JP2018036076A - Facility management device and method for facility management - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a facility management device and a method for facility management which can correctly evaluate degradation of a facility measured multiple times by multiple methods.SOLUTION: The facility management device includes: an acquisition part; a position specification part; an index generation part; and an index conversion part. The data acquisition part acquires measurement data measured by a measuring device for measuring the state of a facility. The position specification part specifies the position of a facility for which measurement data was measured, based on the acquired measurement data. The index generation part generates an index showing the degradation of the facility based on the acquired measurement data. The index conversion part applies a weighting for the measurement device to the generated index.SELECTED DRAWING: Figure 1

Description

  Embodiments described herein relate generally to a facility management apparatus and a facility management method.

  For maintenance of infrastructure facilities such as roads, it is necessary to inspect the state of deterioration and damage of the facilities and perform continuous repairs or updates, etc. to maintain the soundness of the facilities. Inspecting infrastructure facilities, the inspector inspects the appearance of the facility, etc., and internal deterioration visually or by sound, and uses various measuring devices to quantify the external or internal state of the facility There is.

  The evaluation of the inspection result may be performed based on a predetermined index. For example, inspection of road pavement status is managed by an index called MCI (Maintenance Control Index). MCI is composed of three indicators of the road pavement deterioration status: “cracking rate”, “wadder amount” and “flatness”. In order to measure these indicators, various methods have been proposed according to the indicators. For example, a method using an MMS (Mobile Mapping System), a method using a TV camera, or a three-dimensional laser measuring instrument is used to measure “cracking ratio”, “wad digging amount” and “flatness”. A method, a method using a vibrometer, a method using a captured image of a drive recorder, and the like have been proposed.

  However, there are cases where the measurement method of each index is different in measurement object, measurement accuracy, measurement cost, and the like. For example, MCI measurement by MMS is a measurement method using an expensive apparatus that accurately measures three-dimensional data using an on-vehicle digital camera and a three-dimensional laser measuring instrument. In addition, MCI measurement using a TV camera analyzes an image taken with a TV camera, and can measure the cracking rate with high accuracy. However, the cost of the apparatus is high because of advanced image processing. Become. In addition, the measurement accuracy of MCI measurement using a captured image of a drive recorder is low because the resolution of the image is low, but the cost of data measurement can be reduced by diverting images captured by many vehicles. .

  Therefore, the evaluation of the index may be performed by combining a plurality of measurement methods. For example, when the total length of the road to be evaluated for pavement is long, the measurement section using a high-precision measurement method using an expensive measuring instrument is limited to the main road, or the measurement frequency is limited to once a year. In addition, the measurement cost may be reduced by measuring the remaining measurement sections with a low-cost measurement method, or by further reducing the measurement frequency for routes with fewer users.

JP 2010-283517 A International Publication No. 2005/83756

  However, when an indicator that indicates deterioration of a facility is measured by a plurality of measurement methods, the position information of the measured facility may be shifted depending on the measurement method or the measurement time, and determination of deterioration at a specific measurement position may occur. There was a case that could not be correctly.

  In addition, since indexes measured by a plurality of methods having different measurement accuracy have different reliability with respect to measurement results, there are cases where it is difficult to uniformly handle the determination of deterioration.

  The problem to be solved by the present invention is to provide a facility management apparatus and a facility management method capable of correctly evaluating deterioration of facilities measured by a plurality of measurement methods.

  The facility management apparatus according to the embodiment includes a data acquisition unit, a position specifying unit, an index generation unit, and an index conversion unit. The data acquisition unit acquires measurement data measured by a measurement device that measures the state of the facility. The position specifying unit specifies the position of the facility where the measurement data is measured based on the acquired measurement data. The index generation unit generates an index indicating the deterioration of the facility based on the acquired measurement data. The index conversion unit applies a weight corresponding to the measurement device to the generated index.

The figure which shows an example of the outline | summary of the facility management apparatus of embodiment. The block diagram which shows an example of a structure of the facility management apparatus of embodiment. The flowchart which shows an example of the facility management process of embodiment. The figure which shows an example of the feature-value used for the specific process of the measurement position of the facility management apparatus of embodiment. The figure which shows an example of the weighting with respect to the parameter | index measured with the facility management apparatus of embodiment.

  Hereinafter, a facility management apparatus and a facility management method according to an embodiment will be described with reference to the drawings. In the present embodiment, the facility management apparatus and the facility management method exemplify a case where the pavement state of the road is managed.

First, an outline of the facility management apparatus will be described.
Drawing 1 is a figure showing an example of the outline of the facility management device of an embodiment.

  In FIG. 1, the facility management apparatus 1 includes functions of a data acquisition unit 11, a position specification unit 12, an index generation unit 13, an index conversion unit 14, an analysis unit 15, a storage unit 16, a setting unit 17, and a data output unit 18. Have. Input data is input to the facility management apparatus 1. Further, output data is output from the facility management apparatus 1.

  The input data is, for example, device data, date data, GPS data, image data, unevenness data, point cloud data, audio data, or the like. Device data is information for identifying a measuring device such as model information and performance information of a measuring device (not shown). Date data is information such as measurement date and time. The GPS data is position data of longitude and latitude of a GPS receiver (not shown) acquired based on radio waves transmitted from a GPS (Global Positioning System) satellite. The position data includes time information in addition to longitude and latitude. The position data may include information such as altitude and speed. The position data may be corrected using speed information and acceleration information of a vehicle equipped with a GPS receiver in a mountainous area or tunnel where radio waves from GPS satellites are difficult to reach. The image data is data of an image taken with a television camera or the like. The image data may be obtained by performing image processing or the like on a captured image. The unevenness data is data indicating the unevenness of the road surface. The unevenness data is, for example, pavement shape data measured by a three-dimensional laser measuring instrument (not shown), vibration data measured by a vibrometer, and the like. The point cloud data is data representing a structure around a road or the shape of a pavement measured by a three-dimensional laser measuring instrument as three-dimensional point cloud data. The sound data is data such as environmental sounds around the road collected by a sound collecting microphone (not shown). The voice data includes data such as environmental sounds collected only in a specific area such as a railroad crossing alarm.

  The output data is, for example, MCI (cracking rate, rutting amount, flatness) or three-dimensional data. The crack rate, rutting amount, flatness, and MCI calculated based on these are based on a predetermined test method (pavement survey and test method manual (Japan Road Association)). For example, the crack rate is an index indicating pavement deterioration calculated based on how many cracks exist in a predetermined area of road pavement. The rutting amount is an index obtained by measuring the depth of the concave portion of the paved road surface in the crossing direction of the road. Flatness is an index indicating the degree of unevenness in the longitudinal direction of the road. MCI is an index calculated based on the crack rate, rutting amount and flatness. Further, the three-dimensional data is three-dimensional data of the measured structure around the road and the shape of the pavement. The output data is output by the data output unit 18 to other devices connected to the network (not shown), an external memory, a printer, and the like.

  2 for details of the functions of the data acquisition unit 11, the position specifying unit 12, the index generation unit 13, the index conversion unit 14, the analysis unit 15, the storage unit 16, and the setting unit 17 in the facility management apparatus 1. I will explain.

Next, a specific configuration example of the facility management apparatus 1 will be described.
FIG. 2 is a block diagram illustrating an example of the configuration of the facility management apparatus according to the embodiment.

  In FIG. 2, the facility management device 1 is connected to a measuring device 2. The user terminal 3 and the administrator terminal 4 are communicably connected.

  The measuring device 2 measures the state of the infrastructure facility. As described above, the measuring device 2 is, for example, an MMS, a television camera, a three-dimensional laser measuring instrument, a vibrometer, a drive recorder, a GPS receiver, a microphone, or the like. If the measuring device 2 measures the state of an infrastructure facility, for example, an ammeter, a voltmeter, a power meter, a load cell, a thermometer, a hygrometer, a water level meter, a water quality meter, a noise meter, a flaw detector, a pH meter Etc. The measuring device 2 outputs the measured measurement data to the facility management device 1 via the network 9.

  The user terminal 3 is a terminal operated by a user who uses the facility management apparatus 1. For example, the user terminal 3 acquires the analysis result of the MCI analyzed in the facility management apparatus 1 from the facility management apparatus 1 via the network 9.

  The administrator terminal 4 sets the facility management apparatus 1 via the network 9. For example, the administrator terminal 4 sets the weighting applied in the index conversion unit 14 for each measuring device 2. The administrator terminal 4 may manage feature amount data used for specifying a position in the position specifying unit 12. Further, when the position specifying result in the position specifying unit 12 is not correct, the manager terminal 4 corrects or deletes the result.

  The facility management apparatus 1 includes a data acquisition unit 11, a position specifying unit 12, a storage unit 121, an index generation unit 13, an index conversion unit 14, a storage unit 141, an analysis unit 15, a measurement data storage unit 16A, and a maintenance management master data storage unit. 16B and the setting unit 17 are provided. In FIG. 2, the function of the data output unit 18 of FIG. 1 is not shown.

  The data acquisition unit 11 is a communication interface that is connected to the measurement device 2 wirelessly or by wire and acquires measurement data output from the measurement device 2. The data acquisition unit 11 may have a plurality of communication methods according to the measurement device 2 to be connected. The data acquisition unit 11 stores the acquired measurement data in the measurement data storage unit 16A. The measurement data storage unit 16A is an example of the storage unit 16 illustrated in FIG.

  The position specifying unit 12 specifies the position of the facility of the acquired measurement data. The position specifying unit 12 specifies a position by extracting a later-described feature amount of the acquired measurement data and confirming a match with a previously stored feature amount. Details of the processing in the position specifying unit 12 will be described later. For example, when the measurement data is road pavement, the position specifying unit 12 specifies the longitude and latitude of the pavement position. The position specifying unit 12 may specify the measurement data acquisition position as a planar position or a three-dimensional position.

  The storage unit 121 stores setting information used in the specifying process executed by the position specifying unit 12. Details of the measurement position specifying process will be described later.

  The index generation unit 13 generates an index indicating the deterioration of the facility based on the input data acquired by the data acquisition unit 11. The index indicating the deterioration of the facility is, for example, the above-described MCI. MCI can be generated based on image data acquired as input data. Details will be described later with reference to an example of processing for generating a crack rate as index generation processing in the index generation unit 13.

  The index conversion unit 14 applies a weight corresponding to the measurement device to the index generated by the index generation unit 13. Here, weighting refers to applying a predetermined coefficient (weight) to an index based on measurement data measured by each measurement device. For example, when the same index is calculated by a high-precision measurement device and a low-precision measurement device for the same measurement position, a high-precision index based on measurement data measured by a high-precision measurement device is more accurate. The numerical reliability is higher than that of a low-accuracy index based on measurement data measured by a low-measurement device. Therefore, the index conversion unit 14 increases the weighting of the high-accuracy index compared to the low-accuracy index. By performing the weighting, it is possible to evaluate the generated indexes in a unified manner even when the indexes generated at a plurality of measurement times are generated by different measuring devices.

  FIG. 5 is a diagram illustrating an example of weighting for the index measured by the facility management apparatus according to the embodiment.

  FIG. 5A shows a setting example of weighting for the type of camera when the measuring device of the measuring apparatus 2 is a camera. Camera A, camera B, and camera C are cameras having different performances. For example, the camera A is a low-resolution television camera used for a drive recorder or the like. The error range of camera A is ± 5%, and the weight is set to 0.5. The camera C is a high-resolution television camera used for MMS or the like, has an error range of ± 1%, and sets the weight to 1.0. The camera B is a television camera having a resolution approximately in the middle between the camera A and the camera C, the error range is ± 3%, and the weight is set to 0.8. Therefore, the measurement data measured by the camera C is weighted twice with respect to the measurement data measured by the camera A. Note that the error range of the camera may be acquired from the measurement apparatus 2 as device data.

  FIG. 5B shows a setting example of weighting for the type of distance sensor when the measuring device of the measuring apparatus 2 is a distance sensor. The distance sensors A to C are sensors having different performances, and each has an error range shown in the figure. The weighting shown in the figure can be set for each of these distance sensors. For example, the distance sensor A is an ultrasonic sensor, the distance sensor B is an LED sensor, and the distance sensor C is a laser sensor. FIG. 5C shows a setting example of weighting for the type of AE sensor when the measuring device of the measuring apparatus 2 is an AE (Acoustic Emission) sensor.

  In addition, in FIG. 5, although the case where the weighting in the measurement device of the same kind with different performance was set was demonstrated, weighting is performed according to the number of sensors, the environment at the time of measurement, the running state of a vehicle, etc., for example. Also good. The environment at the time of measurement is, for example, conditions such as whether or not there is rainfall, whether it is day or night, and the number of falling objects. Further, the traveling state of the vehicle includes the vehicle speed, the traveling position of the lane (the distance from the sensor to the measurement position), and the like.

  Returning to FIG. 2, the weights stored in the storage unit 141 are set in advance by the setting unit 17 and stored in the storage unit 141 corresponding to the measurement device. The index conversion unit 14 stores and accumulates the index to which the weight is applied in the maintenance master data accumulation unit 16B. By storing the index in the index conversion unit 14, an index indicating the deterioration of the facility measured by a plurality of measurement methods is stored. The measurement data storage unit 16A and the maintenance management master data storage unit 16B are examples of the storage unit 16 described in FIG.

  The analysis unit 15 applies the weight of the facility at the position specified by the position specifying unit 12 based on the index such as MCI to which the weight is applied by the index conversion unit 14 and the weight stored in the maintenance master data storage unit 16B. Analyze the degradation state spatially or temporally. The analysis of the deterioration state is, for example, a process of determining the deterioration state of the facility based on the accumulated index, and generating and visualizing information for repairing or updating the facility. The maintenance management master data storage unit 16B stores weighted indices generated by a plurality of measurements. Therefore, the accumulated index can be covered by another measurement even if a malfunction such as a false detection occurs in a part of the measurement, and the reliability is improved. The analysis unit 15 can correctly evaluate the deterioration of the facility by applying weighting in the index conversion unit 14 and using the index stored in the maintenance master data storage unit 16B. The analysis unit 15 calculates, from the start point to the end point, an index such as MCI measured and weighted by a plurality of measuring devices when the position specifying unit 12 specifies the start point and end point of the road in the measurement data. Analyze pavement degradation.

  The analysis unit 15 outputs the analysis result in which the measurement position and the degree of deterioration are associated with each other to the user terminal 3 to be visualized. The analysis unit 15 may output the analysis result to a printer or the like (not shown) for visualization. Further, the analysis unit may provide the user terminal 3 or the like with information on the time and method of repairing or updating the facility. The analysis unit 15 may output the analysis result as predetermined form data. The analysis result may include spatial data (GIS screen data) using GIS (Geographic Information System). The analysis result may visualize the behavior of the index such that the index increases, decreases, or vibrates over time.

  As the storage unit 16, for example, a storage device such as a hard disk drive or a nonvolatile memory can be used alone or in combination. As described above, the storage unit 16 includes the measurement data storage unit 16A and the maintenance management data storage unit 16B. The measurement data storage unit 16A and the maintenance management data storage unit 16B share a storage device such as a hard disk drive. You may do. The storage unit 16 may store data and programs used in the position specifying unit 12, the index generation unit 13, the index conversion unit 14, the setting unit 17, and the like.

  The setting unit 17 stores the setting information set in the administrator terminal 4 in the storage unit 121, the storage unit 141, and the maintenance management master data storage unit 16B. The setting information can include device information, user identification information, and the like in addition to the weighting information associated with the measurement apparatus 2. The setting unit 17 may be a Web server that provides a user interface (UI) for setting setting information to the administrator terminal 4 connected via a network. The setting unit 17 may have a data receiving function for receiving data including setting information configured in a predetermined format from the administrator terminal 4. For example, the setting unit 17 sets the weight applied in the index conversion unit 14 in association with the measurement device, and stores the weight in the storage unit 141 or the like so as to be readable from the index conversion unit 14.

  The data output unit 18 outputs the output data to the outside of the facility management apparatus 1. The data output unit outputs the output data to, for example, another device connected via a network (not shown), an external memory, a printer, and the like.

Next, facility management processing executed by the facility management apparatus 1 will be described.
FIG. 3 is a flowchart illustrating an example of the facility management process according to the embodiment. In the following description, FIGS. 1 and 2 will be referred to as appropriate.

  In FIG. 3, the facility management apparatus 1 starts recording input data (step S11). For example, the data acquisition unit 11 starts acquisition of measurement data output by the measurement device 2 by an operation of the operator of the facility management device 1, and starts recording in the measurement data storage unit 16A.

  After executing the process of step S11, the facility management apparatus 1 extracts the feature amount of the acquired measurement data (step S12). The feature amount is a characteristic change of measurement data such as an image and sound included in the measurement data measured by the measurement device 2, and is information for specifying a measurement position. For example, when roads are paved, road signs such as road signs, traffic lights, guardrails, buildings, roadside structures, pedestrian crossings, center lines, center lines, headwaters, etc. The position and shape of images such as these do not change much over time. For this reason, the change pattern of the image data etc. which image | photographed these with respect to the advancing direction of a vehicle can be used as a feature-value which specifies a measurement position. Also, changes in image data or the like based on an image of the road crack itself in the traveling direction of the vehicle may be used as a feature amount because there is little change in a short period of time. The position specifying unit 12 extracts a change pattern of measurement data at a predetermined distance as a feature amount from continuous measurement data in the traveling direction of the vehicle. Details of the feature amount extracted in step S12 will be described later with reference to FIG.

  After executing the process of step S12, the facility management apparatus 1 determines whether or not the feature quantity extracted in the process of step S12 matches the feature quantity stored and accumulated in the past (step S13). . For example, when a road sign, a center line, or the like is present in a predetermined section in the traveling direction of the vehicle, the feature amount obtained by performing image processing such as shape recognition on the captured image obtained by capturing these is the vehicle traveling A similar change in direction is indicated. That is, the feature amount of the captured image in the same section is similar in a plurality of measurements. The position specifying unit 12 compares the feature quantity of the acquired measurement data with the feature quantity of the captured image or the like measured in the past, and determines whether or not they match. The matching of feature quantities can be realized by a technique such as pattern matching. In addition, since the change of the feature-value in the advancing direction of a vehicle is measured by driving | running | working of a vehicle, it changes with the driving speed of a vehicle. When the vehicle speed is high, the time interval at which the feature amount appears is short, and when the vehicle speed is low, the time interval is long. The position specifying unit 12 can correct the feature amount based on time information included in the position data.

  When it is determined that the extracted feature value matches the feature value stored and accumulated in the past (step S13: YES), the facility management apparatus 1 is included in the measurement data stored and accumulated in the past. The measurement position of the acquired measurement data is specified from the acquired position data, and the specified position data is added to the acquired measurement data and recorded in the measurement data storage unit 16A (step S14). The measurement data recorded in the measurement data storage unit 16A is read from, for example, the analysis unit 15 and provided to the user terminal.

Here, the feature amount of the measurement data extracted in the process of step S12 in FIG. 3 and compared in the process of step S13 will be described.
FIG. 4 is a diagram illustrating an example of a feature amount used for the measurement position specifying process of the facility management apparatus 1 according to the embodiment.

  The feature value of the measurement data shown in FIG. 4A is recorded in advance in the storage unit 121 and compared with the feature value of the acquired measurement data shown in FIG. 4B when specifying the measurement position. It is reference data that is sometimes used as a reference. In FIG. 4A, the vertical axis exemplifies image data, unevenness data, point cloud data, and audio data as measurement data serving as reference data. The horizontal axis indicates the distance in the traveling direction of the vehicle on the road from the left side to the right side in the figure. Point a in the figure is the distance at the start of measurement. The feature amount is a change pattern of measurement data in the traveling direction.

  Each reference data shown in FIG. 4A is measured and recorded in advance, for example, in a vehicle equipped with a high-accuracy GPS receiver. For example, the image data feature quantity serving as the reference data is recorded as an image change pattern together with the distance information indicated by the GPS data. The figure shown in the figure represents the image to be photographed in a simulated manner. The unevenness data feature amount is recorded as a change in the shape of the road surface together with the GPS data. The feature amount of the point cloud data is recorded as a change in the three-dimensional data of the structure detected together with the GPS data. The feature amount of the voice data is recorded as a change in the voice data collected together with the GPS data. The GPS data is acquired by a GPS receiver mounted on a vehicle on which a measurement device is mounted. The GPS data may be corrected as appropriate based on, for example, map information, an accelerometer, and the like. In FIG. 4A, the numerical values of GPS data (such as longitude and latitude) are not shown.

  FIG. 4B shows the feature amount of the acquired measurement data. For example, it is assumed that the acquired image data changes from the distance a to the distance c in the illustrated measurement data. Here, it is determined whether image data changes coincide with each other at a predetermined distance as a feature amount. Then, a portion having the feature amount of the image data is found in the reference data in FIG. As a result, the position of the image data in which the feature amount is matched is specified. When the position is specified, the image data is recorded together with the specified position data. Once the feature amounts match, for example, it can be determined that the change in the image data at the distance c is also the correct position. The matching of feature quantities is compared until the feature quantities do not match. For example, when the traveling vehicle moves away from the section registered as the reference data, the measurement position can be estimated based on the position where the match is finally determined. Similarly, when the coincidence of the feature amounts of the unevenness data is determined at the distance b, the unevenness data at the position of the distance b is recorded.

  In the present embodiment, by storing feature value reference data in advance, it is possible to acquire an accurate measurement position in the stored measurement data. Therefore, for example, even in a measurement apparatus that does not have a GPS receiver, it is possible to easily grasp the position where measurement data is measured.

  Note that the matching of the feature amounts may be corrected as appropriate by the operator confirming the captured image, for example. For example, when it is known in advance that there is a change in the structure around the road, the reference data in the section in which the structure or the like is changed may be corrected, or the judgment result of the feature amount may be corrected. Good.

Returning to FIG. 3, after performing the process of step S14, the facility management apparatus 1 generates an index indicating the deterioration of the facility based on the measurement data (step S15). The indicator is, for example, a crack rate of pavement. The crack rate is calculated by calculating the area of pavement cracks based on the number of cracks existing in the grid, assuming a grid (mesh) with a side of 0.5 m on the road surface seen from directly above. is there. For example, when there are two or more cracks in the grid, it is calculated to be 0.25 m 2 (100%). Similarly, when there is one crack in the square, it is calculated as 0.15 m 2 (60%), and when there is no crack in the square, it is calculated as 0 m 2 (0%). That is, the crack rate is expressed by the following equation.
Crack rate (%) = 100 x (Crack area) / (Survey area)
Note that the index generated by the process of step S15 is arbitrary. The generated index may be selected according to the facility to be managed.

  After executing the process of step S15, the facility management apparatus 1 converts the index by applying a weight to the index generated by the process of step S15 (step S16). For example, the index conversion unit 14 acquires device data of the measurement apparatus that has acquired the measurement data that is the basis of the index generated by the index generation unit 13. The device data can be acquired by the data acquisition unit 11 from the measurement device 2 and stored together with the measurement data in the measurement data storage unit 16A so as to be readable from the index generation unit 13. Based on the acquired device data, the index conversion unit 14 selects a weight to be applied to the index corresponding to the measurement device 2 that acquired the measurement data. The weighting corresponding to the measuring device 2 is set in the administrator terminal 4 in advance as described above, and stored in the storage unit 141 via the setting unit 17. The index conversion unit 14 applies the selected weighting to the index. The weighting is a means for optimizing indexes generated respectively in measurement apparatuses having various measurement accuracy. For example, since the index based on the measurement data measured with high accuracy has high reliability, the weight is increased. That is, the index converted by applying weighting is an index in which reliability is considered. The method of applying weighting is arbitrary. For example, the index may be converted using a weighted average in weighting. Further, the index may be converted by applying a predetermined function.

  After executing the process of step S16, the facility management apparatus 1 stores and accumulates the index converted by the process of step S16 in the maintenance management master data accumulation unit 16B (step S17). By accumulating the converted index, the index generated based on the measurement data of various measuring devices is accumulated in the maintenance management master data accumulating unit 16B together with the weighting. For example, for a road pavement at a predetermined measurement position, the cracking rate and the like based on different measurement data of the measurement time and the measurement device are respectively weighted and accumulated. As a result, problems due to erroneous detection and the like are reduced, and the reliability of the index can be improved.

  When the facility management apparatus 1 determines that the extracted feature amount does not match the feature amount accumulated in the past (step S13: NO) after executing the process of step S17 or in the process of step S13, It is determined whether or not recording of measurement data is to be terminated (step S18). Whether or not recording of measurement data is to be ended can be determined based on, for example, whether or not there has been an operation by the operator. When it is determined that the recording of the measurement data is not finished (step S18: NO), the facility management apparatus 1 returns to the process of step S12 and repeatedly executes the processes of step S12 to step S17. On the other hand, when it is determined that recording of the measurement data is to be ended (step S18: YES), the facility management apparatus 1 ends the process of the flowchart shown in FIG.

  According to at least one embodiment described above, the facility management apparatus includes a data acquisition unit, a position specifying unit, an index generation unit, and an index conversion unit, so that the facility is measured by a plurality of measurement methods. Can be evaluated correctly.

In this embodiment, a data acquisition part acquires the measurement data measured with the measuring device which measures the state of a facility.
In the above description, road pavement is exemplified as the facility, but the facility in the present embodiment is not limited to road pavement. The facility may be a facility such as a bridge, tunnel, building, dam, water or sewage facility, or power plant. The facility may be a vehicle, a ship, or the like, or may be a ground, a slope, or the like.
Moreover, the measurement data measured by the measuring device is data for indirectly evaluating the deterioration of the facility, even if it is data for directly evaluating the deterioration of each facility such as MCI in pavement. Also good. As measurement data, for example, data such as voltage value, current value, power value, temperature, humidity, pressure, production amount, and processing amount may be used.

In the present embodiment, the position specifying unit specifies the position of the facility where the measurement data is measured based on the acquired measurement data.
In the above description, the location to be identified is exemplified by longitude and latitude information, but the method for identifying the location of the facility is not limited to longitude and latitude. For example, the position may be specified by the distance from the reference point, the direction, the address, the name, the part, or the like.

In the present embodiment, the index generation unit generates an index indicating the deterioration of the facility based on the acquired measurement data.
The generated index is not limited to an index defined by a predetermined standard or standard such as MCI in pavement. The generated index may be an index uniquely determined by a person who manages the facility, for example. Moreover, the parameter | index which shows deterioration of a facility directly or indirectly may be sufficient.

In the present embodiment, the index conversion unit applies a weight corresponding to the measurement device to the generated index.
The weighting may be applied individually to each generated indicator or may be applied to a plurality of indicators. For example, weighting may be applied to the total value or average value of indexes generated in a plurality of measurements. Further, the variation of the index generated in a plurality of measurements may be obtained, and weighting may be applied according to the obtained variation.

  The above-described apparatus may be realized by a computer. In that case, a program for realizing the function of each functional block is recorded on a computer-readable recording medium. The program recorded on the recording medium may be read by a computer system and executed by a CPU (Central Processing Unit). The “computer system” here includes an OS (Operating System) and hardware such as peripheral devices. The “computer-readable recording medium” refers to a portable medium such as a flexible disk, a magneto-optical disk, a ROM (Read Only Memory), and a CD-ROM. The “computer-readable recording medium” includes a storage device such as a hard disk built in the computer system. Furthermore, the “computer-readable recording medium” may include a medium that dynamically holds a program for a short time. What holds the program dynamically for a short time is, for example, a communication line when the program is transmitted via a network such as the Internet or a communication line such as a telephone line. In addition, the “computer-readable recording medium” may include a medium that holds a program for a certain period of time, such as a volatile memory inside a computer system that serves as a server or a client. The program may be for realizing a part of the functions described above. Further, the program may be a program that can realize the above-described functions in combination with a program already recorded in the computer system. The program may be realized using a programmable logic device. The programmable logic device is, for example, an FPGA (Field Programmable Gate Array).

  In addition, each function of the above-described device can be realized by a software function. However, some or all of the functions of the above-described apparatus may be realized by hardware functions. In addition, each function of the above-described apparatus may be realized by combining a plurality of functions as one function unit, or may be realized by dividing one function into a plurality of functions.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

  DESCRIPTION OF SYMBOLS 1 ... Facility management apparatus, 2 ... Measuring apparatus, 3 ... User terminal, 4 ... Manager terminal, 11 ... Data acquisition part, 12 position specific | specification part, 13 ... Index production | generation part, 14 ... Index conversion part, 15 ... Analysis part, 16 ... Storage unit, 17 ... Setting unit, 18 ... Data output unit

Claims (18)

A data acquisition unit that acquires measurement data measured by a measurement device that measures the state of the facility;
Based on the acquired measurement data, a position specifying unit that specifies the position of the facility where the measurement data is measured;
Based on the acquired measurement data, an index generation unit that generates an index indicating deterioration of the facility;
A facility management apparatus comprising: an index conversion unit that applies a weight corresponding to the measurement apparatus to the generated index.   The facility management apparatus according to claim 1, further comprising an analysis unit that analyzes the index to which weighting is applied at the identified position.   The facility management apparatus according to claim 1, wherein the position specifying unit specifies the position based on a characteristic of the acquired measurement data.   The facility management apparatus according to claim 3, wherein the position specifying unit specifies the position based on a feature indicating a change with time of the acquired measurement data. A storage unit for storing the acquired measurement data;
The facility management according to claim 3 or 4, wherein the position specifying unit specifies the position by comparing the acquired characteristic of the measurement data with the characteristic of the measurement data stored in the storage unit. apparatus. The data acquisition unit acquires measurement data from a plurality of types of measurement devices,
The facility management device according to any one of claims 1 to 5, wherein the index conversion unit applies weighting corresponding to a type of the measurement device. A setting unit that presets the correspondence between the measuring device and the weighting;
The facility management device according to any one of claims 1 to 6, wherein the index conversion unit applies the weighting based on the set correspondence. The setting unit sets a weight according to the measurement performance of the measurement device,
The facility management apparatus according to claim 7, wherein the index conversion unit applies a weight corresponding to the set measurement performance.   The facility management apparatus according to any one of claims 1 to 8, wherein the index generation unit generates an index indicating deterioration related to a change with time of the shape based on the measurement data indicating the shape of the facility. . A data acquisition step for acquiring measurement data measured by a measuring device for measuring the state of the facility;
Based on the acquired measurement data, a position specifying step for specifying the position of the facility where the measurement data is measured;
An index generation step for generating an index indicating deterioration of the facility based on the acquired measurement data;
An index conversion step of applying a weight corresponding to the measurement device to the generated index.   The facility management method according to claim 10, further comprising an analysis step of analyzing the index to which weighting is applied at the specified position.   The facility management method according to claim 10 or 11, wherein, in the position specifying step, the position is specified based on characteristics of the acquired measurement data.   The facility management method according to claim 12, wherein in the position specifying step, the position is specified based on a characteristic indicating a change with time of the acquired measurement data. A storage step of storing the acquired measurement data;
The facility management according to claim 12 or 13, wherein, in the position specifying step, the position is specified by comparing the acquired characteristic of the measurement data with the characteristic of the measurement data stored in the storing step. Method. In the data acquisition step, measurement data is acquired from a plurality of types of measurement devices,
The facility management method according to any one of claims 10 to 14, wherein, in the index conversion step, weighting corresponding to a type of the measuring device is applied. A setting step of presetting the correspondence between the measuring device and the weighting;
The facility management method according to claim 10, wherein, in the index conversion step, the weighting is applied based on the set correspondence. In the setting step, a weight is set according to the measurement performance of the measurement device,
The facility management method according to claim 16, wherein weighting corresponding to the set measurement performance is applied in the index conversion step.   The facility management method according to any one of claims 10 to 17, wherein, in the index generation step, an index indicating deterioration related to a change with time of the shape is generated based on the measurement data indicating the shape of the facility. .

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