Analysis system, analysis method, and analysis program

Abstract

To provide an analysis system that can provide sufficient judgment material when situations with respect to the influence of weather are judged.SOLUTION: An analysis system according to an embodiment comprises: a data input device to which weather data related to at least weather in an evaluation target area and structure data on a structure located in the evaluation target area are input; and a diagnosis evaluation device communicably connected to the data input device. The diagnosis evaluation device includes: a storage unit that stores wind condition analysis data in the evaluation target area based on the weather data and structure analysis data of the structure based on the structure data; a control unit that calculates an index of influence on the structure to be received from the wind condition in the evaluation target area based on the wind condition analysis data and the structure analysis data, read from the storage unit; and a display unit that displays a calculation result of the index.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an analysis system, an analysis method, and an analysis program. [Background technology]

[0002] Systems for analyzing meteorological conditions such as wind conditions have been known. The meteorological analysis data calculated by these systems can be used in various situations affected by meteorology. For example, the meteorological analysis data can be used to determine the status of transportation such as railways and roads. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6326550 Summary of the Invention [Problem to be solved by the invention]

[0004] Structures such as railways and roads are installed in places that are affected by weather. Therefore, it is desirable to consider the impact of weather on structures when assessing the situation. However, conventional systems can only provide weather analysis data.

[0005] The problem to be solved by the present invention is to provide an analysis system, an analysis method, and an analysis program that can provide sufficient information for determining the situation regarding the influence of weather. [Means for solving the problem]

[0006] An analysis system according to one embodiment includes a data input device for inputting at least meteorological data relating to the weather in an area to be evaluated and structural data relating to structures located in the area to be evaluated, and a diagnostic evaluation device communicably connected to the data input device. The diagnostic evaluation device includes a memory unit that stores wind analysis data for the area to be evaluated based on the meteorological data and structural analysis data for the structures based on the structural data, a control unit that calculates an index of the impact of wind conditions in the area to be evaluated on the structures based on the wind analysis data and the structural analysis data read from the memory unit, and a display unit that displays the calculated index. [Effects of the Invention]

[0007] According to this embodiment, it is possible to provide sufficient information for judging the situation regarding the influence of weather. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a schematic configuration of an analysis system according to a first embodiment. [Figure 2] 4 is a flowchart showing the procedure of the analysis operation of the analysis system according to the first embodiment. [Figure 3] FIG. 3 is a diagram for explaining details of the analysis operation of the analysis system according to the first embodiment. [Figure 4] 10 is a graph showing an example of wind analysis data. [Figure 5] FIG. 4 is a diagram illustrating an example of an image displayed on a display unit. [Figure 6] FIG. 10 is a block diagram showing a schematic configuration of an analysis system according to a second embodiment. [Figure 7] FIG. 10 is a schematic diagram showing an example of a method for acquiring image data of a structure. [Figure 8] 10 is a flowchart showing the procedure of the analysis operation of the analysis system according to the second embodiment. [Figure 9] FIG. 10 is a diagram for explaining details of the analysis operation of the analysis system according to the second embodiment. [Figure 10]FIG. 10 is a block diagram showing the configuration of an image processing device according to a first modified example of the second embodiment. [Figure 11] 10 is a flowchart showing an example of an operation procedure of the image processing device according to the first modification. [Figure 12] FIG. 10 is a block diagram showing the configuration of a main part of an analysis system according to a second modification of the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. The present invention is not limited to the following embodiments.

[0010] (First embodiment) Fig. 1 is a block diagram showing a schematic configuration of an analysis system according to the first embodiment. The analysis system 1 shown in Fig. 1 includes a data input device 100 and a diagnostic evaluation device 200. The data input device 100 and the diagnostic evaluation device 200 are connected to each other via a communication network 300.

[0011] First, we will explain the configuration of the data input device 100. The data input device 100 has an online data input unit 110 and an offline data input unit 120. Weather data 111, wind condition measurement data 112, accident data 113, and operation data 114 are input to the online data input unit 110 from outside. Each piece of data will be explained below.

[0012] The weather data 111 includes, for example, at least one of Japan Meteorological Agency forecast data, weather forecast GPV (Grid Point Value) data, weather forecast SCW site (Super C Weather) data, meteorological reanalysis data such as ERA-5, and data on the results of WRF (Weather Research and Forecasting) analysis such as numerical weather models. Japan Meteorological Agency forecast data is data predicted by the Japan Meteorological Agency. Weather forecast GPV data is past and future weather forecast data calculated by a supercomputer at grid points preset on a map. ERA-5 data is data used for weather forecasting by the European Centre for Medium-Range Weather Forecasts. WRF is a forecast model for predicting wind conditions such as wind speed and direction.

[0013] The wind condition measurement data 112 includes at least one of Japan Meteorological Agency observation data, railway line wind condition measurement data, and local wind condition measurement data. Japan Meteorological Agency observation data is data obtained by measuring weather information such as wind conditions, temperature, humidity, and air pressure by the Japan Meteorological Agency. Railway line wind condition measurement data is data obtained by measuring wind conditions at multiple points along railway lines by railway companies. Local wind condition measurement data is data obtained by measuring wind conditions at points along railway lines where railway line wind condition measurement data is not obtained. Local wind condition measurement data is wind condition data measured, for example, by LiDAR (Light Detection and Ranging). LiDAR is a measuring instrument that emits laser light into the atmosphere, receives scattered light from the atmosphere, and observes wind speed and direction from the Doppler frequency.

[0014] The accident data 113 is data indicating details of accidents that have occurred along railway lines in the past, including, for example, the date, location, and circumstances of the accident.

[0015] The operation data 114 includes real-time location information of trains in operation, operation plans including planned cancellations, and the like.

[0016] On the other hand, for example, map data 121, structure data 122, train data 123, and railway line data 124 are input from the outside to the offline data input unit 120. Each piece of data will be explained below.

[0017] The map data 121 is data relating to the topography, such as a map of the area to be evaluated along the railway line and its surroundings, and the elevation.

[0018] The structure data 122 is data on structures existing along the railway line and in the surrounding area to be evaluated. This structure data 122 includes, for example, data on buildings and other structures that may affect wind conditions along the railway line, and data on the positions and load-bearing capacity of utility poles and trees that may affect train operation depending on wind conditions along the railway line. Load-bearing capacity can also be referred to as allowable stress.

[0019] The train data 123 is data indicating specifications such as the weight and overall length of the train, and data indicating the load capacity.

[0020] The railway line data 124 is data indicating the locations of railway tracks and stations.

[0021] Next, we will explain the configuration of the diagnostic evaluation device 200. The diagnostic evaluation device 200 has a communication unit 210, an operation unit 220, a display unit 230, a control unit 240, and a storage unit 250. Each unit of the diagnostic evaluation device 200 will be explained below.

[0022] The communication unit 210 functions as a communication interface when communicating with the data input device 100 via the communication network 300 .

[0023] The operation unit 220 receives operation inputs from the user and includes input devices such as a keyboard and a mouse.

[0024] The display unit 230 displays various images under the control of the control unit 240. The display unit 230 has a display device such as a liquid crystal display.

[0025] The control unit 240 has a data acquisition unit 241, a wind condition analysis unit 242, a structural analysis unit 243, an index calculation unit 244, and a wind condition identification unit 245. Each unit will be described below.

[0026] The data acquisition unit 241 acquires various data from the data input device 100 via the communication unit 210 .

[0027] The wind condition analysis unit 242 uses the data acquired by the data acquisition unit 241 to calculate wind conditions, such as wind speed and wind direction.

[0028] The structural analysis unit 243 calculates the wind loads that occur on structures located along the railway line using the wind analysis data from the wind condition analysis unit 242. The wind loads include moments and generated stresses.

[0029] The index calculation unit 244 calculates an index of the impact of wind conditions along the railway on structures in the area being evaluated by the wind condition analysis unit based on the wind condition analysis data and the structural analysis data. This index is, for example, the risk of electric poles and trees installed along the railway being destroyed by strong winds.

[0030] The wind condition identification unit 245 identifies the past, present, and future wind conditions along the railway line.

[0031] The storage unit 250 has an accident database 251, an asset database 252, a wind condition analysis database 253, and a structural analysis database 254. Each database will be described below.

[0032] The accident database 251 is a database showing details of accidents that have occurred along railway lines in the past. In the accident database 251, the date and time of an accident, the location, the weather forecast data at the time of the accident, and the wind condition measurement data are associated with each other based on the weather data 111, the wind condition measurement data 112, and the accident data 113 acquired from the data input device 100.

[0033] The asset database 252 is a database that indicates details related to structures and trains, and includes the train data 123 acquired from the data input device 100.

[0034] The wind condition analysis database 253 is a database showing the results of a prior analysis of wind conditions along railway lines. The wind condition analysis database 253 includes wind condition analysis data calculated by the wind condition analysis unit 242.

[0035] The structural analysis database 254 is a database showing the results of a preliminary analysis of structures existing along the railway line. The structural analysis database 254 includes structural analysis data calculated by the structural analysis unit 243.

[0036] The analysis operation of the above-mentioned analysis system 1 will be described below with reference to Fig. 2 and Fig. 3. Fig. 2 is a flowchart showing the procedure of the analysis operation of the analysis system 1 according to this embodiment. Fig. 3 is a diagram for explaining the details of the analysis operation of the analysis system 1 according to this embodiment.

[0037] As shown in FIG. 2, first, data required for the analysis operation is input from an external organization to the data input device 100 (step S1). The input data is classified into an online data input unit 110 and an offline data input unit 120 according to its characteristics. Online data whose data values change over time, i.e., weather data 111, wind condition measurement data 112, accident data 113, and operation data 114, are input to the online data input unit 110. On the other hand, offline data whose data values are constant, i.e., map data 121, structure data 122, train data 123, and lineside data 124, are input to the offline data input unit 120. Note that the accident data 113 may also be input to the offline data input unit 120.

[0038] Next, the wind condition analysis unit 242 of the diagnostic evaluation device 200 analyzes the wind conditions along the railway line (step S2). Here, the operation of step S2 will be described in detail with reference to FIG.

[0039] 3, first, the wind condition analysis unit 242 creates a wide-area analysis model (step S21) using the map data 121. The wide-area analysis model shows a topographical model of mountainous areas and flatlands in a wide area including along railway lines.

[0040] Next, the wind condition analysis unit 242 inputs the meteorological data 111 into a wide-area analysis model to perform wind condition analysis for the wide area (step S22). In step S22, for example, ERA5 data is input as the meteorological data 111. Meteorological data not only for the evaluation target area itself but also for outside the evaluation target area is input.

[0041] Next, the wind condition analysis unit 242 creates a local analysis model using the map data 121 and the structure data 122 (step S23). In step S23, the wide area is divided into multiple local areas, and the local analysis model includes a terrain model of each local area plus data on buildings, etc. Railroad lines exist within one local area or multiple local areas.

[0042] Next, the wind condition analysis unit 242 inputs the results of the wide-area wind condition analysis performed in step S22 into the local analysis model to perform wind condition analysis for each local area (step S24). Wind condition analysis data indicating the analysis results for each local area is stored in the wind condition analysis database 253.

[0043] Next, the wind condition analysis unit 242 calculates a conversion factor for converting the wind condition analysis value into a measured wind condition value or a predicted wind condition value (step S25). The conversion factor is also stored in the wind condition analysis database 253. The conversion factor can be calculated, for example, by calculating the difference, normalization, sum of squares of the difference, or inner product between the measured value of the wind condition data 112 measured at a certain location and the analytical value of the wind condition analysis data at the same location. The conversion factor can also be used to calculate measured values for locations where wind conditions have not been measured. The wind condition analysis unit 242 may calculate conversion factors at multiple locations. In this case, when calculating the measured value at a certain location, the conversion factor corresponding to the location closest to the location can be used to calculate the measured value with high accuracy. Alternatively, the measured value at a certain location may be calculated based on the conversion factors of multiple measured locations.

[0044] FIG. 4 is a graph showing an example of wind condition analysis data. In FIG. 4, the horizontal axis represents wind speed at a certain point, and the vertical axis represents altitude at that point. In the graph shown in FIG. 4, under normal circumstances, as the altitude increases, the wind speed increases rapidly in the positive direction. In contrast, under emergency circumstances, the wind speed first increases in the negative direction until the altitude reaches a certain value, and then increases in the positive direction. In this way, the manner in which the wind condition analysis data changes differs between under normal circumstances and during an emergency. Therefore, wind condition analysis data under normal circumstances and wind condition analysis data under emergency circumstances may be stored in separate wind condition analysis databases 253. In this case, the wind condition analysis data can be classified and managed according to the wind conditions.

[0045] In this embodiment, in order to create highly accurate wind analysis data, wind analysis is performed by narrowing the area stepwise from wide to local, which is called nesting. However, if data accuracy can be ensured, wind analysis data along railway lines may be created using local wind analysis. In this case, wide-area wind analysis is not necessary, and the time required for wind analysis can be shortened.

[0046] When the above-described wind condition analysis is completed, the structural analysis unit 243 performs a structural analysis of structures existing along the railway line (step S3), as shown in Fig. 2. Here, the operation of step S3 will be described in detail with reference to Fig. 3.

[0047] 3, first, the structural analysis unit 243 creates a structural analysis model using the structure data 122 (step S31). In the structural analysis model, objects to be analyzed, such as utility poles and trees, are positioned based on multiple structural position data.

[0048] Next, the structural analysis unit 243 inputs the wind analysis data stored in the wind analysis database 253 into a structural analysis model to perform a structural analysis of each structure (step S32). The structural analysis data indicating the results of the structural analysis is stored in the structural analysis database 254. The structural analysis unit 243 calculates, as structural analysis data, the wind load that will be generated on the structure when, for example, a wind speed indicated in the wind analysis data occurs. In this embodiment, the structural analysis is performed based on the structure position data, but it is also possible to perform structural analysis on individual analysis targets that do not include position data, and store the results in the structural analysis database 254. In this case, for example, it is possible to create a risk map of trees in a specific area.

[0049] Note that a train is more susceptible to the influence of wind when traveling on an inclined track than when traveling on a flat track. Therefore, in step S3, the structural analysis unit 243 may calculate the load generated on the train. In this case, the structural analysis unit 243 first creates a structural analysis model using the train data 123 and the wayside data 124. Next, the structural analysis unit 243 uses this structural analysis model to calculate the wind load generated on the train as structural analysis data. This structural analysis data is also stored in the structural analysis database 254.

[0050] Furthermore, when strong winds occur, structures may vibrate. In this case, dynamic vibration loads are generated on the structure. Therefore, structural analysis data may be stored in separate structural analysis databases 254 according to the type of load. For example, by storing structural analysis data for structures that experience static wind loads and structural analysis data for structures that experience dynamic vibration loads in separate structural analysis databases 254, the loads can be categorized and managed.

[0051] In this embodiment, as described above, wind condition analysis is performed, and wind condition analysis data such as wind speed along the railway line is stored in advance in the wind condition analysis database 253. Furthermore, a structural analysis is performed based on the results of this wind condition analysis, and structural analysis data such as loads that occur when strong winds act on structures and trains existing along the railway line is stored in advance in the structural analysis database 254.

[0052] Once the wind condition analysis data and structural analysis data have been compiled into a database, the wind condition identification unit 245 identifies the past, present, and future wind conditions along the railway line (step S4), as shown in Fig. 2. The operation of step S4 will now be described in detail with reference to Fig. 3.

[0053] 3, in step S4, the wind condition identification unit 245 identifies past, present, and future wind conditions at each point along the railway line using the meteorological data 111, the wind condition measurement data 112, and data read from the wind condition analysis database 253. When identifying past or present wind conditions, for a point for which past or present wind condition measurement data 112 exists, the wind condition identification unit 245 identifies the wind conditions using, for example, the wind condition measurement data 112. For a point for which past or present wind condition measurement data 112 does not exist, the wind condition identification unit 245 identifies the wind conditions using, for example, the meteorological data 111 for the vicinity of that point and data read from the wind condition analysis database 253 (wind condition analysis data and conversion coefficients). In addition, when identifying future wind conditions, the wind condition identification unit 245 identifies the wind conditions using weather data 111 including weather forecast data such as weather forecast GPV data and data read from the wind condition analysis database 253 (wind condition analysis data and conversion coefficients).

[0054] When the operation of step S4 is completed, the index calculation unit 244 calculates an index indicating the degree of risk of the structure (step S5), as shown in Fig. 2. Here, the operation of step S5 will be described in detail with reference to Fig. 3.

[0055] In step S5, as shown in FIG. 3, the index calculation unit 244 reads out the wind load (including moments, generated stresses, etc.) indicated in the structural analysis data of each structure stored in the structural analysis database 254. Alternatively, the index calculation unit 244 also reads out the withstand load (allowable stress, etc.) indicated in the withstand load data of each structure stored in the asset database 252. Next, the index calculation unit 244 compares the wind load and withstand load for each structure. Next, the index calculation unit 244 calculates the risk of structure collapse based on the comparison result. The index calculation unit 244 also compares the wind load of the train read out from the structural analysis database 254 with the withstand load of the train read out from the asset database 252, and calculates the risk of train operation based on the comparison result. The risk levels of the structure and the train are preset, for example, depending on the withstand load and the difference between the wind load and the withstand load. The calculation results of the above-mentioned indexes are sent to the display unit 230. This completes the operation of step S5.

[0056] Next, the display unit 230 displays the image (step S6). Here, the operation of step S6 will be described in detail with reference to FIG.

[0057] Fig. 5 is a diagram showing an example of an image displayed on the display unit 230. As shown in Fig. 5, the display unit 230 displays a dashboard in which images 401 to 404 are displayed in a list.

[0058] Image 401 is composed of image 411 showing the wind speed distribution over a wide area, image 412 which is an enlarged version of a portion of image 411, and image 413 showing the standard deviation distribution of wind speeds over the wide area. Display unit 230 acquires, for example, measured data for the wide area included in wind condition measured data 112 from data input device 100 via wind condition identification unit 245, and creates and displays images 411 to 413. These images display past, present, and future wind conditions, so image 401 can be used, for example, as a hazard map.

[0059] Image 402 is composed of image 421 showing a terrain model of a specific point specified by a user's input to operation unit 220, and graph image 422 showing time-series changes in wind conditions at the specific point. In graph image 422, the horizontal axis represents time, and the vertical axis represents the wind speed and wind direction identified by wind condition identification unit 245 over time. Graph image 422 shows time-series changes in wind speed and wind direction at the specific point. Therefore, image 402 can be used for detailed analysis of wind conditions, such as the occurrence of turbulence, at the specific point.

[0060] Image 403 shows the time transition of past, present, and future wind speeds identified by the wind condition identification unit 245 on a line having stations A to E. Image 403 shows how wind speeds at each station and between stations change over time. Therefore, image 403 can be used as a basis for deciding whether to resume service on a line after it has been suspended. Image 403 also displays the time transition of index levels, which will be described later. Image 403 may also map areas that may become risky before or after the fact, as well as areas on the tracks where there is a high risk of flying objects causing disruption to service.

[0061] Image 404 is composed of image 441 showing the calculation results of index calculation unit 244 and table image 442 explaining the levels of the index. Image 441 displays multiple utility poles 500 on a map along the railway line based on location data acquired from asset database 252 via index calculation unit 244. Indicators for each utility pole 500 are also displayed as a mapping. Image 441 also displays the risk A of collapse of each utility pole 500 as an index, mapped in association with its level. Risk A can be calculated, for example, by dividing the generated stress (in other words, wind load) of utility pole 500 by the allowable stress (in other words, withstand load), as shown in table image 442. Image 404 displays the risk of strength against wind load. Therefore, image 404 can be used when formulating operation plans and inspection plans after strong winds have passed along the railway line. Although image 404 displays the degree of risk of collapse of utility pole 500, the object may be another structure such as a tree. Alternatively, it may be a mapping of position data of debris along the railway line, such as a vinyl greenhouse, which is heavy enough that it will not be necessary to calculate the structural analysis (step S3) performed by structural analysis unit 243. Image 404 may also map locations that pose a risk before or after the fact, or locations on the railway line where there is a high risk that a flying object could cause an obstruction to train operations.

[0062] The display unit 230 may map and display cumulative values of wind speed, standard deviation, risk level, etc. for a preset period (for example, within the past six hours) on the image 441. The display unit 230 may also display an alarm R on the image 441, as shown in FIG. 5. The alarm R is displayed, for example, in an area where the risk level is higher than a preset threshold and where an accident has occurred in the past in the accident database 251. The alarm R can be displayed in a color different from the risk level (for example, red) or illuminated, but the display manner is not particularly limited. By displaying the alarm R on the image 441, it is possible to alert the user.

[0063] The operations of steps S1 to S5 described above can also be realized by having a computer execute a program that processes each step. This program can also be recorded on a recording medium as software.

[0064] In the present embodiment described above, the wind condition analysis unit 242 predicts strong winds in the event of an abnormality. Furthermore, the structure analysis unit 243 analyzes the impact of the strong winds on the structure. Furthermore, the display unit 230 displays an index of the impact (risk level) calculated by the index calculation unit 244. This makes it possible to provide sufficient information for decision-making when, for example, a railway operator considers resuming operations.

[0065] In this embodiment, the area to be evaluated is along a railway line. However, the area to be evaluated is not limited to along a railway line, and may be a road such as an expressway. In this case, the wind condition analysis unit 242 analyzes the wind conditions on the road. Furthermore, the structure analysis unit 243 analyzes the impact of the wind conditions on structures (e.g., lighting poles) around the road. Furthermore, the display unit 230 displays an index of the impact (risk level) calculated by the index calculation unit 244. This provides sufficient information for making a decision when lifting the road closure.

[0066] (Second embodiment) 6 is a block diagram showing a schematic configuration of an analysis system according to the second embodiment. Components similar to those in the first embodiment described above are given the same reference numerals, and detailed description thereof will be omitted.

[0067] 6, in the analysis system 2 according to this embodiment, structure data 115 is input from the image processing device 600 to the online data input unit 110 of the data input device 100. Similar to the structure data 122 described in the first embodiment, the structure data 115 is data relating to structures existing in the area to be evaluated along the railway line and its surrounding areas. This structure data 115 includes, for example, data on buildings and other structures that may affect wind conditions along the railway line, as well as data on the position, shape, and load-bearing capacity of utility poles and trees that may affect train operation depending on the wind conditions along the railway line.

[0068] The image processing device 600 includes an image storage unit 601 and an image analysis unit 602. Note that the image storage unit 601 and the image analysis unit 602 do not necessarily have to belong to the analysis system 2, and may be configured independent of the analysis system 2. In this case, the structure data 115 is provided to the data input device 100 from outside the analysis system 2.

[0069] Image data of various structures in the area to be evaluated is stored in the image storage unit 601. The image data is stored in a database in association with, for example, the time of photographing.

[0070] The image analysis unit 602 analyzes the image data stored in the image storage unit 601. The analysis results of the image analysis unit 602 are input as structure data 115 to the online data input unit 110. The image analysis unit 602 constantly performs analysis processing, so that the structure data 115 is successively updated to the latest data.

[0071] Fig. 7 is a schematic diagram showing an example of a method for acquiring image data of a structure. In the acquisition method shown in Fig. 7, a photographing device 12, which is composed of, for example, a camera, is installed on a railway vehicle 11. The photographing device 12 photographs structures 13, such as trees, that exist along the railway line while the railway vehicle 11 is in operation. The image data captured by the photographing device 12 is transmitted to an image processing device 600 via a wired or wireless connection and stored in an image storage unit 601.

[0072] The photographing device 12 is not limited to photographing the structure 13 from the railroad vehicle 11, but may also photograph from a vehicle traveling in the area to be evaluated. Alternatively, a person carrying the photographing device 12 may photograph the structure 13 while walking.

[0073] Furthermore, the image data of the structure 13 is not limited to data photographed by the above-described photographing device 12, but may be, for example, data photographed by a fixed camera (such as a surveillance camera) installed in the area to be evaluated. Alternatively, it may be image data from a satellite photographing the area to be evaluated. In addition, various image data provided by external organizations may be used.

[0074] The analysis operation of the above-mentioned analysis system 2 will be described below with reference to Fig. 8 and Fig. 9. Fig. 8 is a flowchart showing the procedure of the analysis operation of the analysis system 2 according to this embodiment. Fig. 9 is a diagram for explaining the details of the analysis operation of the analysis system 2 according to this embodiment.

[0075] 8, first, the image processing device 600 acquires image data from the photographing device 12 and stores it in the image storage unit 601, and then the image analysis unit 602 analyzes the image data stored in the image storage unit 601 to create the structure data 115 (step S0). An example of the operation content of step S0 will be described below.

[0076] The image analysis unit 602 first estimates the position of the structure 13 from the image data stored in the image storage unit 601. If the image capture device 12 is installed on a moving object such as a railway vehicle 11, the image analysis unit 602 estimates the position of the structure 13 using, for example, operation information indicating the vehicle position at the time of capture. Next, the image analysis unit 602 extracts shape data and color data of the structure 13 from the captured image data. Next, the image analysis unit 602 identifies and classifies the type of the structure 13 or identifies the state of the structure 13 based on the extracted shape data and color data. For example, using AI (Artificial Intelligence) or the like to identify the structure 13 allows for more accurate recognition.

[0077] In this embodiment, the process of saving image data in the image storage unit 601, the image analysis process in the image analysis unit 602, and the subsequent input process to the online data input unit 110 are all performed automatically, but these processes are not necessarily limited to being performed automatically. For example, one of these processes may be performed manually, or part of the image analysis process may be performed manually.

[0078] The results of identifying and classifying the structures 13 by the image analysis unit 602 as described above are input as structure data 115 to the online data input unit 110 together with online data such as weather data 111 (step S1). Every time structure data 115 is input, the structure data 115 stored in the online data input unit 110 is updated to the latest data.

[0079] The operation contents from step S2 onwards are the same as those in the first embodiment as shown in Fig. 9, and therefore detailed description will be omitted. In this embodiment, the structure data 115 is used in the wind condition analysis (step S2) and the structure analysis (step S3).

[0080] The actual state of structures within the evaluation area may change over time. For example, various cases are possible, such as the construction, removal, or reconstruction of buildings, as well as changes in shape due to tree growth. In contrast, in the above-described present embodiment, the image processing device 600 updates information about structures as needed. This makes it possible to perform wind analysis and structural analysis with higher accuracy than in the first embodiment.

[0081] In this embodiment, the analysis results of the image processing device 600 are not necessarily limited to being used to update the structure data 115, but can also be used, for example, when creating data for structures for which no existing data exists within the area to be evaluated.

[0082] (Variation 1) 10 is a block diagram showing the configuration of an image processing device 600 according to Modification 1 of the second embodiment. The same components as those in the second embodiment described above are given the same reference numerals, and detailed description thereof will be omitted.

[0083] 10, an image processing device 600 according to this modification further includes an alert unit 603 in addition to an image storage unit 601 and an image analysis unit 602. The alert unit 603 issues a predetermined alarm in accordance with the analysis result of the image analysis unit 602.

[0084] 11 is a flowchart showing an example of the operation procedure of the image processing device 600 according to this modification. The following operation is executed in the structure data processing step (step S0) described in the second embodiment.

[0085] First, the image storage unit 601 stores image data of the structure 13 photographed by the photographing device 12 (step S101). Next, the image analysis unit 602 analyzes the image data stored in the image storage unit 601 (step S102).

[0086] In step S102, when the image analysis unit 602 analyzes the image data using, for example, AI to identify the type of structure, the structure may not always be correctly recognized. In this case, if an incorrect analysis result is input to the online data input unit 110 as structure data 115, it may interfere with the risk assessment that is subsequently performed.

[0087] Therefore, in this modified example, the image analysis unit 602 calculates an index relating to the reliability of the analysis results, such as a matching rate indicating the proportion of data that meets specified matching conditions among the entire data, and determines whether the index is equal to or greater than a predetermined threshold value (step S103).

[0088] If the index is below the threshold value, the warning unit 603 issues an alert (step S104). In step S104, the form of the alert is not particularly limited. For example, the warning unit 603 issues a warning sound or displays a warning image. When the warning unit 603 issues an alert, the user may take action such as directly checking the identification result. On the other hand, if the index is equal to or greater than the threshold value, the analysis result of the image analysis unit 602 is input to the online data input unit 110 as structure data 115 (step S105).

[0089] In step S102, if an unexpected new structure appears in the image data, it is difficult to automatically identify the structure using AI or the like. In this way, when automatic type identification is difficult, the image analysis unit 602 may automatically classify the structure into another structure having a shape most similar to that of the object of analysis. In this case, when the reliability index falls below a threshold, the warning unit 603 issues an alert. Furthermore, when it is difficult to automatically classify a structure, the user may manually register the structure.

[0090] According to the present modified example described above, highly reliable analysis results are input to the online data input unit 110 as structure data 115. This further improves the accuracy of wind analysis and structure analysis.

[0091] In this modification, the warning unit 603 may have a function of issuing an alert based on the reliability of the analysis results of the image analysis unit 602, as well as a function of issuing an alert when a potentially dangerous obstacle is recognized from the analysis results of the image analysis unit 602. Examples of situations that pose a danger to railway operation include tree branches approaching the tracks or obstacles blown in by the wind near the tracks. For example, when comparing the latest image data with past image data, the image analysis unit 602 recognizes that an obstacle such as a tree branch or a flying object exists in the specific area when the image of a specific area, such as a track, within the evaluation area is different. When the image analysis unit 602 recognizes an obstacle in this way, the warning unit 603 issues an alert. The method of recognizing an obstacle from image data is not limited to the method of comparing two pieces of image data as described above, and other methods may be used.

[0092] (Variation 2) 10 is a block diagram showing the configuration of the main parts of an analysis system according to Modification 2 of Embodiment 2. The same components as those in the analysis system 2 according to the second embodiment described above are given the same reference numerals, and detailed description thereof will be omitted.

[0093] In this modification, in addition to the analysis results of the image analysis unit 602, inspection record data is input as structure data 115 to the online data input unit 110 of the data input device 100. The inspection record data is a database of the results of periodic inspections along the railway line by railway workers or irregular inspections carried out after abnormal weather such as typhoons. This inspection record data includes inspection records including the location, type, and condition of structures such as trees that could become obstacles near the railway line, as well as irregular inspection reports.

[0094] For example, if the inspection record data indicates an inspection record of a structure installed in a location that cannot be photographed by the photographing device 12, this inspection record data is reflected in the structure data 115 as supplementary data.

[0095] According to the present modified example described above, the inspection record data is reflected in the structure data 115, thereby enriching the content of the structure data 115 input to the online data input unit 110. This further improves the accuracy of wind analysis and structure analysis.

[0096] In this modification, the inspection record data is input to the data input device 100, but may also be input to the image analysis unit 602 of the image processing device 600. In this case, the image analysis unit 602 compares the analysis results of the image data read from the image storage unit 601 with the inspection record data. For example, the image analysis unit 602 compares the shape and color of the structure shown in the image data with the shape and color of the structure recorded in the inspection record data, and uses the degree of match between the two data as an index of the reliability of the analysis results described in Modification 1. If the degree of data match falls below a threshold, the warning unit 603 issues an alert, as in Modification 1. The inspection record data can also be used as training data when the image analysis unit 602 analyzes image data using AI.

[0097] Although several embodiments have been described above, these embodiments are presented only as examples and are not intended to limit the scope of the invention. The novel system described in this specification can be embodied in various other forms. Furthermore, various omissions, substitutions, and modifications can be made to the forms of the system described in this specification without departing from the spirit of the invention. The appended claims and their equivalents are intended to cover such forms and modifications that fall within the scope and spirit of the invention. [Explanation of symbols]

[0098] 100: Data input device 200: Diagnostic evaluation device 230: Display section 240: Control unit 242: Wind condition analysis department 243: Structural Analysis Department 244: Indicator calculation section 245: Wind condition identification unit 250: Storage section 601: Image storage unit 602: Image Analysis Department 603: Warning section

Claims

1. a data input device into which at least meteorological data relating to the weather in the area to be evaluated and structure data relating to structures located in the area to be evaluated are input; a diagnostic evaluation device communicatively connected to the data input device; the diagnostic evaluation device, a storage unit that stores wind analysis data obtained by analyzing the relationship between altitude and wind speed for each point in the evaluation area based on the meteorological data, and structural analysis data of the structure based on the structure data; a control unit that calculates an index of the influence that the structure receives from the wind conditions in the evaluation area based on the wind condition analysis data and the structural analysis data read from the storage unit; and a display unit that displays the calculation results of the index, The data input device also acquires actual measurement data of the wind conditions in the evaluation area or wind condition forecast data that predicts the wind conditions, the control unit has a wind condition analysis unit that calculates the wind condition analysis data and stores the data in the storage unit, The wind condition analysis unit uses the actual measurement data or the wind condition forecast data and a wind condition analysis value based on the wind condition analysis data for the same location as the actual measurement data or the wind condition forecast data to calculate a conversion coefficient for converting the wind condition analysis value into an actual measurement wind condition value or a wind condition forecast value.

2. The control unit a structural analysis unit that calculates the structural analysis data and stores the calculated data in the storage unit; The analysis system according to claim 1 , further comprising an index calculation unit that calculates the index.

3. The control unit further includes a wind condition identification unit that identifies past, present, or future wind conditions in the evaluation area using the wind condition analysis data and the actual measurement data or the wind condition prediction data; The wind condition identification unit, for a point where past or present actual measurement data or wind condition forecast data exists, identifies past or present wind conditions at the point using the actual measurement data or the wind condition forecast data of this point, and 3. The analysis system of claim 2, wherein, for a point for which no past or present measured data or no wind condition forecast data exists, the wind condition identification unit identifies the past or present wind conditions at the non-existent point using the meteorological data in the vicinity of the non-existent point and the conversion coefficient and the wind condition analysis data of the point closest to the non-existent point.

4. 4. The analysis system according to claim 2, wherein the structural analysis unit calculates, as the structural analysis data, a load generated on the structure due to the wind conditions indicated in the wind condition analysis data.

5. The analysis system according to claim 4 , wherein the index calculation unit calculates, as the index, a result of comparison between the wind load calculated as the structural analysis data and the withstand load of the structure included in the structure data.

6. The analysis system according to claim 5 , wherein the index calculation unit calculates the index based on a comparison result between the wind load and the withstand load for a plurality of structures.

7. The analysis system according to claim 6 , wherein the display unit displays the calculation results of the index for each of the plurality of structures.

8. The analysis system according to claim 3 , wherein the wind condition identification unit identifies the wind conditions using a conversion coefficient for converting the wind condition analysis data into the actual measurement data or the wind condition prediction data.

9. The analysis system according to claim 7 , wherein the display unit displays the plurality of structures on a map of the area to be evaluated, and maps an index of each structure on the map.

10. The storage unit also stores accident data relating to accidents that have occurred in the evaluation area in the past, The analysis system according to claim 8 , wherein the display unit displays an alarm for an area identified based on the level of the index and the accident data.

11. The analysis system according to claim 1 , wherein the area to be evaluated is a railway line or a road.

12. an image storage unit for storing image data of the structure; an image analysis unit that analyzes the image data stored in the image storage unit, The analysis system according to claim 1 , wherein the analysis results of the image analysis unit are input as the structure data to the data input device.

13. The analysis system according to claim 12 , wherein the image analysis unit extracts and classifies the structures from the image data.

14. The analysis system according to claim 12 or 13, further comprising a warning unit that issues an alert depending on the reliability of the analysis result of the image analysis unit.

15. The analysis system according to claim 14 , wherein the warning unit issues the alert even when an obstacle is recognized from the analysis result of the image analysis unit.

16. The analysis system according to claim 12, wherein inspection record data indicating inspection results of the structure is input to the data input device as the structure data.

17. Obtaining meteorological data relating to the weather in the area to be evaluated, structure data relating to structures located in the area to be evaluated, and actual measurement data of wind conditions in the area to be evaluated or wind condition forecast data predicting wind conditions; calculating wind analysis data that analyzes the relationship between altitude and wind speed for each point in the evaluation area based on the meteorological data, and structural analysis data of the structure based on the structure data; calculating a conversion coefficient for converting the wind condition analysis value into the actual wind condition value or the predicted wind condition value using the actual measurement data or the predicted wind condition data and a wind condition analysis value based on the wind condition analysis data for the same location as the actual measurement data or the predicted wind condition data; The wind analysis data and the structural analysis data are stored in a storage unit; calculating an index of the influence of the wind conditions in the evaluation area on the structure based on the wind condition analysis data and the structural analysis data read from the storage unit; and displaying the calculation results of the index.

18. Obtaining at least meteorological data relating to the weather in the area to be evaluated, structure data relating to structures located in the area to be evaluated, and actual measurement data of wind conditions in the area to be evaluated or wind condition forecast data that predicts wind conditions; calculating wind analysis data that analyzes the relationship between altitude and wind speed for each point in the evaluation area based on the meteorological data, and structural analysis data of the structure based on the structure data; calculating a conversion coefficient for converting the wind condition analysis value into the actual wind condition value or the predicted wind condition value using the actual measurement data or the predicted wind condition data and a wind condition analysis value based on the wind condition analysis data for the same location as the actual measurement data or the predicted wind condition data; The wind analysis data and the structural analysis data are stored in a storage unit; calculating an index of the influence of the wind conditions in the evaluation area on the structure based on the wind condition analysis data and the structural analysis data read from the storage unit; A program for causing a computer to execute a process for displaying the calculation results of the index.

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