, the derivation system 10 may derive the number of moving bodies included in other formed moving bodies. For example, the derivation system 10 may derive the number of sleds included in a formed sled to which one or more sleds are connected. Further, the derivation system 10 may derive the number of vehicles included in a trailer to which one or more vehicles are connected.

[0132] Also, in the above-described embodiment, the derivation system 10 derives the number of moving bodies included in a formed moving body that moves across the bridge 5. However, the derivation system 10 may derive the number of moving bodies included in a formed moving body that moves a structure different from a bridge such as a concrete base that supports a track.

[0133] Also, in the above-described embodiment, the number of sensor devices 2 included in the derivation system 10 is assumed to be two, but it may be one or three or more.

[0134] In the above-described embodiment, the control unit 300 acquires, as the time-series data u(t), the data of the displacement (deflection) measured from the acceleration detected via the acceleration sensor 210. However, the control unit 300 may acquire, as u(t), the data of the displacement of the bridge derived from the physical quantities detected via sensors such as impact sensors, pressure sensors, strain gauges, image measurement devices, load cells, displacement gauges, etc. For example, the control unit 300 may detect the displacement of the observation point by periodically photographing a predetermined object arranged at the observation point of the bridge 5 via an image measurement device, and acquire the data of the detected displacement. Further, the control unit 300 may acquire, as u(t), the data of physical quantities different from the displacement of the bridge. For example, the control unit 300 may acquire, as u(t), the acceleration, velocity, stress, etc. at the observation point of the bridge 5. Further, the control unit 300 may acquire, as u(t), the number of pixels corresponding to the displacement amount of a predetermined object arranged at the observation point of the bridge 5 in the image photographed via an image measurement device. Further, the control unit 300 may acquire the data of a plurality of types of physical quantities (for example, displacement, stress, etc.) generated at the observation point as a response to the movement of the railway train 6 over the unit bridge girder.

[0135] In the above-described embodiment, the derivation system 10 obtained the first candidate value, the second candidate value, and the third candidate value respectively, and obtained the final estimated value of N based on the comparison result of the obtained first candidate value, second candidate value, and third candidate value. However, the derivation system 10 may derive any one of the first candidate value, the second candidate value, and the third candidate value as the final estimated value of N. In that case, it may be unnecessary to derive the other two candidate values.

[0136] In the above-described embodiment, the control unit 300 specifies the peak corresponding to the lowest frequency, excluding the side lobes caused by the influence of the window function used in the FFT, from the result of the FFT for the time-series data u(t) acquired by the function of the acquisition unit 301, and determines the specified peak as the fundamental frequency F f However, the control unit 300 takes into account the influence of the noise generated in the result of the FFT for u(t), and the fundamental frequency F fmay be obtained. For example, the control unit 300 identifies peaks equal to or higher than a predetermined threshold corresponding to the lowest frequency from the result of the FFT for u(t), excluding the side lobes caused by the influence of the window function used in the FFT, and determines the identified peaks as the fundamental frequency F f and may be obtained.

[0137] The time series data may be data acquired at a data rate that is two or more times the frequency of vibration assumed to be generated in the structure due to the movement of the moving object being arranged.

[0138] Furthermore, the present invention is also applicable as a program executed by a computer or as a method. Also, the above program and method may be realized as a single device or may be realized by using components provided in a plurality of devices, and include various aspects. Also, it can be appropriately changed, such as part being software and part being hardware. Furthermore, the invention is also established as a recording medium for the program. Of course, the recording medium for the program may be a magnetic recording medium, a semiconductor memory, etc., and can be considered in exactly the same way for any recording medium developed in the future.

Explanation of Reference Numerals

[0139] 1... Measuring device, 2... Sensor device, 3... Server device, 4... Communication network, 5... Bridge, 6... Railway train, 7... Superstructure, 7a... Bridge deck, 7b... Support, 7c... Rail, 7d... Sleeper, 7e... Ballast, F... Floor slab, G... Main girder, 8... Substructure, 8a... Pier, 8b... Abutment, 10... Derivation system, 100... Control unit, 110... Storage unit, 120... Communication unit, 200... Control unit, 210... Acceleration sensor, 220... Storage unit, 230... Communication unit, 300... Control unit, 301... Acquisition unit, 302... Time derivation unit, 303... Number derivation unit, 310... Storage unit, 320... Communication unit

Claims

1. An acquisition step of acquiring time-series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of a formation mobile body formed by one or more mobile bodies moving the structure; A time derivation step of deriving an entry time and an exit time of the formation mobile body with respect to the structure based on the time-series data; When the length of the structure is LB and the length of the mobile body is Lc, and Lc / 2 < LB < 3Lc / 2 is satisfied, based on the time-series data, the entry time, and the exit time, a number derivation step of deriving the number of mobile bodies included in the formation mobile body; comprising: In the number derivation step, a value obtained by rounding to an integer after subtracting 1 from a wave number that is a product of a period from the entry time to the exit time in the time-series data and a fundamental frequency of the time-series data is derived as the number of mobile bodies; Derivation method.

2. An acquisition step of acquiring time-series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of a formation mobile body formed by one or more mobile bodies moving the structure; A time derivation step of deriving an entry time and an exit time of the formation mobile body with respect to the structure based on the time-series data; When the length of the structure is LB and the length of the mobile body is Lc, and Lc / 2 < LB < 3Lc / 2 is satisfied, based on the time-series data, the entry time, and the exit time, a number derivation step of deriving the number of mobile bodies included in the formation mobile body; comprising: In the number derivation step, a value obtained by subtracting 2 from the number of positive peaks within a period from the entry time to the exit time in the time-series data subjected to high-pass filter processing for attenuating components of frequencies less than the fundamental frequency of the time-series data is derived as the number of mobile bodies; Derivation method.

3. An acquisition step of acquiring time-series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of a formation mobile body formed by one or more mobile bodies moving the structure; A time derivation step of deriving an entry time and an exit time of the formation mobile body with respect to the structure based on the time-series data; When the length of the structure is \(L_B\) and the length of the moving body is \(L_C\), and when \(L_C / 2 \lt L_B \lt 3L_C / 2\), a number derivation step of deriving the number of moving bodies included in the organized moving body based on the time series data, the entry time, and the exit time; including; In the number derivation step, a value obtained by subtracting 1 from the number of negative peaks within the period from the entry time to the exit time in the time series data subjected to high-pass filter processing for attenuating vibration components having frequencies lower than the fundamental frequency of the time series data is derived as the number of moving bodies. Derivation method. **Claim 4** An acquisition step of acquiring time series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of an organized moving body in which one or more moving bodies are organized; A time derivation step of deriving an entry time and an exit time of the organized moving body with respect to the structure based on the time series data; When the length of the structure is \(L_B\) and the length of the moving body is \(L_C\), and when \(L_C / 2 \lt L_B \lt 3L_C / 2\), a number derivation step of deriving the number of moving bodies included in the organized moving body based on the time series data, the entry time, and the exit time; including; In the number derivation step, a first candidate value obtained by rounding down to an integer a value obtained by subtracting 1 from a wave number that is the product of the period from the entry time to the exit time in the time series data and the fundamental frequency of the time series data, a second candidate value obtained by subtracting 2 from the number of positive peaks within the period from the entry time to the exit time in the time series data subjected to high-pass filter processing for attenuating vibration components having frequencies lower than the fundamental frequency of the time series data, and a third candidate value obtained by subtracting 1 from the number of negative peaks within the period from the entry time to the exit time in the time series data subjected to high-pass filter processing, the number of moving bodies included in the organized moving body is derived based on the comparison result of these. Derivation method. **Claim 5** In the time derivation step, for each of the entry time and the exit time, a process of obtaining a time within a period after one of two times corresponding to two consecutive data sandwiching a predetermined threshold value and before the other time, the two consecutive data being included in the time series data that has undergone low-pass filter processing for attenuating vibration components having a frequency equal to or higher than the fundamental frequency of the time series data, is performed, thereby deriving the entry time and the exit time. The derivation method according to any one of claims 1 to 4.

6. In the number derivation step, when the first candidate value and the second candidate value are not equal and the second candidate value and the third candidate value are equal, the second candidate value is determined as the number of the moving bodies included in the formation moving body. The derivation method according to claim 4.

7. In the number derivation step, when the second candidate value and the third candidate value are not equal, the value closer to the value obtained by subtracting 1 from the wave number among the second candidate value and the third candidate value is derived as the number of the moving bodies included in the formation moving body. The derivation method according to claim 4.

8. The model of the deflection of the structure is an expression based on the structure of the structure. The derivation method according to any one of claims 1 to 7.

9. The structure is in the form of a simple beam supported at both ends. The derivation method according to any one of claims 1 to 8.

10. The structure is a bridge. The derivation method according to any one of claims 1 to 9.

11. The moving body is a railway vehicle that moves on the structure via wheels. The derivation method according to any one of claims 1 to 10.

12. The time series data is data based on data detected via at least one of an acceleration sensor, a shock sensor, a pressure sensor, a strain gauge, an image measuring device, a load cell, and a displacement meter. The derivation method according to any one of claims 1 to 11.

13. The structure is applicable to BWIM (Bridge Weigh in Motion). The derivation method according to any one of claims 1 to 12.

14. An acquisition unit that acquires time series data including a physical quantity generated at a predetermined observation point in the structure as a response when a formation moving body formed by one or more moving bodies moves on the structure; A time derivation unit that derives an entry time and an exit time of the formation moving body with respect to the structure based on the time series data; When the length of the structure is \(L_B\) and the length of the moving body is \(L_c\), when \(L_c / 2 < L_B < 3L_c / 2\) is satisfied, a number derivation unit that derives the number of moving bodies included in the organized moving body based on the time-series data, the entry time, and the exit time; comprising; The number derivation unit derives, as the number of the moving bodies, a value obtained by rounding to an integer after subtracting 1 from a wave number that is a product of a period from the entry time to the exit time in the time-series data and a fundamental frequency of the time-series data. Derivation device.

15. An acquisition unit that acquires time-series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of an organized moving body formed by organizing one or more moving bodies; A time derivation unit that derives an entry time and an exit time of the organized moving body with respect to the structure based on the time-series data; When the length of the structure is \(L_B\) and the length of the moving body is \(L_c\), when \(L_c / 2 < L_B < 3L_c / 2\) is satisfied, a number derivation unit that derives the number of moving bodies included in the organized moving body based on the time-series data, the entry time, and the exit time; comprising; The number derivation unit derives, as the number of the moving bodies, a value obtained by subtracting 2 from the number of positive peaks within a period from the entry time to the exit time in the time-series data subjected to a high-pass filter process that attenuates components having a frequency lower than the fundamental frequency of the time-series data. Derivation device.

16. An acquisition unit that acquires time-series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of an organized moving body formed by organizing one or more moving bodies; A time derivation unit that derives an entry time and an exit time of the organized moving body with respect to the structure based on the time-series data; When the length of the structure is \(L_B\) and the length of the moving body is \(L_c\), when \(L_c / 2 < L_B < 3L_c / 2\) is satisfied, a number derivation unit that derives the number of moving bodies included in the organized moving body based on the time-series data, the entry time, and the exit time; comprising; The number derivation unit derives, as the number of the moving bodies, a value obtained by subtracting 1 from the number of negative peaks within a period from the entry time to the exit time in the time-series data on which a high-pass filter process for attenuating vibration components having frequencies lower than the fundamental frequency of the time-series data is performed. Derivation device. **Claim 17** An acquisition unit that acquires time-series data including a physical quantity generated at a predetermined observation point in the structure as a response when an organized moving body formed of one or more moving bodies moves the structure; A time derivation unit that derives, based on the time-series data, an entry time and an exit time of the organized moving body with respect to the structure; When the length of the structure is LB and the length of the moving body is Lc, and LB satisfies Lc / 2 < LB < 3Lc / 2, a number derivation unit that derives the number of the moving bodies included in the organized moving body based on the time-series data, the entry time, and the exit time; Comprising: The number derivation unit calculates a first candidate value obtained by subtracting 1 from a wave number that is a product of a period from the entry time to the exit time in the time-series data and the fundamental frequency of the time-series data and rounding down to an integer, a second candidate value obtained by subtracting 2 from the number of positive peaks within a period from the entry time to the exit time in the time-series data on which a high-pass filter process for attenuating vibration components having frequencies lower than the fundamental frequency of the time-series data is performed, and a third candidate value obtained by subtracting 1 from the number of negative peaks within a period from the entry time to the exit time in the time-series data on which the high-pass filter process is performed, and derives the number of the moving bodies included in the organized moving body based on a comparison result thereof. Derivation device. **Claim 18** A derivation system comprising a derivation device and a sensor, wherein The derivation device includes: An acquisition unit that acquires time-series data including a physical quantity generated at a predetermined observation point in the structure as a response when an organized moving body formed of one or more moving bodies moves the structure, the physical quantity being measured via the sensor; A time derivation unit that derives, based on the time-series data, an entry time and an exit time of the organized moving body with respect to the structure; When the length of the structure is \(L_B\) and the length of the moving body is \(L_c\), when \(L_c / 2 \lt L_B \lt 3L_c / 2\) is satisfied, based on the time-series data, the entry time, and the exit time, a number derivation unit that derives the number of moving bodies included in the organized moving body comprising The number derivation unit derives, as the number of the moving bodies, a value obtained by subtracting 1 from a wave number that is the product of a period from the entry time to the exit time in the time-series data and the fundamental frequency of the time-series data and then rounding to an integer. Derivation system.

19. A derivation system comprising a derivation device and a sensor, wherein the derivation device an acquisition unit that acquires time-series data including a physical quantity that occurs at a predetermined observation point in the structure as a response to the movement of an organized moving body formed by one or more moving bodies moving the structure, and the physical quantity measured via the sensor a time derivation unit that derives an entry time and an exit time of the organized moving body with respect to the structure based on the time-series data When the length of the structure is \(L_B\) and the length of the moving body is \(L_c\), when \(L_c / 2 \lt L_B \lt 3L_c / 2\) is satisfied, based on the time-series data, the entry time, and the exit time, a number derivation unit that derives the number of moving bodies included in the organized moving body comprising The number derivation unit derives, as the number of the moving bodies, a value obtained by subtracting 2 from the number of positive peaks within a period from the entry time to the exit time in the time-series data subjected to a high-pass filter process that attenuates components having a frequency lower than the fundamental frequency of the time-series data. Derivation system.

20. A derivation system comprising a derivation device and a sensor, wherein the derivation device an acquisition unit that acquires time-series data including a physical quantity that occurs at a predetermined observation point in the structure as a response to the movement of an organized moving body formed by one or more moving bodies moving the structure, and the physical quantity measured via the sensor a time derivation unit that derives an entry time and an exit time of the organized moving body with respect to the structure based on the time-series data When the length of the structure is \(L_B\) and the length of the moving body is \(L_C\), when \(L_C / 2 < L_B < 3L_C / 2\) is satisfied, based on the time-series data, the entry time, and the exit time, a number derivation unit that derives the number of moving bodies included in the organized moving body; comprising; The number derivation unit derives, as the number of the moving bodies, a value obtained by subtracting 1 from the number of negative peaks within the period from the entry time to the exit time in the time-series data subjected to a high-pass filter process that attenuates vibration components having a frequency lower than the fundamental frequency of the time-series data. Derivation system.

21. A derivation system comprising a derivation device and a sensor, wherein the derivation device an acquisition unit that acquires time-series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of an organized moving body formed by one or more moving bodies moving the structure, the physical quantity being measured via the sensor; a time derivation unit that derives, based on the time-series data, an entry time and an exit time of the organized moving body with respect to the structure; When the length of the structure is \(L_B\) and the length of the moving body is \(L_C\), when \(L_C / 2 < L_B < 3L_C / 2\) is satisfied, based on the time-series data, the entry time, and the exit time, a number derivation unit that derives the number of moving bodies included in the organized moving body; comprising; The number derivation unit calculates a first candidate value obtained by subtracting 1 from the wave number, which is the product of the period from the entry time to the exit time in the time-series data and the fundamental frequency of the time-series data, and rounding it to an integer, a second candidate value obtained by subtracting 2 from the number of positive peaks within the period from the entry time to the exit time in the time-series data subjected to a high-pass filter process that attenuates vibration components having a frequency lower than the fundamental frequency of the time-series data, and a third candidate value obtained by subtracting 1 from the number of negative peaks within the period from the entry time to the exit time in the time-series data subjected to the high-pass filter process, and based on the comparison result of these, derives the number of moving bodies included in the organized moving body. Derivation system.

22. In a computer, an acquisition step of acquiring time-series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of an organized moving body formed by one or more moving bodies moving the structure; A time derivation step of deriving an entry time and an exit time of the assembled moving body with respect to the structure based on the time series data When the length of the structure is LB and the length of the moving body is Lc, when Lc / 2 < LB < 3Lc / 2 is satisfied, based on the time series data, the entry time, and the exit time, a number derivation step of deriving the number of moving bodies included in the assembled moving body A program for causing the execution In the number derivation step, a value obtained by subtracting 1 from a wave number that is the product of a period from the entry time to the exit time in the time series data and the fundamental frequency of the time series data and rounding to an integer is derived as the number of moving bodies Program

23. To a computer An acquisition step of acquiring time series data including a physical quantity generated at a predetermined observation point in the structure as a response when an assembled moving body formed by one or more moving bodies moves the structure A time derivation step of deriving an entry time and an exit time of the assembled moving body with respect to the structure based on the time series data When the length of the structure is LB and the length of the moving body is Lc, when Lc / 2 < LB < 3Lc / 2 is satisfied, based on the time series data, the entry time, and the exit time, a number derivation step of deriving the number of moving bodies included in the assembled moving body A program for causing the execution In the number derivation step, a value obtained by subtracting 2 from the number of positive peaks within a period from the entry time to the exit time in the time series data subjected to high-pass filter processing for attenuating components having a frequency less than the fundamental frequency of the time series data is derived as the number of moving bodies Program

24. To a computer An acquisition step of acquiring time series data including a physical quantity generated at a predetermined observation point in the structure as a response when an assembled moving body formed by one or more moving bodies moves the structure A time derivation step of deriving an entry time and an exit time of the assembled moving body with respect to the structure based on the time series data When the length of the structure is \(L_B\) and the length of the moving body is \(L_C\), when \(L_C / 2 < L_B < 3L_C / 2\) is satisfied, a number derivation step of deriving the number of moving bodies included in the organized moving body based on the time-series data, the entry time, and the exit time. A program for causing the execution of: In the number derivation step, a value obtained by subtracting 1 from the number of negative peaks within the period from the entry time to the exit time in the time-series data subjected to high-pass filter processing for attenuating vibration components having frequencies lower than the fundamental frequency of the time-series data is derived as the number of the moving bodies. Program.

25. Causing a computer to: An acquisition step of acquiring time-series data including a physical quantity generated at a predetermined observation point in the structure as a response to the movement of an organized moving body in which one or more moving bodies are organized moving the structure. A time derivation step of deriving the entry time and the exit time of the organized moving body with respect to the structure based on the time-series data. When the length of the structure is \(L_B\) and the length of the moving body is \(L_C\), when \(L_C / 2 < L_B < 3L_C / 2\) is satisfied, a number derivation step of deriving the number of moving bodies included in the organized moving body based on the time-series data, the entry time, and the exit time. A program for causing the execution of: In the number derivation step, a first candidate value obtained by subtracting 1 from the wave number which is the product of the period from the entry time to the exit time in the time-series data and the fundamental frequency of the time-series data and rounded to an integer, a second candidate value obtained by subtracting 2 from the number of positive peaks within the period from the entry time to the exit time in the time-series data subjected to high-pass filter processing for attenuating vibration components having frequencies lower than the fundamental frequency of the time-series data, and a third candidate value obtained by subtracting 1 from the number of negative peaks within the period from the entry time to the exit time in the time-series data subjected to the high-pass filter processing, and based on the comparison result of these, the number of moving bodies included in the organized moving body is derived. Program.

Images