JP7461798B2 - Equipment monitoring support device, method, and program - Google Patents

Description

The present invention relates to an equipment monitoring support device, method, and program for supporting the monitoring of changes in the status of equipment.

In order to monitor equipment, sensors that measure status information may be installed in the equipment.
In this case, simply analyzing the status information measured by the sensors on a sensor-by-sensor basis may not be enough to accurately capture changes in the status of the equipment.

As a technology related to equipment monitoring, for example, Patent Document 1 discloses a configuration for determining the degree of abnormality of an entire plant to be diagnosed based on the difference in spatial distance between data belonging to a category determined from data in normal times by adaptive resonance theory and the plurality of measurement data from various sensors installed in the plant to be diagnosed.Furthermore, for example, Patent Document 2 discloses an abnormality sign diagnosis device that diagnoses the presence or absence of an abnormality sign of mechanical equipment based on a normal model that indicates a normal range of operation information of the mechanical equipment, and discloses a configuration for diagnosing the presence or absence of an abnormality sign of the mechanical equipment based on a normal model associated with a group to which the sensor belongs and each detection value of the sensor corresponding to the normal model.
However, the techniques of Patent Documents 1 and 2 require category discrimination and normal models, which complicates the monitoring mechanism and raises concerns that the targets to which the techniques can be applied may be limited.

International Publication No. 2018/051568 Japanese Patent No. 6615963

The present invention was made in consideration of the above points, and aims to make it possible to easily and accurately capture changes in the condition of equipment.

The equipment monitoring support device of the present invention is an equipment monitoring support device for supporting monitoring of changes in the status of equipment, and includes an acquisition means for acquiring status information from sensors that measure status information installed at multiple locations of a target part included in the equipment, and an index calculation means for calculating an index a PE expressed by equation (1) using sensor identifiers i, j, the number N (N≧2) of installation locations of the sensors, the status information x _i , x _j measured by the sensors i, j, and time t based on the status _information at the multiple locations acquired by the acquisition means, wherein equation (1) is characterized in that the concept of spring potential energy is applied between data to expand to a state in which N samples (x ₁ , x ₂ , ..., x _N ) are connected to each other by a spring, and the sum of the potential energies is divided by the total number N ² of combinations as in equation (6) to obtain the average value.
In addition, the equipment monitoring support device of the present invention is an equipment monitoring support device for supporting monitoring of changes in the status of equipment, and is characterized in having an acquisition means for acquiring status information from sensors that measure status information installed at multiple locations of a target part included in the equipment, and an index calculation means for calculating an index a SD represented by equation (2) using an identifier i of the sensor, the number N (N≧2) of installation locations of the sensor, the status information x _i measured by the sensor i, the average value μ of the N pieces of status information, and time t, based on the status _information at the multiple locations acquired by the acquisition means.

The present invention makes it possible to easily and accurately detect changes in equipment conditions.

1 is a diagram illustrating a functional configuration of an equipment monitoring support device according to a first embodiment. FIG. 2 is a diagram for explaining an overview of a pressure roll which is an example of a target portion. FIG. 1 is a diagram for explaining potential energy of a spring. FIG. 1 is a conceptual diagram of potential energy between data. 11 is a characteristic diagram showing an example of a time series change of an index a _PE and a threshold value a _PEth . 13 is a characteristic diagram showing an example of the relationship between the number of data items and the index a _PE when the data set of performance values is arranged in descending order. FIG. 4 is a flowchart showing a process executed by the facility monitoring support device according to the first embodiment. FIG. 13 is a characteristic diagram showing an example of a time series change in the index a _SD and a threshold value a _SDth .

Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings.
[First embodiment]
First, with reference to FIG. 2, the equipment targeted in this embodiment and the target parts included in the equipment will be described.
In this embodiment, the target part is a pressure roll 201 included in equipment for straightening a steel plate. Fig. 2 is a diagram for explaining an overview of the pressure roll 201, (a) being a front view of the equipment including the pressure roll 201, and (b) being a side view showing the pressure roll 201 and a backup roll 202. The pressure roll 201 is a roll for pressing a steel plate being unwound from a pay-off reel (not shown), and both ends (work side (WS) and drive side (DS)) are supported by a support part 204 via bearings 203a and 203b. A backup roll 202 is installed on the back of the pressure roll 201.

Sensors 205a and 205b are installed on the bearings 203a and 203b at both ends of the pressure roll 201, which is the target part. The sensors 205a and 205b are, for example, wireless sensors that combine a sensor function and a wireless communication function, and can measure status information and transmit the measured value via wireless communication. In this embodiment, the sensors 205a and 205b measure the temperature as status information and transmit the measured value via wireless communication.

FIG. 1 shows a functional configuration of an equipment monitoring support device 100 according to an embodiment.
The equipment monitoring support device 100 includes an input unit 101 , a threshold setting unit 102 , an index calculation unit 103 , a comparison unit 104 , and a notification unit 105 .

The input unit 101 inputs and acquires temperature measurement values from each of the sensors 205a, 205b via wireless communication when the equipment is in operation. The input unit 101 acquires temperature measurement values from each of the sensors 205a, 205b, for example, at regular intervals (every time t) when the equipment is in operation. In this embodiment, the input unit 101 functions as the acquisition means referred to in the present invention.

The threshold setting unit 102 sets a threshold a _PEth for an index a _PE , which will be described later, based on a data set of actual temperature values measured by each sensor 205a, 205b during operation of the equipment during a predetermined period in the past. The predetermined period may be set appropriately depending on the operation status of the equipment, the type of the target part, etc., but may be, for example, about several months in order to prepare a data set including a large number of actual values. In this embodiment, the threshold setting unit 102 functions as a threshold setting means as referred to in the present invention.

The index calculation unit 103 calculates an index a _PE for monitoring a change in the state of the target part, which is expressed by the formula (1), based on the temperatures measured by the sensors 205a and 205b acquired by the input unit 101. i and j are identifiers of the sensors, N (N≧2) is the number of sensor installation locations (=the number of sensors), x _i and x _j are temperatures measured by the sensors i and j, and t is time. As shown in the formula (1), the index a _PE includes the sum of squares of the difference in temperature at two locations among the multiple locations where the sensors are installed. In this embodiment, the sensors 205a and 205b are installed on the bearings 203a and 203b at both ends of the pressure roll 201, and N=2. In this embodiment, the index calculation unit 103 functions as an index calculation means as referred to in the present invention.

The comparison unit 104 compares the index a _PE calculated by the index calculation unit 103 with a threshold a _PEth set in advance by the setting unit 102. In this embodiment, the comparison unit 104 functions as a comparison means according to the present invention.

When the index a _PE exceeds the threshold a _PEth as a result of the comparison by the comparison unit 104, the notification unit 105 issues a notification, for example, an alarm, regarding a change in the state of the target unit. In this embodiment, the notification unit 105 functions as a notification means as defined in the present invention.

The equipment monitoring support device 100 described above is configured, for example, by a computer device equipped with a CPU, ROM, RAM, etc., and the functions of each of the units 101 to 105 are realized by the CPU executing a specific program stored, for example, in the ROM.

Here, the index a _PE for monitoring the change in state of the target portion will be described.
The inventors of the present application have investigated an index a _PE that uses potential energy between data.
Fig. 3 is a diagram for explaining the potential energy of a spring, and Fig. 4 is a conceptual diagram of the potential energy between data.
As shown in FIG. 3, the potential energy PE of a spring is given by equation (3) where k is the spring constant and Δx is the extension of the spring from its natural length.
PE=k(Δx) ² /2 (3)

Let us consider applying this concept of spring potential energy to two sets of data. Let the spring constant be k = 1, and consider the spring extension Δx to be the difference between the sets of data. That is,
When two variables are x _A and x _B , Δx is expressed as in equation (4).
Δx = x _A - x _B ... (4)
In this case, the potential energy PE(x _A , x _B ) between the data of the two variables x _A and x _B is given by the formula (5).
PE( _xA , _xB )=( _xA - _xB ) ^2/2 ... (5)

While equation (5) shows the potential energy when two samples ( _xA , _xB ) are connected by a spring, this idea can be extended to a state in which N samples ( _x1 , _x2 , ..., _xN ) are connected to each other by springs, as shown in Figure 4, to find the average value of the potential energy. That is, as shown in equation (6), the sum of the potential energies is divided by the total number of combinations, ^N2, to find the average value.

According to this idea, the index calculation unit 103 calculates an index a _PE using the potential energy between data, expressed by formula (1). For temperatures (x ₁ (t), x ₂ (t), ..., x _N (t)) measured by N sensors at a certain time t, the temperature measured by sensor i is x _i , the temperature measured by sensor j is x _j , and the index a _PE is calculated by dividing the sum of the squares of the differences by 2N ² . As described above, formula (1) is an extension of formula (3) of the potential energy PE of a spring, and can be mechanically interpreted as the average value of the potential energy when N samples are connected to each other by springs. In other words, it calculates the average value of the potential energy of the differences between the temperatures.

When the equipment is in operation, the value of the index a _PE is relatively small and fluctuates little when the target part is in a stable state, but when the target part changes to an unstable state, the potential energy between the data becomes large and the index a _PE tends to become large. In this way, by calculating the index a _PE expressed by the formula (1) for each time t, it becomes possible to monitor the change in the state of the target part.
5 shows an example of a time series change in the index a _PE calculated by the index calculation unit 103 when the pressure roll 201 is the target part. The horizontal axis is time, the vertical axis is the index a _PE , and a characteristic line 501 represents the time series change in the index a _PE .

Next, the threshold a _PEth for the index a _PE will be described.
The threshold value a _PEth is set based on a data set of performance values of state information measured by sensors installed at multiple locations on the target part during operation of the equipment during a predetermined past period.
Specifically, the index _aPE calculated using a data set of actual values is sorted in descending order of value, and the value corresponding to a predetermined percentage (percentile) from the top is set as the threshold _aPEth . The threshold _aPEth is not used to judge an abnormality in the equipment, but to extract a change in the state of the target part, and the data set is composed of actual values during a period when the equipment can be said to be normal, in other words, during a period when no obvious abnormality occurs in the equipment.

For example, for a data set D=[X ⁽¹⁾ , X ⁽²⁾ , ..., X ^(L) ], an index _aPE is calculated for each actual value X ⁽⁾ , i.e., [ _aPE (X ⁽¹⁾ ), _aPE (X ⁽²⁾ ), ..., _aPE (X ^(L) )], and the indexes _aPE are arranged in descending order from the largest value. If the number L of actual values X ⁽⁾ is 2000, for example, the value of the index _aPE corresponding to the top 1% (1st percentile value) is the 20th largest value of the index aPE, specifically [ _aPE (X ⁽¹⁾ ), _aPE (X ⁽²⁾ ), ..., _aPE (X ^(L) )], and this value is set as the threshold _aPEth . The percentile may be set as appropriate, such as 1%, 3%, 5%, etc., depending on the type of target part and the type of status information.

6 shows an example of the relationship between the number of data items and the index a _PE when the data set of performance values in the case where the pressure roll 201 is the target part is arranged in descending order. As shown in FIG. 6, in the data set, the target part is in a stable state for most of the time when the equipment is in operation, and the value of the index a _PE is relatively small and its fluctuation is small. In addition, in the data set, although the number of data items is small, there are events in which the target part changes to an unstable state, and the value of the index a _PE may become relatively large.

In accordance with this concept, the threshold setting unit 102 sets the threshold a _PEth based on a data set of actual values of temperatures measured by the sensors 205a, 205b during operation of the equipment in a predetermined past period.
5 shows the threshold a _PEth set by the threshold setting unit 102 when the pressure roll 201 is the target part. A threshold 502 indicates a threshold a _PEth set to the 1st percentile value, a threshold 503 indicates a threshold a _PEth set to the 3rd percentile value, and a threshold 504 indicates a threshold a _PEth set to the 5th percentile value.

Fig. 7 is a flowchart showing the processing executed by the equipment monitoring support device 100. The equipment monitoring support device 100 repeatedly executes the processing of the flowchart in Fig. 7 at regular intervals (every time t) during the operation of the equipment. It is assumed that the threshold _aPEth has already been set by offline analysis.

In step S1, the input unit 101 inputs and acquires the temperature measurement values from each sensor 205a, 205b via wireless communication.

In step S2, the index calculation unit 103 calculates the index a _PE expressed by the above-mentioned formula (1) based on the temperatures measured by the sensors 205a and 205b acquired in step S1.

In step S3, the comparison unit 104 compares the index a _PE calculated in step S2 with a preset threshold a _PEth . If the comparison result shows that the index a _PE exceeds the threshold a _PEth , the process proceeds to step S4. If the index a _PE does not exceed the threshold a _PEth , the process ends.

In step S4, the notification unit 105 issues a notification, for example by issuing an alarm, regarding a change in the state of the target part.

When the equipment is in operation and the pressure roll 201 is in a stable state, the temperatures of the bearings 203a, 203b at both ends WS, DS are approximately the same, and the value of the index a _PE is relatively small and does not vary much. When this state changes to an unstable state due to, for example, a lack of oil in the bearings 203a, 203b, deterioration of the horizontality of the pressure roll 201, or damage to the bearings 203a, 203b, the potential energy between the data becomes large, and the index a _PE tends to become large.
When the temperature history of the bearings 203a, 203b at both ends WS, DS and the state of the pressure roll 201 was actually analyzed in an actual machine, it was confirmed that the index a _PE can be used to accurately grasp the state change. In this way, when the index a _PE exceeds the threshold a _PEth and a notification is received, for example, equipment maintenance such as lubrication, level adjustment, and replacement of the bearings 203a, 203b during a stoppage can be performed, which makes it possible to prevent troubles on the operation line before they occur, and is effective in maintaining productivity and quality.

As described above, simultaneous multipoint measurements are taken at multiple locations on the target part during operation of the equipment, and the index a _PE is calculated using the potential energy between the data.
By using the index a _PE using the potential energy between data in this manner, it becomes possible to detect online when the target part changes to an unstable state and accurately grasp the change in state of the target part.
The index a _PE includes the sum of squares of the difference in state information at two of the multiple locations, not at the sensor level, and is analyzed at the target unit level, allowing accurate capture of state changes at the target unit. For example, when measuring temperature with a sensor, the temperature measured by the sensor also includes the effects of changes in the environmental temperature. Therefore, analysis at the sensor level alone will be affected by changes in the environmental temperature. In contrast, the index a _PE includes the sum of squares of the difference in temperature at two of the multiple locations, making it possible to eliminate the effects of changes in the environmental temperature.
Furthermore, it is only necessary to monitor the index a _PE , and there is no need for category discrimination or normal models as in the techniques of Patent Documents 1 and 2. This makes the monitoring mechanism simple and does not limit the targets to which the invention can be applied.
As described above, it is possible to easily and accurately detect changes in the state of equipment.

In this embodiment, a pressure roll included in equipment for straightening steel plates has been described as the target part, but this is not limited to this, and for example, the target part may be equipment other than equipment for straightening steel plates, or other devices included in equipment for straightening steel plates.
Also, a facility may be divided into multiple sections, and multiple sensors may be installed in each section to monitor status changes simultaneously in the multiple sections. In this case, the same physical status information may be used for each section, and a threshold may be set for each section.
The number and positions of the sensors installed on the target part may be set appropriately depending on the type of the target part, the type of status information, etc. The status information measured by the sensors is not limited to temperature, but may be vibration, displacement, pressure, etc., and may be set appropriately depending on the type of the target part, etc.

In the present embodiment, the equipment monitoring support device 100 is described as having the threshold setting unit 102, but the present invention is not limited to this. For example, the threshold setting unit 102 may be configured as a device separate from the equipment monitoring support device 100, and the threshold a _PEth determined by the separate device may be input to the equipment monitoring support device 100. Also, the user may manually input the threshold a _PEth to the equipment monitoring support device 100.

In the present embodiment, the equipment monitoring support device 100 is configured to include the comparison unit 104 and the notification unit 105, but the present invention is not limited to this. For example, the equipment monitoring support device 100 may be configured to simply present the index a _PE calculated by the index calculation unit 103 to the user. The user can determine a change in the equipment status based on the presented index a _PE , so that simply presenting the index a _PE to the user can assist in monitoring the change in the equipment status.

Second Embodiment
The second embodiment is an example in which an index a _SD obtained by statistical analysis is used as an index for monitoring a change in the state of a target portion.
In the following, the description of the contents common to the first embodiment will be omitted, and the description will focus on the differences from the first embodiment. The functional configuration of the equipment monitoring support device 100 and the processing executed by the equipment monitoring support device 100 are basically the same as those described in the first embodiment, and the index a _PE and the threshold a _PEth are read as the index a _SD and the threshold a _SDth , respectively.

The index calculation unit 103 calculates an index a _SD for monitoring a change in the state of the target part, which is expressed by the formula (2), based on the temperatures measured by the sensors 205a and 205b input by the input unit 101. i is a sensor identifier, N (N≧2) is the number of sensor installation locations (=the number of sensors), x _i is the temperature measured by the sensor i, μ is the average value of N temperatures, and t is time. As shown in the formula (2), the index a _SD includes the difference between the temperature at one of the multiple locations where the sensors are installed and the average value of the temperatures at the multiple locations, that is, the sum of squares of the deviation. In this embodiment, the sensors 205a and 205b are installed on the bearings 203a and 203b at both ends of the pressure roll 201, and N=2.

As for the threshold value a _SDth for the index a _SD , similarly to the threshold value a _PEth in the first embodiment, the index a _SD calculated using the data set of actual values is sorted in descending order from the largest value, and the value corresponding to a predetermined percentage (percentile) from the top may be set as the threshold value a _SDth .

Here, by transforming the index a _PE , we obtain the formula (7), which can be interpreted as a _SD =√a _PE .

During operation of the equipment, when the target part is in a stable state, the value of the index a _SD is relatively small and its fluctuation is small, similar to the index a _PE , but when the target part changes to an unstable state, the index a _SD tends to become larger. In this way, by calculating the index a _SD expressed by the formula (2) at each time t, it becomes possible to monitor the change in the state of the target part.
8 shows an example of the time series change of the index _aSD and the threshold value _aSDth calculated by the index calculation unit 103 when the pressure roll 201 is the target part. The horizontal axis is time, the vertical axis is the index _aSD , and a characteristic line 801 represents the time series change of the index _aSD . Furthermore, a threshold value 802 represents the threshold value _aSDth set to the 1st percentile value, a threshold value 803 represents the threshold value _aSDth set to the 3rd percentile value, and a threshold value 804 represents the threshold value _aSDth set to the 5th percentile value.

As described above, simultaneous multipoint measurements were taken at multiple locations on the target part while the equipment was in operation, and the index a _SD , which satisfies the relationship a _SD =√a _PE , was calculated.
By using the index a _SD in this way, it becomes possible to detect online when the target part changes to an unstable state, and to accurately grasp the state change of the target part.
The index a _SD includes the sum of squares of deviations, not on a sensor basis, and is analyzed on a target part basis, allowing accurate capture of changes in the state of the target part. For example, when measuring temperature with a sensor, the temperature measured by the sensor is also affected by changes in the environmental temperature. Therefore, analysis on a sensor basis alone will be affected by changes in the environmental temperature. In contrast, the index a _SD includes the sum of squares of deviations, making it possible to eliminate the effects of changes in the environmental temperature.
Furthermore, it is only necessary to monitor the index a _SD , and there is no need for category discrimination or normal models as in the techniques of Patent Documents 1 and 2. This makes the monitoring mechanism simple and does not limit the targets to which the invention can be applied.
As described above, it is possible to easily and accurately detect changes in the state of equipment.

In addition, which of the index a _PE and the index a _SD to use may be appropriately selected depending on the type of the target part and the type of the status information. For example, since the index a _PE is in a square relationship with the index a _SD , it is possible to emphasize the time series change of the index a _PE compared to the time series change of the index a _SD . Therefore, when the time series change of the index a _PE appears relatively small, the index a _PE may be used.

Although the present invention has been described above with reference to the embodiments, the above embodiments are merely examples of the implementation of the present invention, and the technical scope of the present invention should not be interpreted as being limited by these. In other words, the present invention can be implemented in various forms without departing from its technical concept or main features.
The present invention is not limited to the equipment for straightening steel plates described in the embodiment, but can be widely applied to various types of equipment including mechanical elements.

100: Equipment monitoring support device, 101: Input unit, 102: Threshold setting unit, 103: Index calculation unit, 104: Comparison unit, 105: Notification unit, 201: Pressure roll, 205a, 205b: Sensors

Claims (10)

An equipment monitoring support device for supporting monitoring of changes in a state of an equipment,
An acquisition means for acquiring status information from sensors that are installed at multiple locations of a target part included in the equipment and measure the status information;
an index calculation means for calculating an index a PE expressed by formula (1) using identifiers i and j of the sensors, a number N (N≧2) of installation locations of the sensors, the status information x i and x j measured by the sensors i and j _, and _time t, based on the status information at the plurality of locations acquired by the _acquisition means ;
The equipment monitoring support device is characterized in that the above formula (1) applies the concept of spring potential energy between data, expanding it to a state in which N samples (x1, x2, ..., xN) are connected to each other by springs, and the sum of the potential energies is divided by the total number of combinations N2 to obtain the average value, as _shown in _formula ( ₆ ⁾ .

An equipment monitoring support device for supporting monitoring of changes in a state of an equipment,
An acquisition means for acquiring status information from sensors that are installed at multiple locations of a target part included in the equipment and measure the status information;
and an index calculation means for calculating an index a SD expressed by equation (2) using an identifier i of the sensor, a number N (N≧2) of installation locations of the sensor, the status information _{x i} measured by the sensor i, an average value μ of the N pieces of status information, and time t, based on the status information at the multiple locations acquired by the acquisition means.
A comparison means for comparing the index calculated by the index calculation means with a preset threshold value;
3. The facility monitoring support device according to claim 1 , further comprising a notification unit that issues a notification when the comparison result in the comparison unit indicates that the index exceeds the threshold value. The equipment monitoring support device according to claim 3, further comprising a threshold setting means for setting the threshold based on a data set of actual values of the status information measured by the sensors installed at the multiple locations during operation of the equipment during a specified period in the past. The equipment monitoring support device according to claim 4, characterized in that the threshold setting means sorts the indices calculated using the data set in order of decreasing value, and sets a value corresponding to a predetermined percentage from the top as the threshold. The equipment includes a roller serving as the target portion,
6. The facility monitoring support device according to claim 1, wherein the sensors are installed in bearings on both ends of the roller. 1. An equipment monitoring support method for supporting monitoring of a state change of an equipment, comprising:
An acquisition step of acquiring status information from sensors that measure status information and are installed at multiple locations of a target part included in the equipment;
and an index calculation step of calculating an index a PE expressed by formula (1) using identifiers i and j of the sensors, a number N (N≧2) of installation locations of the sensors, the status information x i and _x j _measured by the sensors i and j , and time t based on the status information at the plurality of _locations acquired in the acquisition step ,
The equipment monitoring support method is characterized in that the above formula (1) is expanded by applying the concept of spring potential energy between data, so that N samples (x1 _, x2 _, ..., xN ₎ are connected to each other by springs, and the sum of the potential energies is divided by the total number of combinations N2 to obtain an average value, as shown in formula (6 ⁾ .

1. An equipment monitoring support method for supporting monitoring of a state change of an equipment, comprising:
An acquisition step of acquiring status information from sensors that measure status information and are installed at multiple locations of a target part included in the equipment;
and an index calculation step of calculating an index a SD expressed by equation (2) using an identifier i of the sensor, the number N (N≧2) of installation locations of the sensor, the status information x _i measured by the sensor i, an average value μ of the N pieces of status information, and time t based on the status _information at the multiple locations acquired in the acquisition step.
A program for assisting in monitoring changes in the state of equipment,
An acquisition means for acquiring status information from sensors that are installed at multiple locations of a target part included in the equipment and measure the status information;
a computer is caused to function as an index calculation means for calculating an index a PE expressed by formula (1) using identifiers i and j of the sensors, the number N (N≧2) of installation locations of the sensors, the status information x _i and x _j measured by the sensors i and j, and time t based on the status information at the plurality of _locations acquired by the acquisition means ;
The program is characterized in that the above formula (1) applies the concept of spring potential energy between data, expanding it to a state in which N samples (x1 _, x2 _, ..., xN ₎ are connected to each other by springs, and the sum of the potential energies is divided by the total number of combinations N2 to obtain the average value, as shown in formula (6 ⁾ .

A program for assisting in monitoring changes in the state of equipment, comprising:
An acquisition means for acquiring status information from sensors that are installed at multiple locations of a target part included in the equipment and measure the status information;
A program for causing a computer to function as index calculation means for calculating an index a SD expressed by equation (2) using the identifier i of the sensor, the number N (N≧2) of installation locations of the sensor, the status information _{x i} measured by the sensor i, the average value μ of the N pieces of status information, and time t, based on the status information at the multiple locations acquired by the acquisition means.

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