JP6673510B1 - Structure monitoring device, structure monitoring method, and structure monitoring program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a structure monitoring device in which each device autonomously learns and determines the operating time without setting the operating time to each structure monitoring device from the outside. The present invention relates to a structure monitoring device for monitoring a structure that a vehicle is passing, and includes a measuring unit that measures a passing condition of the vehicle at a measurement time, and a passing condition of the vehicle measured by the measuring unit. Based on the calculated traffic frequency of the vehicle in each time zone, the future traffic frequency is estimated from the calculated vehicle traffic frequency and the past vehicle traffic frequency. And a schedule determining means for setting a time zone having a high traffic frequency as the next measurement time of the measuring means. [Selection diagram] Fig. 1

Description

  The present invention relates to a structure monitoring device, a structure monitoring method, and a structure monitoring program, and can be applied to, for example, a sensor device fixedly installed on a structure such as a bridge that vibrates due to a load such as a vehicle.

  Conventionally, many attempts have been made to install various sensors on a vibrating structure (for example, a bridge) and measure the soundness of the structure (see Patent Document 1). In order to determine the soundness of a structure, it is necessary to apply a load to the structure. What is given as a load on a daily basis is, for example, a weight associated with the passage of a vehicle or the like.

  By the way, power is required to operate the sensor device, but it is not easy to secure a power source outdoors such as a bridge. In addition, there are many places where the equipment is installed, such as behind the floorboard of a bridge, which cannot be reached by ordinary methods, and it is not practical to frequently change batteries. Even if a power generation function such as a solar cell is used, it is difficult to always drive the sensor device. However, the structure deteriorates over a long period of time, and there is little need for constant monitoring. It is rational to perform monitoring intermittently and increase the frequency of monitoring if there is an abnormality.

  On the other hand, monitoring by the sensor device needs to be performed at the time when the vehicle passes. However, the time at which the vehicle passes is not obvious. In an environment with sufficient traffic, it is possible to achieve the objective only by operating at an appropriate time.However, in an environment with low traffic such as in a sparsely populated area, the vehicle can be operated simply by operating appropriately. It is difficult to obtain data at the time of passage.

JP-A-2017 / 064854

  In the conventional structure monitoring system, a time zone during which traffic is heavy is estimated based on past knowledge and a result of a survey, and setting is performed so that the device is operated at the estimated time. However, there are problems that it is difficult to verify whether or not the prediction is correct, it is necessary to make settings for individual devices, and it takes time and effort.

  Therefore, a structure monitoring device, a structure monitoring method, and a structure monitoring program that each device autonomously learns and determines the operation time without externally setting the operation time of each structure monitoring device. Is desired.

  According to a first aspect of the present invention, there is provided a structure monitoring apparatus for monitoring a structure passing by a vehicle, wherein (1) measuring means for measuring a traffic condition of the vehicle at a measurement time, and (2) measuring means for measuring the traffic condition. Based on the traffic situation of the vehicle, the traffic frequency of the vehicle in each time zone is calculated, the future traffic frequency is estimated from the calculated traffic frequency of the vehicle and the traffic frequency of the past vehicle, and the estimated future traffic frequency is estimated. And a schedule determining unit that sets a time zone in which the vehicle travels most frequently as the next measurement time of the measuring unit.

  According to a second aspect of the present invention, there is provided a structure monitoring method used in a structure monitoring apparatus for monitoring a structure passing by a vehicle, comprising: a measuring unit and a schedule determining unit; (2) The schedule determination means calculates the traffic frequency of the vehicle in each time zone based on the traffic status of the vehicle measured by the measurement means, and (2) calculates the traffic frequency of the vehicle in each time zone. Estimating the future traffic frequency from the past vehicle traffic frequency and the estimated future traffic frequency, and setting the time zone where the vehicle traffic frequency is the highest as the next measurement time of the measuring means. Features.

  The structure monitoring program according to a third aspect of the present invention includes: a computer mounted on a structure monitoring device that monitors a structure through which a vehicle passes; (1) a measuring unit that measures a traffic condition of the vehicle at a measurement time; 2) Based on the traffic condition of the vehicle measured by the measuring means, the traffic frequency of the vehicle in each time zone is calculated, and the future traffic frequency is estimated from the calculated traffic frequency of the vehicle and the traffic frequency of the past vehicle. The time period in which the frequency of vehicle traffic is the highest among the estimated future traffic frequencies is made to function as schedule determination means to be the next measurement time of the measurement means.

  ADVANTAGE OF THE INVENTION According to this invention, each apparatus can autonomously learn and determine the operating time, without setting the operating time for each structure monitoring apparatus from outside.

FIG. 2 is an internal configuration diagram illustrating an internal configuration of the wireless device according to the embodiment. 1 is an overall configuration diagram illustrating an overall configuration of a data measurement system according to an embodiment. FIG. 3 is an explanatory diagram illustrating an example of an operation schedule of the wireless device according to the embodiment. It is explanatory drawing (the 1) which shows an example of the vehicle traffic situation measured according to the schedule determined by the schedule determination part which concerns on embodiment. It is explanatory drawing which shows the example which normalized the vehicle traffic situation of FIG. 4 which concerns on embodiment. It is explanatory drawing (the 2) which shows an example of the vehicle traffic situation measured according to the schedule determined by the schedule determination part which concerns on embodiment. It is explanatory drawing which shows an example of the frequency | count of the measurement of the passing vehicle measured according to the schedule determined by the schedule determination part which concerns on embodiment. It is explanatory drawing which shows the expected value of the number of passing vehicles per unit time in each time zone calculated by the schedule determination unit according to the embodiment.

(A) Main Embodiment Hereinafter, main embodiments of a structure monitoring device, a structure monitoring method, and a structure monitoring program according to the present invention will be described in detail with reference to the drawings.

(A-1) Configuration of Embodiment [Overall Configuration]
FIG. 2 is an overall configuration diagram illustrating an overall configuration of the data measurement system according to the embodiment.

  2, the data measurement system according to the embodiment includes a wireless device 10 (10-1 to 10-n), a master device 20, and a monitoring device 30 as a structure monitoring device.

  In FIG. 1, the network between each wireless device 10 and the master device 20 is a sensor network SN. In general, a low-speed wireless communication system represented by a specific low-power wireless system or the like can be applied to the communication system of the sensor network SN. For example, a wireless network standard represented by IEEE 802.11a / b / g / n or a wireless communication system such as IEEE 802.15.4 or Bluetooth (registered trademark) may be used. The sensor network SN is a communication method that is slower than the trunk network NT.

  The network between the master device 20 and the monitoring device 30 is a backbone network NT. The backbone network NT is, for example, Internet or Ethernet (registered trademark). The backbone network NT may be a wireless line or a wired line.

  The data measurement system 1 is a system in which the monitoring device 30 collects sensor data of each wireless device 10 via the master device 20. The data measurement system 1 mainly includes each wireless device 10, the master device 20, and the monitoring device 30.

[wireless device]
The wireless device 10 mainly includes a sensor, a schedule determining unit, and a communication unit. The wireless device 10 determines the time to operate the sensor while learning as needed. Data measured by the wireless device 10 is transmitted to the master device 20 via the sensor network SN. In this embodiment, it is assumed that the wireless device 10 is installed so as to be fixed to a structure such as a bridge, for example.

[Master unit]
Master device 20 has a function of relaying data between sensor network SN and backbone network NT. When receiving data from each wireless device 10, master device 20 transmits information including data of each wireless device 10 to monitoring device 30. Thereby, sensor data can be provided to the monitoring device 30.

[Monitoring device]
The monitoring device 30 collects information including sensor data from each wireless device 10 via the master device 20, and stores (accumulates and manages) each data. In addition, as a modified example, a configuration in which the devices of the master device 20 and the monitoring device 30 are integrated may be adopted.

[Internal configuration of wireless device]
FIG. 1 is an internal configuration diagram illustrating an internal configuration of the wireless device 10 according to the embodiment.

  1, the wireless device 10 includes a communication unit 101, a control unit 102, an acceleration sensor 103, a schedule determination unit 104, a timer unit 105, and a clock 106.

  In the wireless device according to the present embodiment, each unit may be configured by hardware, and a part of the configuration may be configured by software.

  The communication unit 101 is a communication interface for accessing the sensor network SN.

  The control unit 102 controls each unit and generates data to be transmitted to the master device 20 (monitoring device 30).

  The acceleration sensor 103 senses a physical quantity to be measured on a structure such as a bridge. In addition to the acceleration sensor, various types of sensors such as a temperature sensor, a humidity sensor, a vibration sensor, and an infrared image sensor may be used.

  The schedule determination unit 104 determines a time at which the wireless device 10 is activated (a time at which the acceleration sensor 103 is next measured) by using a traffic situation of the vehicle estimated from the measurement result of the acceleration sensor 103. The details of the schedule determination unit 104 will be described in the section of the operation.

  The timer unit 105 is a functional unit that changes the wireless device 10 from the hibernation state to the activation state according to the specification of the schedule determination unit 104. Here, the halt state means halt of components other than the timer unit 105 and the clock 106.

  The clock 106 is a clock that provides the current time.

(A-2) Operation of the Embodiment Next, the operation of the data measurement system 1 of the embodiment having the above configuration will be described with reference to the drawings. In this embodiment, the operation schedule determination processing of each wireless device 10 included in the data measurement system 1 has a feature. Therefore, the following description focuses on the operation schedule determination process of the wireless device 10.

  First, an outline of the operation of the wireless device 10 will be briefly described.

  The wireless device 10 activates the acceleration sensor 103 for a certain period of time to acquire sensing data (measurement result) indicating characteristics of the structure. The wireless device 10 estimates the traffic condition of the vehicle (presence or absence of traffic) based on the measurement result. The wireless device 10 transmits the measurement result and the traffic condition of the vehicle to the monitoring device 30 using the communication unit 101.

  Next, a schedule process for operating the wireless device 10 will be described.

(A-2-1) Operation schedule determination processing (initial state)
In the initial state, the schedule determination unit 104 determines a schedule so as to operate at regular intervals in order to collect data at each time. At this time, the schedule determining unit 104 assumes that the traffic of the vehicle has a periodicity due to a human activity cycle or the like, and sets an interval that is relatively prime to the assumed cycle.

  FIG. 3 is an explanatory diagram illustrating an example of an operation schedule in an initial state of the wireless device according to the embodiment.

  In FIG. 3, the operation time of the wireless device 10 is 1 hour, and the assumed activity cycle is 24 hours (= 1 day) and 168 hours (= 1 week). 23 hours was used as an interval which is relatively prime to these. FIG. 3 shows an example in which the operation is started at 0:00 on Monday. Since it is every 23 hours, it also operates at 23:00 on the same day. The next operation will be at 22:00 on the second day. The number in each cell in FIG. 3 indicates on which day from the start the operating state was activated in the time zone.

  In the example of FIG. 3, it can be seen that the operation is performed on all the days and times in 161 days. Naturally, in the initial state, it is possible to acquire all the data in seven days by keeping the wireless device 10 always operating. However, in this case, the power consumption per day is 20 times or more. It should be noted that the battery life of the sensor device is reduced by 150 days or more compared to the case where the operation is performed for one hour per day.

  It should be noted that the schedule determination unit 104 may adopt a method of setting a probability based on general knowledge instead of using actual measurement data as an initial state. For example, it is also possible to set a probability from knowledge such as "there is commuting at 8:00 and 18:00 on weekdays".

(A-2-2) Operation schedule determination processing (after initial state)
Next, a process in which the schedule determining unit 104 corrects (determines) the operation schedule from the obtained vehicle traffic condition data and the like will be described. As an example, a case where the operation is finally performed for one hour per day will be described.

  It is assumed that the schedule determining unit 104 periodically measures the vehicle according to the schedule shown in FIG. The number of each cell in FIG. 4 indicates the number of vehicles passing in each time zone.

  FIG. 5 is an example in which the total number of vehicles for each day of the week in FIG. The schedule determining unit 104 determines the next measurement time from the result of FIG. For example, the schedule determination unit 104 may stochastically select the operation time according to the day of tomorrow. In the example of FIG. 5, if the next day is Monday, the schedule determination unit 104 selects the eight o'clock range of “0.13”, which is the value with the highest probability.

  Note that, at this time, the schedule determination unit 104 performs processing such as further increasing the selection probability of the time when the number of vehicles is large, and setting the probability to 0 when the number of vehicles is equal to or less than a certain value such as 1 or 2. Next, the time at which measurement is performed may be determined.

  Further, even if the data in the time zone as shown in FIG. 4 (FIG. 5) is not prepared, the schedule determination unit 104 can determine the operation schedule by a predetermined method such as supplementing with the data before and after the time, and other data such as other days of the week. May be modified.

  Then, the schedule determining unit 104 reflects the result of the actual operation on the vehicle traffic status data (FIG. 4) as needed. At the time of reflection, simply adding the values increases the value of the time zone in which the operating time is long, so it is necessary to use the number of vehicles passing per operating time. For this reason, the wireless device 10 needs to keep the number of passing vehicles and the operating time at each time. FIG. 6 shows the number of passing vehicles measured after a lapse of a predetermined period from the state of FIG. FIG. 7 shows the number of times of measurement of passing vehicles in each time zone.

  The schedule determination unit 104 calculates an expected value of the number of passing vehicles per unit time in each time zone based on the number of passing vehicles in FIG. 6 and the number of times of measurement of the passing vehicle in FIG. The operation schedule is determined so that the time zone in which is larger is operated preferentially.

  By repeating the above series of processing, the probability of selecting a time zone in which the vehicle can be expected to travel more reliably increases, and the probability of selecting a time zone in which the vehicle cannot be expected is reduced.

(A-3) Effects of the Embodiment According to the present embodiment, the following effects can be obtained.

  By learning the time at which the wireless device 10 operates itself autonomously, the situation where the vehicle does not pass during the operating time (the measurement time of the acceleration sensor 103) is reduced. This leads to a reduction in power consumption, for example, when the measurement is continued until a certain number of vehicles pass. In addition, when the measurement is performed for a certain period of time irrespective of the presence or absence of vehicle traffic, it is possible to reliably measure the state of deterioration of the structure.

(B) Other Embodiments The present invention is not limited to the above embodiments, but may include modified embodiments as exemplified below.

  (B-1) In the above embodiment, the holidays of each date are not taken into account. However, for example, calendar information is distributed from the monitoring device 30, and the radio device 10 uses the calendar information to Can be handled as another day of the week (for example, if Monday is a holiday, it may be handled as Sunday).

  (B-2) In the above embodiment, the type of each vehicle measured is not particularly considered. It is generally said that it is better to use a heavy vehicle to detect deterioration of a bridge or the like. Therefore, if it is possible to classify a small vehicle (for example, a general passenger car) and a large vehicle (for example, a large bus) at the time of measurement, the wireless device 10 (schedule determination unit 104) operates at a time when there is a high probability that a large vehicle will pass. It is desirable to set the time.

  For example, the wireless device 10 counts the number of small vehicles as it is, while counting large vehicles as X small vehicles. X is determined by how much importance is given to a large vehicle. Further, it may be changed according to attributes such as the weight of the vehicle.

  Further, among the heavy vehicles described above, there are vehicles that can be expected to travel on a fixed road at a fixed time. For example, a garbage collection vehicle, a route bus, a facility shuttle bus, and the like can be considered. The schedule determination unit 104 can determine the operation schedule efficiently by setting such a traffic schedule of the vehicle in advance and increasing the operation probability at the time.

  (B-3) In the above embodiment, the remaining amount of the power supply (for example, battery) of the wireless device 10 is not considered. In general, replacement operation of a battery-operated device is determined in advance, and the battery is often replaced at a fixed time regardless of the remaining battery level.

  In the wireless device 10 that continues measurement until a certain number of vehicles pass, if the operation time is predicted correctly, the battery consumption becomes smaller than expected. Therefore, the wireless device 10 may be configured to speculatively select the time and measure using the remaining battery capacity.

  (B-4) In the above embodiment, the number of wireless devices (the number of sensors) attached to the structure was not particularly considered. For example, there is a case where a plurality of sensors (wireless devices) are attached to the same structure. The purpose is to detect the deterioration of a plurality of parts having different progress of deterioration, or to simply provide system redundancy. When a plurality of sensor devices (wireless devices 10) can directly communicate with each other or communicate via the master device 20, the operation time of each sensor device (wireless device 10) is notified, and the other wireless devices 10 are notified. Can be configured to set its own operation time at a time when is not operating. By operating in this manner, it is possible to efficiently monitor the structure.

  (B-5) In the above embodiment, the example in which the structure monitoring device of the present invention is applied to the wireless device 10 has been described, but the structure monitoring device may be applied to a wired communication device.

  DESCRIPTION OF SYMBOLS 1 ... Data measurement system, 10 ... Wireless device, 20 ... Master device, 30 ... Monitoring device, 101 ... Communication unit, 102 ... Control unit, 103 ... Acceleration sensor, 104 ... Schedule determination unit, 105 ... Timer unit, 106 ... Clock , NT: backbone network, SN: sensor network.

Claims (10)

A structure monitoring device that monitors a structure through which a vehicle passes,
Measuring means for measuring the traffic situation of the vehicle at the measurement time;
Based on the traffic condition of the vehicle measured by the measuring means, the traffic frequency of the vehicle in each time zone is calculated, and the traffic frequency of the calculated vehicle and the traffic frequency of the past vehicle are estimated and the future traffic frequency is estimated and estimated. And a schedule determining unit that sets a time zone in which the frequency of vehicle traffic is the highest in the future traffic frequency as the next measurement time of the measuring device.   2. The structure monitoring apparatus according to claim 1, wherein the schedule determination unit sets a predetermined time provided from the outside as a next measurement time of the measurement unit.   3. The structure according to claim 1, wherein, as an initial stage, the measuring unit measures a traffic condition of the vehicle in all time zones using a cycle that is relatively simple to a cycle estimated for vehicle traffic. 4. Object monitoring device.   The structure monitoring apparatus according to any one of claims 1 to 3, wherein the past traffic frequency of the vehicle uses data acquired by another structure monitoring apparatus as an initial value.   The structure monitoring apparatus according to any one of claims 1 to 3, wherein the past traffic frequency of the vehicle uses data of regularly operated vehicles that periodically pass through the structure as an initial value.   The structure monitoring apparatus according to any one of claims 1 to 5, wherein the past vehicle traffic frequency is a vehicle traffic frequency in each time zone for each day of the week.   7. The structure according to claim 6, wherein the past traffic frequency is based on a predetermined calendar, and the traffic frequency of the vehicle measured by the measuring means on a holiday such as a holiday is data on Sunday. Monitoring device.   The structure monitoring device according to any one of claims 1 to 7, wherein the measuring unit counts the large vehicle as a plurality of small vehicles. A structure monitoring method used for a structure monitoring device that monitors a structure through which a vehicle passes,
Comprising measuring means and schedule determining means,
The measuring means measures the traffic condition of the vehicle at a measurement time,
The schedule determination means calculates the traffic frequency of the vehicle in each time zone based on the traffic condition of the vehicle measured by the measurement means, and calculates future traffic based on the calculated traffic frequency of the vehicle and the traffic frequency of the past vehicle. A structure monitoring method characterized by estimating a frequency, and setting a time zone in which the frequency of the vehicle is the highest among the estimated future traffic frequencies as a next measurement time of the measuring means. A computer mounted on a structure monitoring device that monitors a structure through which a vehicle passes,
Measuring means for measuring the traffic situation of the vehicle at the measurement time;
Based on the traffic condition of the vehicle measured by the measuring means, the traffic frequency of the vehicle in each time zone is calculated, and the traffic frequency of the calculated vehicle and the traffic frequency of the past vehicle are estimated and the future traffic frequency is estimated and estimated. A structure monitoring program which causes a time zone in which the frequency of vehicle traffic is highest among the future traffic frequencies described above to function as schedule determination means for setting a next measurement time of the measurement means.

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