JP6150545B2 - Data processing apparatus and program - Google Patents

Description

  The present invention relates to measurement value interpolation processing.

Building-related equipment management services install multiple sensors in building-related equipment and analyze time-series data acquired from each sensor for the purpose of energy and cost savings and asset value improvement.
In this analysis of time-series data, four arithmetic operations of multiple data and comparison of the calculation results are performed, but if the sampling period of multiple data is different in the process of this analysis, the value at an arbitrary timing is calculated. It is necessary to obtain by interpolation processing.

As a conventional technique related to such interpolation processing, an interpolator for estimating a signal value at an arbitrary time described in Patent Document 1 by interpolation processing, or an input sample string described in Patent Document 2 as an asynchronous output sample string Sampling frequency converters for conversion are known.
However, there are various types of sensors installed in building-related equipment, such as those that measure instantaneous values and those that measure the sum of values in a certain time width. None of them performed an interpolation process suitable for the type of data.

  Further, Patent Document 3 describes correction / interpolation processing using time series data and error factors, but refers to time series data different from the interpolation target in an arbitrary time width, and interpolation processing using this Did not do.

Japanese Patent No. 4249425 JP-A-5-235698 JP 2003-227048 A

On the other hand, a sensor installed in a building-related facility has a plurality of data types (measurement items), and some of these data types have a relationship.
For example, data can be acquired from two data types, a data type for measuring the total power consumption in a certain time span and a data type for measuring the operating state of the air conditioning, from sensors installed in the air conditioning equipment.
At this time, when the time series data of each data type is individually interpolated, the data value of the data type for measuring the driving state indicates 0 or off when comparing the interpolation processing results of the two data types at an arbitrary time. Nevertheless, a situation that cannot occur in reality, such as a data value of a data type for measuring power consumption showing a value of 0 or more, may be output as a result of interpolation processing.

  The present invention has been made in view of such circumstances, and a main object of the present invention is to obtain an interpolation result consistent with related measurement values.

The data processing apparatus according to the present invention
A determination unit that determines whether or not a related measurement item that is a related measurement item exists in an interpolation target measurement item that is a measurement item to be interpolated;
Interpolation target measurement value data input unit for inputting measurement value data indicating measurement values measured for the interpolation target measurement item as interpolation target measurement value data;
When the determination unit determines that a related measurement item exists in the interpolation target measurement item, measurement value data indicating a measurement value measured for the related measurement item of the interpolation target measurement item is displayed as a related measurement value. Related measurement data input part to input as data,
An interpolation processing unit that performs an interpolation process on the measurement value indicated in the interpolation target measurement value data using the measurement value indicated in the related measurement value data.

In the present invention, related measurement value data is input, and the measurement value indicated in the input related measurement value data is used to interpolate the measurement value indicated in the interpolation target measurement value data.
For this reason, it is possible to obtain an interpolation result that matches the measurement value of the related measurement value data for the measurement value of the interpolation target measurement value data.

1 is a block diagram illustrating a configuration example of a data processing device according to a first embodiment. FIG. 3 is a flowchart showing an operation procedure according to the first embodiment. It is a figure which shows an example of the correspondence table of the data classification memorize | stored in the data classification relationship memory | storage part which concerns on Embodiment 1, and relationship definition information. FIG. 10 illustrates an example of a correspondence table between combinations of data types and interpolation processing identifiers stored in a combination information storage unit according to the first embodiment. FIG. 7 illustrates an example of a correspondence table between an interpolation process identifier and interpolation process content stored in an interpolation process content storage unit according to Embodiment 1. FIG. It is a figure which shows an example of the correspondence table of the data classification memorize | stored in the corresponding | compatible information storage part which concerns on Embodiment 1, and an interpolation process identifier. FIG. 6 is a flowchart showing an operation procedure of interpolation processing by a combination of a state determination interpolation program and a linear interpolation program according to the first embodiment. It is a figure which shows the totaling process of the operation state with respect to the data of an operation state of the interpolation process by the combination of the state determination interpolation program and linear interpolation program which concern on Embodiment 1. FIG. It is a figure which shows the distribution process with respect to the data of power consumption of the interpolation process by the combination of the state determination interpolation program and linear interpolation program which concern on Embodiment 1. FIG. It is a figure which shows the linear interpolation process with respect to each data of the distributed power consumption of the interpolation process by the combination of the state determination interpolation program and linear interpolation program which concern on Embodiment 1. FIG. FIG. 10 is a flowchart showing an operation procedure according to the second embodiment. 6 is a diagram showing power consumption data according to Embodiment 1. FIG. It is a figure which shows the result of carrying out the linear interpolation of the power consumption which concerns on Embodiment 1 independently. 3 is a diagram illustrating a hardware configuration example of a data processing device according to Embodiments 1 and 2. FIG.

Embodiment 1 FIG.
In the present embodiment, an interpolation process for a measurement value acquired by a sensor or the like installed in a building-related facility will be described.
More specifically, by realizing an interpolation process that considers the relationship between a plurality of data types, there is a discrepancy between the result of the interpolation process of the measurement value to be analyzed at an arbitrary time and the related measurement value. A method for preventing the occurrence will be described.

  FIG. 1 is a block diagram illustrating a configuration example of the data processing device 1001 according to the first embodiment.

The data processing device 1001 receives the sensor data 1000 and records the interpolation processing execution result for the sensor data 1000 in the sensor data storage device 1010.
In the sensor data 1000, a measured value measured by a sensor or the like installed in a building-related facility is shown.
The sensor data 1000 corresponds to an example of measured value data.
In the following, the term measurement item is also used in the same meaning as the data type.

The data processing apparatus 1001 according to the present embodiment inputs sensor data 1000 indicating measurement values measured for measurement items that are targets of interpolation processing.
The sensor data 1000 indicating the measured values measured for the measurement item to be interpolated is an example of the interpolation target measured value data.
Hereinafter, the sensor data 1000 indicating the measurement value of the measurement item to be interpolated is referred to as sensor data 1000 to be interpolated.
The data processing apparatus 1001 determines whether or not there is a related measurement item (related measurement item) in the measurement item to be interpolated.
In addition, when a related measurement item exists in the measurement item to be interpolated, the data processing device 1001 inputs sensor data 1000 indicating a measured value measured for the related measurement item.
This sensor data 1000 is an example of related measurement value data.
Further, the data processing device 1001 performs an interpolation process on the measurement values of the sensor data 1000 to be interpolated using the measurement values indicated in the sensor data 1000 for the related measurement items.

The data processing device 1001 includes a data type relationship storage unit 1002, an interpolation processing unit 1003, a combination interpolation execution unit 1004, an interpolation library 1005, an interpolation processing content storage unit 1006, a correspondence information combination management unit 1007, a correspondence information storage unit 1008, and combination information. A storage unit 1009, an interpolation execution order specifying unit 1011, and a sensor data acquisition unit 1012 are provided.
Details of the interpolation execution order specifying unit 1011 will be described in the second embodiment.

The sensor data acquisition unit 1012 inputs sensor data 1000.
The sensor data acquisition unit 1012 corresponds to an example of an interpolation target measurement value data input unit and a related measurement value data input unit.

  The data type relationship storage unit 1002 stores relationship definition information between data types, and returns a list of related data types with the data type as an input.

The interpolation processing unit 1003 receives the sensor data 1000 to be interpolated and one or more data types as input, inquires the corresponding information combination management unit 1007 about the interpolation processing identifier, and interpolates the contents of the interpolation processing that matches the interpolation processing identifier. An inquiry is made to 1005 and the acquired interpolation processing content is executed for the sensor data 1000 to be interpolated.
The interpolation processing unit 1003 corresponds to an example of an interpolation processing unit and a determination unit.

  The combination interpolation execution unit 1004 is a part of the interpolation processing unit 1003, and a combination of a plurality of interpolation processing contents acquired from the interpolation library 1005 when the data type to be interpolated is related to other data types. Execute.

  The interpolation library 1005 receives one or more data types as input, acquires the corresponding interpolation processing content from the interpolation processing content storage unit 1006, and returns it to the interpolation processing unit 1003.

The interpolation processing content storage unit 1006 is a part of the interpolation library 1005 and stores the interpolation processing content corresponding to the data type.
The interpolation processing content storage unit 1006 corresponds to an example of a standard interpolation processing algorithm information storage unit together with a correspondence information storage unit 1008 described later.
The interpolation processing content storage unit 1006 corresponds to an example of an additional interpolation processing algorithm information storage unit together with a combination information storage unit 1009 described later.

  In response to the inquiry from the interpolation processing unit 1003, the correspondence information combination management unit 1007 sends an inquiry about the interpolation process identifier corresponding to the data type to be interpolated to the correspondence information storage unit 1008, and has a relationship with other data types. In the case of a certain data type, an inquiry is made to the combination information storage unit 1009 for an interpolation processing identifier corresponding to a combination of related data types.

The correspondence information storage unit 1008 stores an interpolation processing identifier that uniquely corresponds to one data type.
The correspondence information storage unit 1008 corresponds to an example of a standard interpolation processing algorithm information storage unit together with the interpolation processing content storage unit 1006 described above.

The combination information storage unit 1009 stores an interpolation processing identifier that uniquely corresponds to a combination of a plurality of related data types.
The combination information storage unit 1009 corresponds to an example of the additional interpolation processing algorithm information storage unit together with the interpolation processing content storage unit 1006 described above.

  Next, an operation procedure in the present embodiment will be described with reference to FIGS.

First, the sensor data acquisition unit 1012 acquires the sensor data 1000 to be interpolated, and the interpolation processing unit 1003 determines whether there is a data type relevant to the data type of the sensor data 1000 to be interpolated. An inquiry is made to the type relationship storage unit 1002 (S2001).
FIG. 3 shows an example of a correspondence table between data types and relationship definition information in the data type relationship storage unit 1002.
For example, when the data type of the sensor data 1000 to be interpolated is power consumption, the data type related to this data type is the operating state.
Strictly speaking, FIG. 3 means that a measured value of power consumption measured by the same building-related equipment (for example, air conditioning equipment) is related to a measured value of the operating state.
Based on the response from the data type relationship storage unit 1002, the interpolation processing unit 1003 determines whether there is a data type that is related to the data type of the sensor data 1000 to be interpolated.

If there is a related data type as a result of the inquiry in S2001 (YES in S2002), the interpolation processing unit 1003 first inputs a combination of related data types and inputs a corresponding interpolation processing identifier to the corresponding information combination management unit 1007. (S2003).
The correspondence information combination management unit 1007 acquires the interpolation processing identifier from the combination information storage unit 1009 and returns it to the interpolation processing unit 1003.
FIG. 4 shows an example of a correspondence table between combinations of data types and interpolation process identifiers in the combination information storage unit 1009.
For example, when the data type of the sensor data 1000 to be interpolated is power consumption and the related data type is an operating state, the interpolation process identifier is f_1.

The interpolation processing unit 1003 inquires of the interpolation library 1005 about the interpolation processing content corresponding to the interpolation processing identifier f_1 acquired in response to the inquiry of S2003 (S2004).
The interpolation library 1005 acquires the interpolation processing content from the interpolation processing content storage unit 1006 and returns it to the interpolation processing unit 1003.
FIG. 5 shows an example of a correspondence table between the interpolation process identifier and the interpolation process content in the interpolation process content storage unit 1006.
For example, when the interpolation process identifier to be targeted this time is f_1, the interpolation process content is a state determination interpolation program.
Each interpolation program described in the column of interpolation processing content in FIG. 5 is a program for realizing a predetermined interpolation processing algorithm.
Further, as will be described later, the state determination interpolation program is a program that is executed in addition to the linear interpolation program, and corresponds to a program that realizes an additional interpolation processing algorithm.

Similarly, in S2005 to S2006, the interpolation processing unit 1003 makes an inquiry about the data type of the sensor data 1000 to be interpolated to the corresponding information combination management unit 1007, and acquires the interpolation processing content from the interpolation library 1005.
At this time, the correspondence information combination management unit 1007 acquires an interpolation process identifier from the correspondence information storage unit 1008.
FIG. 6 shows an example of a correspondence table between data types and interpolation processing identifiers in the correspondence information storage unit 1008.
For example, when the data type of the sensor data 1000 to be interpolated is power consumption, the interpolation process identifier is f_3, and the content of the interpolation process is a linear interpolation program from FIG.
The linear interpolation program is defined as a standard interpolation program for the data type (power consumption) of the sensor data 1000 to be interpolated, and corresponds to a program for realizing a standard interpolation processing algorithm.

The interpolation processing unit 1003 and the combination interpolation execution unit 1004 execute the combination of the interpolation programs acquired in S2004 and S2006, and return an interpolation processing result (S2007).
Here, a case where the data type of the sensor data 1000 to be interpolated is power consumption will be described as an example.
From S2001 to S2005 described above, the interpolation processing content corresponding to the data type “power consumption” is a linear interpolation program, and the interpolation processing content corresponding to “power consumption × operating state” which is a combination of related data types is a state determination interpolation program. It is.
Here, the linear interpolation program realizes an interpolation processing algorithm for linearly interpolating between start point and end point data in an arbitrary time series section to obtain data (measurement value) at an arbitrary time.
In addition, the state determination interpolation program receives two pieces of data, stores a time series interval in which the value of the data representing the state is greater than 0, and distributes the value of the other data according to the ratio of the time series interval width. Implement interpolation processing algorithm.

  A specific operation procedure of S2007 will be described with reference to FIG. 7 to FIG. 10, FIG. 12, and FIG.

First, the interpolation processing unit 1003 acquires a power consumption sampling period (S7001).
This power consumption sampling period corresponds to an example of a first time width.
In the following description, the power consumption sampling period is 30 minutes.
In the following description, the measured value of the power consumption of the air conditioning equipment measured at 10:30 (the total power consumption in the time width of 10:01 to 10:30) will be described as an example.
FIG. 12 shows the measured value of power consumption measured at 10:30.

Next, the interpolation processing unit 1003 transmits the sensor data (hereinafter referred to as the operation state) of the operation state per minute measured by the building-related facility whose power consumption is shown in FIG. Are obtained over 30 minutes, which is the result of S7001 (S7002).
Note that one minute, which is a unit of measurement of the driving state data, corresponds to an example of the second time width.

In S7003, the interpolation processing unit 1003 counts the time zone indicating the operating state (the state where the air conditioning equipment is turned on) from the operation state data obtained every one minute acquired in S7002 (FIG. 8).
In the example of FIG. 8, the interpolation processing unit 1003 inputs driving state data in which the measured value of the driving state is shown in units of one minute for 30 minutes from 10:01 to 10:30, and driving every minute. From the status data, obtain the total result that the air conditioning equipment is in operation between 10:03 and 10:10 and that the air conditioning equipment is in operation between 10:15 and 10:20. Yes.

Next, the interpolation processing unit 1003 distributes the current power consumption sensor data (hereinafter referred to as power consumption data) in accordance with the time width ratio of the operating state based on the aggregation result of S7003 (S7004). , FIG. 9).
Assuming that the total power consumption shown in FIG. 12 is 120, the interpolation processing unit 1003 allocates 70 for 7 minutes of 10:03 to 10:10, and 50 for 5 minutes of 10:15 to 10:20. Assign.

  Next, the interpolation processing unit 1003 performs linear interpolation on each piece of power consumption data distributed in S7004 to obtain an interpolation result (S7005, FIG. 10).

  Then, the interpolation processing unit 1003 repeatedly executes S7002 to S7005 while shifting the entire power consumption data to be interpolated for each power consumption sampling period, thereby completing the interpolation processing (S7006).

  Note that the processing of S7002 to S7004 is processing by the state determination interpolation program, and the processing of S7005 is processing by the linear interpolation program.

When the linear interpolation process is performed only with the power consumption data without collating with the operation state data, the interpolation process result shown in FIG. 13 is obtained, and the air conditioning equipment is not operating 10:01 to 10:02. Between 10:11 and 10:14, electric power is consumed even between 10:21 and 10:30, resulting in inconsistency with the data of the operation state.
On the other hand, in the interpolation processing result of FIG. 10, since the power consumption data is interpolated after collating with the operation state data, there is a match between the power consumption data and the operation state data. It is taken.

  In FIG. 2, if NO is obtained in S2002, that is, if there is no data type related to the data type to be interpolated, the interpolation processing unit 1003 inquires the correspondence information storage unit 1008 and corresponds to the data type. The content of the interpolation process is acquired from the interpolation library 1005, and the interpolation process is executed (S2008 to S2010).

The above is the description of the operation of the data processing apparatus according to the first embodiment.
In the present embodiment, the data type is the power consumption, the related data type is the operation state, and the interpolation processing content corresponding to the combination of the power consumption × the operation state data type corresponds to the state determination interpolation program and the power consumption data type. The case where the interpolation processing content is a linear interpolation program has been described as an example.
However, the data type and the related data type can be arbitrarily set according to the application system, and the interpolation processing content corresponding to each data type and combination can be set by the user according to the meaning of the data.
In the present embodiment, an example is shown in which the processing of S7002 to S7004 in FIG. 7 is performed by the state determination interpolation program and the processing of S7005 is performed by the linear interpolation program. Is possible.

The interpolation processing unit 1003 and the combination interpolation execution unit 1004 provide a framework of the operation flow in S7001 and S7006, and execute each user-defined interpolation program for each sampling period of the data type to be interpolated.
Thus, when the combination interpolation execution unit 1004 executes an interpolation program corresponding to a combination of data types, another interpolation program corresponding to each data type in the interpolation program is called by using the data type as a key. Even when the correspondence between each data type and the interpolation program is changed, it is not necessary to change the contents of the interpolation program corresponding to the combination of the data types.

In this embodiment, an example in which there is one data type related to the data type to be interpolated has been described. However, there may be two or more data types related to the data type to be interpolated.
When there are two or more related data types, the interpolation processing unit 1003 performs interpolation processing of the sensor data 1000 of the data type to be interpolated using each of the sensor data 1000 of two or more data types.

In the above description, the example in which the sensor data acquisition unit 1012 acquires the sensor data 1000 to be interpolated at the stage of S2001 in FIG. 2 has been described. However, the acquisition timing of the sensor data 1000 to be interpolated may be another timing. .
For example, the sensor data 1000 to be interpolated may be acquired at the timing of S7001 in S2007.

Embodiment 2. FIG.
In this embodiment, the interpolation execution order specifying unit 1011 will be described.
The interpolation execution order specifying unit 1011 acquires a data type related to the data type to be interpolated from the data type relationship storage unit 1002, and notifies the interpolation processing unit 1003 of the execution priority of the interpolation program.

  FIG. 11 is a flowchart showing the operation procedure of the second embodiment.

Since S11001 to S11002 are the same as S2001 to S2002 of the first embodiment, description thereof is omitted.
In step S11003, the interpolation execution order specifying unit 1011 determines the priority order of the interpolation processing and notifies the interpolation processing unit 1003 so as to preferentially execute the interpolation for the related data type.
Steps S11004 to S11007 are the same as steps S2003 to S2006 of the first embodiment, and a description thereof is omitted.
In step S11008, the interpolation processing unit 1003 executes the interpolation processing according to the priority order in step S11003.
As an example, when the power consumption in FIG. 3 is the data type to be interpolated, the relational data type is the operating state, and an interpolation process (in this example, a state determination interpolation program) is performed on the time series data of the operating state. .
Steps S11009 to S11012 are the same as steps S2007 to S2010 in the first embodiment, and a description thereof is omitted.

The above is the description of the operation of the data processing apparatus according to the second embodiment.
In the second embodiment, the case where the data type is power consumption and the related data type is the operation state has been described as an example. However, the data type and the related data type can be arbitrarily set according to the application system, A case where there are a plurality of related data types or a nested state where another related data type exists in the interpolation processing of the related data types can be similarly handled.

As described above, in the first embodiment and the second embodiment,
In managing time series data of different types acquired in buildings, such as buildings,
An apparatus that performs interpolation processing for missing values in time series data of a certain data type,
"Data type relationship storage unit" that stores information defining the relationship between data types,
An “interpolation execution order determination unit” that determines a data type to be interpolated preferentially from the relationship definition information held in the data type relationship storage unit;
“Combination information storage unit” for storing combination information uniquely determined from combinations of data types;
A “corresponding information combination management unit” that acquires two or more pieces of correspondence information and the one piece of combination information from the relationship definition information held in the data type relationship storage unit;
Based on two or more pieces of correspondence information acquired from the correspondence information combination management unit and one piece of combination information, an interpolation process in which one or more interpolation programs are called from an interpolation library and a plurality of time-series data is input. It has a `` combination interpolation execution part '' to execute,
A data processing apparatus has been described that performs appropriate interpolation on missing values based on relationship definition information between data types.

  In addition, the data type relationship storage unit receives one or more arbitrary data types, and one or more time series data of other data types that need to be referred to when performing interpolation processing of time series data of this data type It has been explained that the data type is specified when it exists.

  In addition, the interpolation execution order designating unit repeatedly inputs the relation data type acquired from the data type relation storage unit as an input to the data type relation storage unit, thereby executing interpolation processing for each data type that requires interpolation processing. It explained that the priority order was specified.

  In addition, the combination information storage unit and the correspondence information combination management unit input an interpolation target data type and one or more data types related thereto, and correspond to an interpolation program corresponding to each data type and a combination thereof. It explained that the interpolation program to be decided uniquely.

  Further, the combination interpolation execution unit acquires an interpolation program based on information from the correspondence information combination management unit, and the corresponding interpolation program according to the interpolation execution priority order of each data type from the interpolation execution order determination unit As described above, the interpolation processing result for the time series data of each data type is acquired by sequentially executing the above.

  Further, in the interpolation program corresponding to the combination of data types, the combination interpolation execution unit calls the related data type instead of the interpolation program as a key when calling the interpolation program corresponding to the data type related to the interpolation target. explained.

Finally, a hardware configuration example of the data processing apparatus 1001 shown in the first and second embodiments will be described with reference to FIG.
The data processing device 1001 is a computer, and each element of the data processing device 1001 can be realized by a program.
As a hardware configuration of the data processing device 1001, an arithmetic device 901, an external storage device 902, a main storage device 903, a communication device 904, and an input / output device 905 are connected to a bus.

The arithmetic device 901 is a CPU (Central Processing Unit) that executes a program.
The external storage device 902 is, for example, a ROM (Read Only Memory), a flash memory, or a hard disk device.
The main storage device 903 is a RAM (Random Access Memory).
The “to storage unit” described in the first and second embodiments is realized by the external storage device 902 or the main storage device 903.
The communication device 904 is, for example, a NIC (Network Interface Card), and receives the sensor data 1000.
The input / output device 905 is, for example, a mouse, a keyboard, a display device, or the like.

The program is normally stored in the external storage device 902, and is loaded into the main storage device 903 and sequentially read into the arithmetic device 901 and executed.
The program is a program that realizes a function described as “˜unit” (excluding “˜storage unit”, the same applies hereinafter) shown in FIG.
Further, an operating system (OS) is also stored in the external storage device 902. At least a part of the OS is loaded into the main storage device 903. ”Is executed.
In the description of the first and second embodiments, “determining”, “determining”, “interpolating process”, “matching”, “specifying”, “input of”, “ Information, data, signal values, and variable values indicating the results of the processing described as “acquisition of” are stored in the main storage device 903 as files.
Further, the encryption key / decryption key, random number value, and parameter may be stored in the main storage device 903 as a file.

  14 is merely an example of the hardware configuration of the data processing apparatus 1001, and the hardware configuration of the data processing apparatus 1001 is not limited to the configuration illustrated in FIG. Also good.

  1000 sensor data, 1001 data processing device, 1002 data type relationship storage unit, 1003 interpolation processing unit, 1004 combination interpolation execution unit, 1005 interpolation library, 1006 interpolation processing content storage unit, 1007 correspondence information combination management unit, 1008 correspondence information storage unit , 1009 Combination information storage unit, 1010 Sensor data storage device, 1011 Interpolation execution order designation unit, 1012 Sensor data acquisition unit.

Claims (6)

A determination unit that determines whether or not a related measurement item that is a related measurement item exists in an interpolation target measurement item that is a measurement item to be interpolated;
Interpolation target measurement value data input unit for inputting measurement value data indicating measurement values measured for the interpolation target measurement item as interpolation target measurement value data;
When the determination unit determines that a related measurement item exists in the interpolation target measurement item, measurement value data indicating a measurement value measured for the related measurement item of the interpolation target measurement item is displayed as a related measurement value. Related measurement data input part to input as data,
Using the measurement values shown in the related measurement value data, an interpolation processing unit that performs an interpolation process of the measurement values shown in the interpolation target measurement value data ;
For each measurement item, a standard interpolation processing algorithm information storage unit that stores standard interpolation processing algorithm information in which a standard interpolation processing algorithm that is a standard interpolation processing algorithm is defined;
Interpolation processing that is executed in addition to the standard interpolation processing algorithm when the measurement value indicated in the related measurement value data is used for the interpolation processing for each combination of the measurement item having the related measurement item and the related measurement item. An additional interpolation processing algorithm information storage unit that stores additional interpolation processing algorithm information in which the algorithm is defined as an additional interpolation processing algorithm;
An interpolation execution order designating unit for designating an execution order of the additional interpolation processing algorithm and the standard interpolation processing algorithm;
The interpolation processing unit
According to the execution order specified by the interpolation execution order specifying unit, using the measurement value indicated in the related measurement value data, for the combination of the measurement item to be interpolated and the related measurement item in the additional interpolation processing algorithm information The additional interpolation processing algorithm defined in the standard interpolation processing algorithm information and the standard interpolation processing algorithm defined for the interpolation target measurement item in the standard interpolation processing algorithm information are executed and indicated in the interpolation target measurement value data. A data processing apparatus that performs interpolation processing of measured values . The measurement value data input unit is
Input measurement value data indicating at least the first time width as a measurement value measured in units of a first time width that is a predetermined time width as the interpolation target measurement value data;
The related measurement value data input unit is:
A measurement value measured in units of a second time width that is a time width that is 1 / n (n is an arbitrary number greater than or equal to 2) times the first time width, for each second time width, Input at least measurement value data indicated by the first time width as the related measurement value data,
The interpolation processing unit
Interpolating the measurement value indicated in the interpolation target measurement value data by collating the measurement value indicated in the interpolation target measurement value data with the measurement value for each second time width indicated in the related measurement value data The data processing apparatus according to claim 1, wherein the processing is performed. The interpolation processing unit
The data processing apparatus according to claim 1, characterized in that executing the program for implementing the standard interpolation algorithms, and a program for implementing the additional interpolation algorithm. The interpolation processing unit
When calling the program that realizes the standard interpolation processing algorithm, the program is called using the measurement item to be interpolated instead of the program name,
4. The program according to claim 3 , wherein when the program that realizes the additional interpolation processing algorithm is called, the program is called using not the program name but a combination of the measurement item to be interpolated and the related measurement item as a key. Data processing device. The related measurement value data input unit is:
When the determination unit determines that two or more related measurement items exist in the interpolation target measurement item, the related measurement value data is input for each of the two or more related measurement items,
The interpolation processing unit
Using the measurement values shown in the relevant measurement data, the data processing apparatus according to any one of claims 1 to 4, characterized in that performs interpolation processing of the measurement values shown in the interpolation target measurement data.   A program causing a computer to function as the data processing apparatus according to claim 1.

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