JP7245120B2 - Structure judgment system - Google Patents

Description

The present invention relates to a structure determination system for determining the state of structures.

Conventionally, it has been proposed to identify the vibrations at a plurality of locations of the bridge by analyzing the image of the bridge and grasp the progress of deterioration of the bridge (see, for example, Patent Document 1).

JP 2017-207339 A

A structure is usually configured including a plurality of structural members. For example, a bridge includes girders, which are superstructures, abutments, which are substructures, and bearings, which are structural members connecting them. For such a structure, it is not necessarily possible to appropriately estimate the state of the structure, such as progress of deterioration, simply by using vibrations at a plurality of locations.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a structure determination system capable of appropriately determining the state of a building such as a bridge.

In order to achieve the above object, a structure determination system according to the present invention is a structure determination system for determining the state of a structure, comprising: change information indicating a relative change between two parts of the structure; a variation information acquisition unit that acquires a combination of a plurality of parts, and a relative variation of a combination of predetermined parts, a combination other than the predetermined part indicated by the variation information acquired by the variation information acquisition unit a prediction unit that makes predictions based on typical fluctuations, a relative change in a combination of predetermined portions predicted by the prediction unit, and a combination of the predetermined portions indicated by the change information acquired by the change information acquisition unit and a determination unit that determines the state of the structure by comparing with the relative variation of .

In the structure determination system according to the present invention, the state of the structure is determined by appropriately using the relative variation in the combination of multiple parts of the structure. Therefore, according to the structure determination system according to the present invention, it is possible to appropriately determine the state of a building such as a bridge.

ADVANTAGE OF THE INVENTION According to this invention, the state of buildings, such as a bridge, can be determined appropriately.

It is a figure showing composition of a server which is a structure judging system concerning an embodiment of the present invention. FIG. 4 is a diagram showing an example of an image used for structure determination; 4 is a table showing displacement values calculated from an image; It is a figure which shows the tensor used for determination of a structure. It is a graph which shows the image of the data of a tensor. 4 is a flow chart showing processing executed by a server, which is the structure determination system according to the embodiment of the present invention; It is a figure for demonstrating a modification. It is a figure which shows the hardware constitutions of the server which is the structure determination system which concerns on embodiment of this invention.

Hereinafter, an embodiment of a structure determination system according to the present invention will be described in detail with reference to the drawings. In the description of the drawings, the same elements are denoted by the same reference numerals, and overlapping descriptions are omitted.

FIG. 1 shows a server 10 which is a structure determination system according to this embodiment. The server 10 is a system that determines the state of structures. A structure to be determined is, for example, a bridge 30 as shown in FIG. However, the structure to be determined is not limited to the bridge 30, and may be any structure such as a building. In this embodiment, among the parts of the bridge 30, in particular, the supporting part 33, which is a structural member that connects the girder 31, which is the upper structure, and the abutment 32, which is the lower structure, and the surrounding parts thereof are targeted for determination. The determination target may be the bearing portion 33, which is a movable bearing capable of horizontal movement and rotation. However, other than this may be used as the determination target. The state of (part of) the structure to be determined is, for example, whether or not there is an abnormality (for example, deterioration) in the structure. The server 10 may determine the state of each part of the structure. The result of determination by the server 10 is used, for example, to determine whether to reinforce or repair the structure.

The server 10 is realized by, for example, a server device. Also, the server 10 may be implemented by a plurality of server devices, that is, computer systems. The server 10 has a communication function and can transmit and receive information to and from other devices.

The server 10 determines the state of the structure using the moving image captured by the camera 20 . The camera 20 is an imaging device that captures (a portion of) a structure to be determined and obtains a moving image of the structure. The camera 20 is preliminarily fixedly installed at a position where (a part of) the structure can be imaged. As the camera 20, a well-known camera capable of imaging with a resolution that can be used to determine the state of the structure can be used. As shown in FIG. 1, a plurality of cameras 20 may be provided for each portion of the structure to be determined. Note that the determination described below is performed for each (moving image captured by) the camera 20 . The server 10 and the camera 20 can exchange information with each other. The camera 20 captures an image of the building at a preset frame rate (fps) and transmits the captured moving image to the server 10 .

As shown in FIG. 1 , the server 10 functionally includes a variation information acquisition unit 11 , a prediction unit 12 , and a determination unit 13 .

The variation information acquisition unit 11 is a functional unit that acquires variation information indicating a relative variation between two parts of a structure for a combination of a plurality of parts. The variation information acquisition unit 11 may acquire a moving image of a structure, calculate a relative variation based on the acquired moving image, and acquire variation information.

Determination of the state of the structure by the server 10 is performed based on changes occurring in the structure. For example, when the structure to be determined is the bridge 30 as in the present embodiment, when a vehicle such as an automobile passes over the bridge 30, the bridge 30 vibrates according to the passage of the vehicle. The state of the bridge 30 is determined based on the change in the portion of the bridge 30 caused by the vibration.

The variation information acquisition unit 11 acquires variation information, for example, as follows. The variation information acquisition unit 11 receives and acquires a moving image of a structure, which is transmitted from the camera 20 . The variation information acquisition unit 11 may acquire the variation information using only the portion of the set time period in the received moving image. The time period is, for example, a time period designated by the administrator of the server 10, and is a time period during which the vehicle passes over the bridge 30 and the structure vibrates. The variation information acquisition unit 11 detects displacements in sub-pixel units from the received moving image using a conventional technique, and detects variations (vibrations) in a plurality of parts of the building. Three or more parts are used to detect variations so that a plurality of combinations of two parts can be configured.

FIG. 2 shows an example of images forming a moving image. In the image, a plurality of regions (ROI: Regions of Interest) 40, which are portions (measurement points) for detecting variations, are positioned and set in advance. A plurality of regions 40 are set in each of the girder 31 , the upper and lower shoes 33 a , 33 b and bottom plate 33 c of the bearing portion 33 and the abutment 32 . In the example of the image shown in FIG. 2, the members forming the bridge 30 appearing in the area 40 differ depending on the position of the area 40 in the I-axis direction, which is the vertical direction. Also, the position within the same member reflected in the region 40 differs depending on the position of the region 40 in the J-axis direction, which is the horizontal direction. A roller 33d is provided on the lower shoe 33b inside the bottom plate 33c, but it is not shown in the image because it is positioned inside the bottom plate 33c. The plurality of regions 40 in which variations are detected may be set across different members as in the I-axis direction, or may be set in the same member as in the J-axis direction. They may be mixed.

It is assumed that the number of regions 40 provided in the J-axis direction is the same at any position in the I-axis direction. This is for properly creating a tensor, which will be described later. For example, on the lower side of the image where the regions 40 are provided over a wider range, the regions are provided at larger intervals than on the upper side of the image. However, the region 40 may be provided at locations other than those described above. The variation information acquisition unit 11 stores the position of each region 40 in advance.

The variation information acquisition unit 11 calculates the positional deviation (displacement amount) of the image from the reference image for each region 40 of each image that constitutes the moving image as variation in each portion. The reference image is, for example, the first image of the moving image for which variation is to be calculated. For example, the variation information acquiring unit 11 calculates the variation as a value of displacement in each of the I-axis direction and the J-axis direction. The amount of displacement is the amount of displacement in a preset direction in each axial direction. Therefore, when the position is shifted in the direction opposite to the preset direction, the value of the displacement amount becomes negative.

FIG. 3 shows an example of a table of calculated displacement amount values. A displacement amount value (x _i ,j ) in the I-axis direction and a displacement amount value (y _{i,j ) in the J-axis direction are obtained for each time corresponding to the position (i, j} ) of the region 40 and each image. Here, i and j are indices of the region 40 in the I-axis direction and the J-axis direction, respectively. Moreover, the value of the amount of displacement is a value for each time, that is, a time-series value. In this embodiment, the number of regions 40 in the I-axis direction is I, the number of regions 40 in the J-axis direction is J, and the number of displacements in the K direction, which is the time axis, is K. FIG.

From the calculated time-series displacement amount values (x, y), the variation information acquisition unit 11 determines that the size is I×J×K and that the spatial maintenance relationship of each region 40 is held as shown in FIG. generates a 3rd order tensor T that FIG. 5(a) shows an image 50 of T _i,j as time-series data. T _i,j,k corresponds to one sample (point corresponding to one time) in the graph of FIG. 5(a). T _i,j,k includes values of the displacement amounts in the I-axis direction (x _i,j ) and the J-axis direction (y _i,j ) at time k.

Based on the calculated tensor T, the variation information acquisition unit 11 calculates variation information indicating the relative variation between the two regions 40 of the structure. In the present embodiment, the relative fluctuations are the value of displacement in the I-axis direction (x _i,j ) and the value of displacement in the J-axis direction (y _{i , j} ). The variation information acquisition unit 11 calculates, as variation information, a tensor T′ representing the value of the amount of displacement of each region 40 as viewed from the region 40 as a reference for each region 40 . With respect to the position (i _r ,j _r ) of the region 40 as a reference, the element T _{′ k,i,j} of the tensor T′ becomes T _i,j,k −T _ir,jr,k . FIG. 5(b) shows an image 51 of T'i _,j as time-series data. The variation information acquiring unit 11 calculates T′ each time all the regions 40 are used as reference regions 40 . The variation information acquiring unit 11 sets the tensor T′ of the number L of the positions (i, j) of the region 40 serving as the reference as the fourth-order tensor T″. The variation information acquisition unit 11 outputs the generated fourth order tensor T″ to the prediction unit 12 and the determination unit 13 .

Note that the amount of displacement of another area 40 viewed from a certain area 40 and the amount of displacement of a certain area 40 viewed from another area 40 have the same value with opposite directions of displacement. may contain only one of them.

The prediction unit 12 is a functional unit that predicts the relative fluctuation of the combination of the predetermined portions based on the relative fluctuation of the combination other than the predetermined portions indicated by the fluctuation information acquired by the fluctuation information acquisition unit 11. is. The prediction unit 12 predicts the relative fluctuation of the combination between the predetermined parts by tensor decomposition of the tensor T″ configured by the fluctuation information.

The prediction unit 12 predicts a predetermined value of T _{′ i,j} at a predetermined reference position (i _r , j _r ) from other values of the tensor T″. The prediction unit 12 performs the above prediction using, for example, weighted optimization (CP-WOPT (Weighted Optimization)) based on CP (Canonical Polyadic) decomposition. The reference position (i _r , j _r ) to be predicted and T _{′ i, j} (i _r , j _r , i, j of (that is, the combination of the positions of the region 40 to be predicted) are set in advance is set. The prediction unit 12 treats the value of the element of T' _i,j to be predicted (the element of the index for which the state of the structure is to be detected) in T'' as a missing value. The prediction unit 12 calculates a tensor TD″ in which the value of the missing element is set to 0 among the elements of T″.

The prediction unit 12 stores in advance a weight tensor W having the same size as the tensor T'' corresponding to the reference position (i _r , j _r ) to be predicted and T _{′ i, j} (or can be calculated at this point). The tensor W is a tensor in which the value of the element corresponding to T′ _i,j to be predicted (the element treated as missing) is 0, and the value of the other elements (used for prediction) is 1.

The prediction unit 12 calculates a tensor TP″ including prediction data based on the following formula (that is, complements the missing portion).
TP''=W*TD''+(1-W)*[A ^{(I axis)} , A ^{(J axis)} , A ^{(K axis)} , A ^{(L axis)} ]
In the above formula, * indicates an element product. 1 is a tensor of the same size as W with all elements equal to 1. Each of A ^{(I axis)} , A ^{(J axis)} , A ^{(K axis)} , and A ^{(L axis)} is a factor tensor of each axis obtained by CP-WOPT. [. . . ] is a tensor of the same size as TD″ generated from the tensor product of the factor tensors. The value of the element corresponding to the prediction target element of TP'' is the predicted value.

The prediction unit 12 may, for example, predict the reference position (i _r , j _r ) and T _{′ i, j} designated by the administrator of the server 10 . The prediction unit 12 may also predict combinations of a plurality of reference positions (i _r , j _r ) and T _{′ i, j} . In that case, the prediction unit 12 calculates a plurality of TP'' corresponding thereto. Also, the prediction unit 12 may predict all combinations of reference positions (i _r , j _r ) and T _{′ i, j} . The prediction unit 12 outputs the calculated TP″ to the determination unit 13 .

The determination unit 13 determines the relative variation in the combination of the predetermined portions predicted by the prediction unit 12 and the relative variation in the combination of the predetermined portions indicated by the variation information acquired by the variation information acquisition unit 11. It is a functional unit that determines the state of the structure by comparing the For example, the determination unit 13 makes determinations as follows.

The determination unit 13 receives T″, which is actually measured data of fluctuation, from the fluctuation information acquisition unit 11 . The determination unit 13 receives from the prediction unit 12 TP″ including prediction data (complementary data) of fluctuation. The determining unit 13 calculates the difference E between the measured data and the predicted data for the element of the combination of the positions of the region 40 to be predicted, using the following formula.
E=(1−W)*(T″−TP″)

The determination unit 13 calculates the Frobenius norm D=||E|| _F using all the elements of E. The determination unit 13 compares the calculated value of D with a preset threshold, and determines that there is an abnormality in the structure if D is greater than the threshold. This determination is based on the idea that if there is no abnormality in the structure, there will be no difference between the measured data and the predicted data.

Further, the determining unit 13 may calculate the above E for a plurality of combinations of positions of the region 40 and compare D calculated for each combination with other positions with a threshold. If the number of D's larger than the threshold is larger than a preset constant number, the determination unit 13 may determine that there is an abnormality at that position. In addition, the determination part 13 may determine by methods other than the above.

The determination unit 13 outputs information indicating the determination result. The determination unit 13, for example, transmits the information to a client terminal connected to the server 10 and causes the information to be displayed. The output from the determination unit 13 is, for example, referred to by the user and used to determine whether to reinforce or repair the building, as described above. Note that the output by the determination unit 13 may be performed to a device other than the above or in a form other than the above. The above is the configuration of the server 10 according to the present embodiment.

Subsequently, processing executed by the server 10 according to the present embodiment (operation method executed by the server 10) will be described using the flowchart of FIG. First, a moving image captured by the camera 20 is transmitted from the camera 20 to the server 10, and received and acquired by the variation information acquisition unit 11 (S01). Subsequently, the change information acquisition unit 11 calculates time-series displacement amounts for a plurality of regions 40, which are image portions forming a moving image (S02). Subsequently, the variation information acquisition unit 11 generates a tensor T'' relating to the relative displacement amount between the regions 40 (S03).

Subsequently, the prediction unit 12 calculates a tensor TP'' including prediction data by tensor decomposition from the tensor T'' (S04). Subsequently, the determination unit 13 compares the predicted data and the measured data. Specifically, a difference E between the measured data and the predicted data is calculated (S05). Subsequently, the determination unit 13 determines the state of the structure based on the difference E (S06). Subsequently, the determination unit 13 outputs information indicating the determination result of the state of the building (S07). The above is the processing executed by the server 10 according to the present embodiment.

As described above, in this embodiment, the relative variation in the combination of multiple parts of the structure is appropriately used to determine the state of the structure. If the members that make up the structure are healthy, they will move to perform the desired function (for example, if the support section 33 has a function to absorb the deformation of the upper structure), there will be no correlation between the motions of adjacent members. be. In order to understand the function of a structure, it is important to measure the relative variation between multiple parts, especially between spatially close parts. Therefore, according to this embodiment, it is possible to appropriately determine the state of a building such as a bridge.

Also, relative fluctuations may be predicted by tensor decomposition as in this embodiment. According to this configuration, prediction can be made appropriately and reliably, and the state of the building can be determined appropriately and reliably. However, a method other than the present embodiment may be used for prediction.

Also, relative changes may be calculated based on a moving image of a structure as in this embodiment. According to this configuration, the variation information can be obtained easily and reliably, and the state of the building can be easily and reliably determined. However, the relative variation need not be based on moving images. For example, sensors (for example, displacement sensors or strain gauges) that detect variations may be provided in a plurality of parts of the structure, and variation information may be calculated using the variations detected by the sensors.

Subsequently, a modification of this embodiment will be described. The prediction unit 12 predicts the relative variation of the combination between predetermined portions for each of the plurality of timings, and calculates the factor tensor obtained for any one of the plurality of timings in the prediction for each of the plurality of timings. may be used. For example, when a vehicle continuously passes over a structure whose state is to be determined, and the structure periodically fluctuates (vibrates), the prediction unit 12 makes a prediction for each cycle. may be

As shown in FIG. 7, the prediction unit 12 divides the tensor T described above into tensors T used for prediction by dividing the period length 1/f (f is the frequency of fluctuation) in the direction of the time axis. FIG. 7(a) shows the tensor T described above. A part of the tensor T indicated by a dashed line in FIG. 7A is divided. FIG. 7(b) shows time zones into which T _i,j as time series data is divided. The prediction unit 12 inputs and stores information indicating the length of the cycle in advance, and performs division based on the information.

The prediction unit 12 makes a prediction using each of the divided tensors T. FIG. The prediction unit 12 predicts any one of the divided tensors T, for example, the first tensor T, in the same manner as described above. The prediction unit 12 stores the factor tensor calculated during prediction. The prediction unit 12 predicts other tensors T using the stored factor tensors. That is, the prediction unit 12 shifts the prediction target tensor T by 1/f, divides the process into multiple processes, and continues to use the factor tensor calculated only for the first time for transition prediction. The determination unit 13 uses the prediction results from the prediction unit 12 to make determinations in the same manner as described above. By performing prediction in this way, the calculation cost of the prediction by the prediction unit 12 can be reduced.

Note that the time periods (timings) to be predicted need not be divided into the same length as described above, and may be arbitrarily set as long as they have the same length.

It should be noted that the block diagrams used in the description of the above embodiments show blocks in units of functions. These functional blocks (components) are realized by any combination of at least one of hardware and software. Also, the method of implementing each functional block is not particularly limited. That is, each functional block may be implemented using one device that is physically or logically coupled, or directly or indirectly using two or more devices that are physically or logically separated (e.g. , wired, wireless, etc.) and may be implemented using these multiple devices. A functional block may be implemented by combining software in the one device or the plurality of devices.

Functions include judging, determining, determining, calculating, calculating, processing, deriving, investigating, searching, checking, receiving, transmitting, outputting, accessing, resolving, selecting, choosing, establishing, comparing, assuming, expecting, assuming, Broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, assigning, etc. can't For example, a functional block (component) that makes transmission work is called a transmitting unit or a transmitter. In either case, as described above, the implementation method is not particularly limited.

For example, the server 10 in one embodiment of the present disclosure may function as a computer that performs information processing of the present disclosure. FIG. 8 is a diagram illustrating an example of a hardware configuration of server 10 according to an embodiment of the present disclosure. The server 10 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, and the like.

Note that in the following description, the term "apparatus" can be read as a circuit, device, unit, or the like. The hardware configuration of the server 10 may be configured to include one or more of each device shown in the figure, or may be configured without some of the devices.

Each function in the server 10 is performed by causing the processor 1001 to perform calculations, controlling communication by the communication device 1004, controlling communication by the communication device 1004, and controlling the communication by the memory 1002 and It is realized by controlling at least one of data reading and writing in the storage 1003 .

The processor 1001, for example, operates an operating system to control the entire computer. The processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic device, registers, and the like. For example, the server 10 described above may be implemented by the processor 1001 .

The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 to the memory 1002, and executes various processes according to these. As the program, a program that causes a computer to execute at least part of the operations described in the above embodiments is used. For example, the server 10 may be implemented by a control program stored in the memory 1002 and running on the processor 1001 . Although it has been explained that the above-described various processes are executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. FIG. Processor 1001 may be implemented by one or more chips. Note that the program may be transmitted from a network via an electric communication line.

The memory 1002 is a computer-readable recording medium, and is composed of at least one of, for example, ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), and RAM (Random Access Memory). may be The memory 1002 may also be called a register, cache, main memory (main storage device), or the like. The memory 1002 can store executable programs (program code), software modules, etc. for performing information processing according to an embodiment of the present disclosure.

The storage 1003 is a computer-readable recording medium, for example, an optical disc such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disc, a magneto-optical disc (for example, a compact disc, a digital versatile disc, a Blu-ray disk), smart card, flash memory (eg, card, stick, key drive), floppy disk, magnetic strip, and/or the like. Storage 1003 may also be called an auxiliary storage device. The storage medium provided by the server 10 may be, for example, a database including at least one of the memory 1002 and the storage 1003, a server, or other suitable medium.

The communication device 1004 is hardware (transmitting/receiving device) for communicating between computers via at least one of a wired network and a wireless network, and is also called a network device, a network controller, a network card, a communication module, or the like.

The input device 1005 is an input device (for example, keyboard, mouse, microphone, switch, button, sensor, etc.) that receives input from the outside. The output device 1006 is an output device (eg, display, speaker, LED lamp, etc.) that outputs to the outside. Note that the input device 1005 and the output device 1006 may be integrated (for example, a touch panel).

Devices such as the processor 1001 and the memory 1002 are connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between devices.

The server 10 includes hardware such as a microprocessor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array). A part or all of each functional block may be implemented by the hardware. For example, processor 1001 may be implemented using at least one of these pieces of hardware.

The processing procedures, sequences, flowcharts, etc. of each aspect/embodiment described in this disclosure may be rearranged as long as there is no contradiction. For example, the methods described in this disclosure present elements of the various steps using a sample order, and are not limited to the specific order presented.

Input/output information and the like may be stored in a specific location (for example, memory), or may be managed using a management table. Input/output information and the like can be overwritten, updated, or appended. The output information and the like may be deleted. The entered information and the like may be transmitted to another device.

The determination may be made by a value represented by one bit (0 or 1), by a true/false value (Boolean: true or false), or by numerical comparison (for example, a predetermined value).

Each aspect/embodiment described in the present disclosure may be used alone, may be used in combination, or may be used by switching according to execution. In addition, the notification of predetermined information (for example, notification of “being X”) is not limited to being performed explicitly, but may be performed implicitly (for example, not notifying the predetermined information). good too.

Although the present disclosure has been described in detail above, it should be apparent to those skilled in the art that the present disclosure is not limited to the embodiments described in this disclosure. The present disclosure can be practiced with modifications and variations without departing from the spirit and scope of the present disclosure as defined by the claims. Accordingly, the description of the present disclosure is for illustrative purposes and is not meant to be limiting in any way.

Software, whether referred to as software, firmware, middleware, microcode, hardware description language or otherwise, includes instructions, instruction sets, code, code segments, program code, programs, subprograms, and software modules. , applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, and the like.

Software, instructions, information, etc. may also be sent and received over a transmission medium. For example, the software uses wired technology (coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), etc.) and/or wireless technology (infrared, microwave, etc.) to create websites, Wired and/or wireless technologies are included within the definition of transmission medium when sent from a server or other remote source.

As used in this disclosure, the terms "system" and "network" are used interchangeably.

In addition, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values from a predetermined value, or may be expressed using other corresponding information. may be represented.

Servers and/or clients may also be referred to as transmitters, receivers, communication devices, and/or the like. At least one of the server and the client may be a device mounted on a mobile object, the mobile object itself, or the like. The mobile object may be a vehicle (e.g., car, airplane, etc.), an unmanned mobile object (e.g., drone, self-driving car, etc.), or a robot (manned or unmanned ). At least one of the server and the client includes devices that do not necessarily move during communication operations. For example, at least one of the server and client may be an IoT (Internet of Things) device such as a sensor.

Also, the server in the present disclosure may be read as a client terminal. For example, a configuration in which communication between a server and a client terminal is replaced with communication between a plurality of user terminals (for example, D2D (Device-to-Device), V2X (Vehicle-to-Everything), etc.) Each aspect/embodiment of the present disclosure may be applied to. In this case, the client terminal may have the functions of the server described above.

Similarly, the client terminal in the present disclosure may be read as a server. In this case, the server may have the functions that the client terminal described above has.

As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Judgement", "determining" are, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (eg, lookup in a table, database, or other data structure), ascertaining as "judged" or "determined", and the like. Also, "judgment" and "determination" are used for receiving (e.g., receiving information), transmitting (e.g., transmitting information), input, output, access (accessing) (for example, accessing data in memory) may include deeming that a "judgement" or "decision" has been made. In addition, "judgment" and "decision" are considered to be "judgment" and "decision" by resolving, selecting, choosing, establishing, comparing, etc. can contain. In other words, "judgment" and "decision" may include considering that some action is "judgment" and "decision". Also, "judgment (decision)" may be read as "assuming", "expecting", "considering", or the like.

The terms "connected", "coupled", or any variation thereof, mean any direct or indirect connection or coupling between two or more elements, It can include the presence of one or more intermediate elements between two elements being "connected" or "coupled." Couplings or connections between elements may be physical, logical, or a combination thereof. For example, "connection" may be read as "access". As used in this disclosure, two elements are defined using at least one of one or more wires, cables, and printed electrical connections and, as some non-limiting and non-exhaustive examples, in the radio frequency domain. , electromagnetic energy having wavelengths in the microwave and optical (both visible and invisible) regions, and the like.

As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly specified otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

Any reference to elements using the "first," "second," etc. designations used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, reference to a first and second element does not imply that only two elements can be employed or that the first element must precede the second element in any way.

Where "include," "including," and variations thereof are used in this disclosure, these terms are inclusive, as is the term "comprising." is intended. Furthermore, the term "or" as used in this disclosure is not intended to be an exclusive OR.

In this disclosure, where articles have been added by translation, such as a, an, and the in English, the disclosure may include the plural nouns following these articles.

In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean that "A and B are different from C". Terms such as "separate," "coupled," etc. may also be interpreted in the same manner as "different."

DESCRIPTION OF SYMBOLS 10... Server, 11... Fluctuation information acquisition part, 12... Prediction part, 13... Judgment part, 20... Camera, 1001... Processor, 1002... Memory, 1003... Storage, 1004... Communication apparatus, 1005... Input device, 1006... Output Device, 1007...Bus.

Claims (4)

A structure determination system for determining the state of a structure,
a variation information acquisition unit that acquires variation information indicating relative variation between two parts of the structure for a combination of a plurality of parts;
a prediction unit that predicts relative fluctuations in combinations of predetermined portions based on relative fluctuations in combinations other than the predetermined portions indicated by fluctuation information acquired by the fluctuation information acquisition unit;
comparing the relative variation in the combination of the predetermined portions predicted by the prediction unit with the relative variation in the combination of the predetermined portions indicated by the variation information obtained by the variation information obtaining unit; a determination unit that determines the state of the structure;
A structure determination system with 2. The structure determination system according to claim 1, wherein the prediction unit predicts the relative variation of the combination between the predetermined parts by tensor decomposition of the tensor formed by the variation information. The prediction unit predicts relative variations in combinations between the predetermined portions for each of a plurality of timings, and a factor tensor obtained for any one of the plurality of timings in the prediction for each of the plurality of timings. 3. The structure determination system according to claim 2, wherein 4. The variation information acquiring unit acquires a moving image of the structure, calculates the relative variation based on the acquired moving image, and acquires the variation information. The structure judgment system according to the paragraph.

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