WO2016098805A1 - データ関連情報処理装置及びプログラム - Google Patents

データ関連情報処理装置及びプログラム Download PDF

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WO2016098805A1
WO2016098805A1 PCT/JP2015/085191 JP2015085191W WO2016098805A1 WO 2016098805 A1 WO2016098805 A1 WO 2016098805A1 JP 2015085191 W JP2015085191 W JP 2015085191W WO 2016098805 A1 WO2016098805 A1 WO 2016098805A1
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data
related information
parameter list
parameter
output
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PCT/JP2015/085191
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English (en)
French (fr)
Japanese (ja)
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剛維 木村
米山　純一
北上　眞二
誠 今村
隆彦 増▲崎▼
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三菱電機株式会社
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/16—Real estate

Definitions

  • the present invention relates to a data-related information processing apparatus and program for processing data-related information used for analyzing data related to equipment.
  • a provider of a monitoring service such as a building or a plant monitors equipment by acquiring data related to the equipment periodically or each time.
  • the data to be acquired when the device to be monitored is an air conditioner, for example, there are measured values and set values measured by various sensors such as a set temperature, an actually measured temperature, an air condition, a voltage value, a current value, and a pressure value.
  • Acquired data can range from thousands to tens of thousands depending on the size of the building.
  • Each data is given a data name for identification and stored.
  • the data name given to the output data of various sensors includes, for example, a term indicating the installation location of the device, a term indicating the type of data, a term indicating the type of device, and the like.
  • the service provider of the monitoring service is not limited to just monitoring the device, but is conducting diagnosis of the device and analysis for energy saving based on the acquired data based on the support contract.
  • the analysis identifies the type of equipment to be analyzed, the installation location, etc., extracts the data corresponding to the specified model, etc. from the accumulated data, and specially analyzes the extracted data Done with tools. In order to perform analysis using the analysis tool, it is necessary to generate input parameters to the analysis tool.
  • information indicating the installation location of the device and the type (equipment name) of the device by analyzing the notation of the data name, and the item of the data (signal name)
  • Information property name
  • data related information including the information and data name is generated in advance.
  • the data name may be expressed as “temperature” or may be expressed as “Temp”.
  • An object of the present invention is to select data-related information candidates to be set for input parameters that could not be identified by referring to output data of the sensor.
  • the data related information processing apparatus includes an installation location term indicating an installation location of a device to be detected by the sensor, an equipment type term indicating the type of the device, and an output type term indicating the type of output data of the sensor.
  • Data-related information generated for each output value based on data name information associated with output data of each of a plurality of sensors, and device-specific terms including installation location terms and device type terms
  • acquisition means for acquiring a plurality of data related information used for extracting output data of the sensor to be analyzed from among the data related information each including the output type term as an item value, and the acquisition means From the acquired data-related information, input to the device analysis tool according to a predetermined parameter list generation rule.
  • Selects data-related information to be set for each of a plurality of parameters for each device generates a parameter list including identification information of the selected data-related information for each device, and a parameter list generated by the generating unit If the data related information is not selected for all the parameters to be included in the data, the data related information to be selected as the parameter for which the data related information is not selected is the data related information of the output data of each sensor.
  • Selection means for selecting according to the degree of fitness as a parameter for which information was not selected and complement processing means for complementing the parameter list with the data related information selected by the selection means.
  • a data characteristic rule storage unit that stores a data characteristic rule that defines a characteristic of output data of the sensor to be set as the parameter
  • the selection unit includes the data characteristic rule of the output data of each sensor
  • the degree of matching is calculated as the degree of matching, the top predetermined number of data related information having a high degree of matching is selected, and the complement processing means is selected by the user from the data related information selected by the selecting means.
  • the data-related information supplements the parameter list.
  • the data characteristic rule defines at least one of a rule indicating characteristics of output data of each sensor and a rule indicating relation between output data of the sensors.
  • the data processing apparatus has correction / complementation processing means for performing correction / complementation processing on the data related information acquired by the acquisition means.
  • the program according to the present invention includes an installation location term indicating the installation location of a device to be detected by the sensor, a device type term indicating the type of the device, and an output type term indicating the type of output data of the sensor.
  • Data-related information generated for each output value based on data name information associated with output data of each of a plurality of sensors, including device-specific terms including installation location terms and device type terms
  • An acquisition means for acquiring a plurality of data related information used for extracting output data of a sensor to be analyzed among data related information each including an output type term as an item value, acquired by the acquisition means Input to the device analysis tool according to a predetermined parameter list generation rule 1
  • data-related information to be set for each of a plurality of parameters is selected for each device, and a parameter list including identification information for the selected data-related information is generated for each device, a parameter list generated by the generator If the data related information is not selected for all the parameters to be included, the data related information to be selected as the parameter for which the data related information
  • data-related information to be set as an input parameter to the analysis tool is specified based on a term that specifies the installation location and type of equipment from a group of data-related information or a term that specifies a signal name of data. If it is not possible, by referring to the output data of the sensor, it is possible to select data related information candidates to be set for the input parameters that could not be specified.
  • the user can correct / complement data related information including incorrect notation.
  • FIG. 1 is an overall configuration diagram of a data analysis system having an embodiment of a data-related information processing apparatus according to the present invention. It is a hardware block diagram of the computer which forms the data related information processing apparatus in this Embodiment. It is a block block diagram of the data related information processing apparatus in this Embodiment. It is the figure which showed the data setting example of the data relevant information in this Embodiment. It is the flowchart which showed the parameter list production
  • FIG. 1 is an overall configuration diagram of a data analysis system having an embodiment of a data related information processing apparatus according to the present invention.
  • the data analysis system in the present embodiment acquires data related to various devices such as air conditioners, lighting, and substation equipment installed in the building 1, and extracts data to be analyzed based on the data names given to the data Then, analysis and diagnosis are performed based on the extracted data.
  • various devices such as air conditioners, lighting, and substation equipment installed in the building 1
  • analysis and diagnosis are performed based on the extracted data.
  • FIG. 1 data from a plurality of buildings 1 may be acquired for analysis, diagnosis, or the like.
  • Building 1 is, for example, an office building or a plant.
  • Various devices that detect various data are attached to the devices installed in the building 1, and data output by the sensors is transmitted to the data collection device 3 via the network 2.
  • Each data is associated with a data name for identifying the data. This data name is created by the user of the building 1, for example.
  • the data management system 4 is formed by one or a plurality of computers. Each storage unit 41, 42 is realized by one or a plurality of hard disk drives (HDDs) mounted on a computer.
  • HDDs hard disk drives
  • the data related information generation device 5 extracts a set of data names (analysis target data name set) assigned to each data to be analyzed from the data name list stored in the data management system 4. Further, the data-related information generation device 5 analyzes each data name included in the extracted analysis target data name set to identify the type and installation location of the device from which the data was acquired, the signal name of the data, and the like. Then, data-related information is generated using the identified information as data items. Then, a set of data related information (data related information group) is generated by grouping the generated data related information in the analysis target data name set.
  • the analysis target data name set may be generated using, for example, a patent application filed by the same patent applicant as the present application (a data name extraction device or a program described in Japanese Patent Application No. 2013-094260).
  • the data extraction device 6 extracts data to which data names included in the data related information (group) sent from the data related information processing device 10 are assigned from the data storage unit 41 as analysis target data.
  • the analysis device 7 performs analysis, diagnosis, and the like of the analysis target device based on the analysis target data.
  • the analysis device 7 performs analysis of devices using various analysis tools, and each analysis tool inputs a data ID for specifying data-related information as a parameter, such as the abnormality detection engine illustrated in FIG. Is done.
  • the notation such as the type of device included in the data related information specifically the entity name and property name included in the data related information may fluctuate depending on the data name.
  • the data ID of the data related information set as the input parameter to the analysis tool cannot be correctly extracted from the data related information group.
  • the data storage unit By referring to the output data of the sensor stored in 41, data-related information candidates to be set as input parameters that could not be specified can be selected.
  • each of the devices 5 to 7 and 10 is configured by a plurality of devices. May be.
  • FIG. 2 is a hardware configuration diagram of a computer forming the data related information processing apparatus 10 according to the present embodiment.
  • the computer forming the data-related information processing apparatus 10 can be realized by a general-purpose hardware configuration that has existed in the past. That is, as shown in FIG. 2, the computer is provided as a CPU 51, ROM 52, RAM 53, HDD controller 55 connected with a hard disk drive (HDD) 54, a mouse 56 and keyboard 57 provided as input means, and a display device.
  • An input / output controller 59 for connecting each of the displays 58 and a network controller 60 provided as communication means and used for data communication between at least the data related information generation device 5 and the data extraction device 6 are connected to the internal bus 61. Configured.
  • FIG. 3 is a block configuration diagram of the data-related information processing apparatus 10 in the present embodiment.
  • the data related information processing apparatus 10 includes a data related information acquisition unit 11, an entity name conversion unit 12, a property name conversion unit 13, a parameter list generation unit 14, a parameter list supplement processing unit 15, a correction / complement processing unit. 16, a data related information output unit 17, a control unit 18, a data related information storage unit 21, a generation rule storage unit 22, a parameter list storage unit 23, and a data characteristic rule storage unit 24.
  • the data related information acquisition unit 11 is provided as an acquisition unit, and acquires a plurality of data related information used for extracting the output data of the sensor to be analyzed as a set from the data related information generation device 5.
  • the information is stored by registering in the information storage unit 21.
  • the entity name conversion unit 12 refers to a dictionary (not shown) and corrects an entity name that needs to be corrected among the plurality of data related information acquired by the data related information acquisition unit 11.
  • the property name conversion unit 13 refers to a dictionary (not shown) and corrects a property name that needs to be corrected among the plurality of data related information acquired by the data related information acquisition unit 11.
  • the parameter list generation unit 14 is provided as a generation unit, and one or a plurality of parameters are input to the device analysis tool according to a predetermined parameter list generation rule from the data related information group acquired by the data related information acquisition unit 11. Data related information set for each parameter is selected for each device, and a parameter list including identification information of the selected data related information is generated for each device.
  • the parameter list complement processing unit 15 in the present embodiment functions as a selection unit and a complement processing unit. That is, the parameter list complement processing unit 15 does not select the data related information when the data related information is not selected for all the parameters to be included in the parameter list generated by the parameter list generating unit 14. Data-related information to be selected as a parameter is selected according to the degree of fitness of the output data of each sensor as a parameter for which data-related information has not been selected, and the parameter list is complemented with the selected data-related information.
  • the correction / complementation processing unit 16 is provided as a correction / complementation processing unit, and performs correction / complementation processing on the data related information acquired by the data related information acquisition unit 11.
  • the data related information output unit 17 outputs the data related information corrected by the entity name conversion unit 12 and the property name conversion unit 13 as necessary and the parameter list supplemented by the parameter list supplement processing unit 15 as necessary to the data extraction device 6. To do.
  • the control unit 18 operates in cooperation with the constituent elements 11 to 17 and performs overall control of processing performed in the data related information processing apparatus 10.
  • the data related information storage unit 21 stores data related information acquired by the data related information acquisition unit 11 and targeted for correction / complementation in the data related information processing apparatus 10.
  • the data related information in the present embodiment will be described with reference to FIG.
  • the data related information is generated for each output data of the sensor.
  • FIG. 4 shows data related information (data related information group) for 8 data.
  • a data ID for identifying each data is given to the data related information.
  • items such as a type name, a data name, an entity name, and a property name are set in association with the data ID.
  • output data from a sensor is classified into a plurality of types according to the type, and the type name is signal type information indicating a signal type to which an output signal from the sensor belongs.
  • the data name is a name given to output data from the sensor.In this embodiment, according to a predetermined naming rule, an installation location term indicating the installation location of the device to be detected by the sensor, and the type of the device are used.
  • the entity name includes a device identification term including an installation location term and a device type term extracted from the data name by being analyzed by the data related information generation device 5.
  • the property name includes an output type term extracted from the data name by being analyzed by the data-related information generation device 5.
  • the data ID in the present embodiment includes a controller identification code for identifying a controller that controls the operation of the device, a signal type code indicating the type of an output signal from the sensor, and a serial number assigned to each data related information. And are generated as a pair.
  • the one set of data related information is information corresponding to data acquired from a sensor corresponding to a device connected to the controller identification codes “0101” and “0102”. .
  • the property name is a signal name given to the output signal from the sensor, and is classified according to the type of signal (signal type code) represented by “AI” or the like, and the signal name represented by “measurement” or the like. Classified by type (type name).
  • the signal type code and type name classify property names (signal names) according to different classification criteria even in the information indicating the same signal type.
  • the data (output signal) corresponding to the data-related information 31 is data output from a sensor that measures the temperature of the air supply (SA) of an air conditioner installed in B1F (first basement). Show.
  • the data corresponding to the data related information 31 is signal data indicating the type from the property name “SA temperature” to the supply air temperature.
  • this data is data classified into a group of signals input as analog signals from “AI” according to the classification criteria in the data ID, and at the same time obtained from measurement from “measurement” according to the classification criteria in the type name. It can be seen that the data is classified into a group called data.
  • Each component 11 to 18 in the data-related information processing apparatus 10 is realized by a cooperative operation of a computer that forms the data-related information processing apparatus 10 and a program that operates on the CPU 51 mounted on the computer.
  • each of the storage units 21 to 24 is realized by an HDD 54 mounted on the data related information processing apparatus 10.
  • the RAM 53 or an external storage means may be used via a network.
  • the program used in this embodiment can be provided not only by communication means but also by storing it in a computer-readable recording medium such as a CD-ROM or USB memory.
  • the program provided from the communication means or the recording medium is installed in the computer, and various processes are realized by the 51 CPU of the computer sequentially executing the program.
  • the data related information acquiring unit 11 acquires it and stores the data related information. Register in the unit 21 (step 101).
  • the entity name conversion unit 12 When one set of data related information is acquired, the entity name conversion unit 12 reads all the data related information included in the set from the data related information storage unit 21 and is included in each data related information. Extract the entity name. Then, if there is a duplicate entity name in the extracted entity name, the entity name conversion unit 12 deletes the duplicate entity name, or refers to a dictionary (not shown), and the entity name with the notation in the notation Or change. Similarly, the property name conversion unit 13 refers to the dictionary and changes the property name whose notation is shaken.
  • FIG. 6 is a diagram showing a standard scenario pattern preliminarily defined as a rule for generating a parameter list (parameter list generation rule) stored in the generation rule storage unit 22.
  • the parameter list generator 14 generates a parameter list as shown in FIG. 7 from the data related information according to the standard scenario pattern illustrated in FIG. 6 (step 102).
  • the parameter list generation unit 14 extracts the entity name from the data related information stored in the data related information storage unit 21 according to the setting of the entity (scenario name) in the standard scenario pattern, and sets it as the scenario name of the parameter list.
  • scenario name the entity name of “B1F system air conditioner” and “3F system air conditioner” are extracted from the data related information, and the extracted entity names are used as scenario names “B1F system air conditioner”. "Scenario” and "3F system air conditioner scenario” are set.
  • B1F system air conditioner is described as an example.
  • the property name is “SA” in “B1F system air conditioner scenario” (entity name is “B1F system air conditioner”).
  • the data related information of “temperature” or “air supply temperature” is specified, and the data ID “0101_AI — 0000001” of the specified data related information is set to parameter 1 in the parameter list.
  • the data related information whose property name is “SA temperature setting” or “supply air temperature setting” in “B1F system air conditioner scenario” is specified, and the specified data related information Data ID “0101_AV_0000002” is set in parameter 2 in the parameter list.
  • the same processing is performed for parameter 3 and parameter 4 to set the corresponding data ID for each parameter. If the data-related information is correctly generated, only “SA temperature” or “supply air temperature” is set in the data-related information, and “SA temperature setting” or “supply air temperature setting” is set. Only one of "" is set in the data related information.
  • the parameter list shown in FIG. 7 is generated by setting the parameter list for “3F system air conditioner” by performing the same processing.
  • the parameter list is generated based on the entity name and property name. If the entity name and property name included in the data related information are set correctly, all parameters are set for each scenario as shown in FIG. 7 (Y in step 103), so the parameter list is generated correctly. It is judged that
  • the data related information output unit 17 reads a plurality of data related information (data related information group) to be processed from the data related information storage unit 21, and stores the read data related information group and the data related information group.
  • the parameter list of one or a plurality of entities generated based on the set is output to the data extraction device 6 as a set.
  • the data extraction device 6 extracts data to which data names included in the data related information (group) sent from the data related information processing device 10 are assigned from the data storage unit 41 as analysis target data. Based on the analysis target data, the analysis device 7 uses the parameters set in the parameter list sent directly from the data-related information processing device 10 or via the data extraction device 6 as input parameters to analyze the analysis target device. Make a diagnosis.
  • FIG. 8 is a diagram showing an abnormality detection engine that detects an abnormality of a device as an example of an analysis tool.
  • the parameter list is generated for each device specified by the entity name as described above, the data (sensor output data) corresponding to the parameters set for the device is input to the abnormality detection engine. Detect devices that are abnormal candidates.
  • data-related information corresponding sensor output data
  • the data for this analysis is specified based on the installation location, type, and signal name of the device specified from the data name included in the data related information as described above.
  • the entity name and the property name are corrected by the entity name converting unit 12 and the property name converting unit 13.
  • the influence of the notation in the data name cannot be lost and at least one of the entity name and the property name is generated in an incorrect notation. Can occur. Since the data related information 32 and 33 are originally data related information to be set like the data related information 34 and 35 in FIG. 4, the entity names are not written correctly.
  • FIG. 10 shows an example of the parameter list when the parameter list generating unit 14 generates based on the data related information illustrated in FIG.
  • the parameter 4 of the “B1F system air conditioner scenario” should specify the data related information 32 whose property name is “status change value”, but is not specified because it is determined that the entity name is different. As a result, nothing is set in the parameter 4 of the “B1F system air conditioner scenario”, and the parameter list 36 of the “B1F system air conditioner AHU-1 scenario” is generated separately. Further, the parameter 2 of “3F system air conditioner scenario” should specify the data related information 33 whose property name is “SA temperature setting”, but is not specified because it is determined that the entity name is different. As a result, nothing is set in the parameter 2 of “3F system air conditioner scenario”, and the parameter list 37 of “13F system air conditioner scenario” IV is generated separately.
  • the control unit 18 activates the parameter list complement processing unit 15.
  • the parameter list complementing processing unit 15 performs the following processing for each scenario with reference to the data characteristic rule.
  • FIG. 11 is a diagram showing a setting example of data characteristic rules set in advance in the data characteristic rule storage unit 24 in the present embodiment.
  • the data characteristic rule at least one of a rule indicating characteristics of output data of each sensor to be set as a parameter and a rule indicating relation between output data of sensors is defined. If an appropriate data ID set is set as a parameter list corresponding to each scenario, the relationship that the data or data set corresponding to each data ID matches all the rules specified in the data characteristic rule It is in. Therefore, the parameter list complementing processing unit 15 searches the data ID to be set for the parameter for which no data ID is set with reference to the data characteristic rule as follows.
  • the parameter list complementing processing unit 15 when reading the parameter list of the first “B1F system air conditioner scenario” included in the parameter list, the parameter list complementing processing unit 15 recognizes that no data ID is set for the parameter 4 in the parameter list. .
  • the parameter list complement processing unit 15 extracts a rule including the parameter 4 from the data characteristic rules set in the data characteristic rule storage unit 24. In the setting example of the data characteristic rule illustrated in FIG. 11, only rule 1 is extracted. That is, here, the parameter list complement processing unit 15 performs parameter complementation using the rule 1. Since this rule 1 includes parameters 1 to 3, the parameter list complementing processing unit 15 acquires the data corresponding to the data ID set in the parameters 1 to 3 by reading the data from the data storage unit 41. (Step 104). The predetermined period for reading data is determined in advance.
  • the parameter list complementing processing unit 15 obtains the data by reading all data except the data stored in the data storage unit 41, strictly speaking, the data corresponding to the data IDs set in the parameters 1 to 3 ( Step 105). Then, one of the data corresponding to the data ID set in the parameters 1 to 3 and the read data is sequentially applied to the rule 1.
  • the parameter list complementation processing unit 15 calculates the degree of agreement with the rule (the number of data that matches the rule / the total number of data within a predetermined period) for each of the read data (step 106). It can be said that the higher the matching degree, the more correct data corresponding to the data ID to be set in the parameter 4. Therefore, the parameter list of the “B1F system air conditioner scenario” may be completed by automatically setting the data ID of the data with the highest degree of matching in the parameter 4. However, in this embodiment, an administrator or the like is set.
  • the parameter list complementation processing unit 15 calculates the degree of coincidence for all the data included in the data storage unit 41, the upper-level predetermined number of data related information of the degree of coincidence is obtained as “B1F system air conditioner scenario.
  • "" Is displayed on the display 58 together with the data related information set as parameters in the parameter list (step 107).
  • the data ID to be set in the parameter 4 may be selected by the administrator or the like.
  • the parameter list complementing processing unit 15 sets the data ID of the data related information selected by the administrator or the like to the parameter 4 for which the data ID has not been set, so that the “B1F system air conditioner scenario” is set.
  • the data ID to be set in the parameter 4 of the “B1F system air conditioner scenario” described above is set in any scenario (“B1F system air conditioner AHU-1 scenario” in the above example).
  • Any of the set scenarios in the above example, “B1F system air conditioner AHU-1 scenario” may be deleted because it is a scenario added to the parameter list due to a mistake in notation.
  • the parameter list complementing processing unit 15 As is clear from the processing contents in the parameter list complement processing unit 15 described above, it is preferable to perform processing from a small number of scenarios in which no data ID is set for the parameter. This is because the “B1F system air conditioner AHU-1 scenario” can be deleted by processing the “B1F system air conditioner scenario” as in the above example. If it is attempted to perform the process of complementing the parameters for the “B1F system air conditioner AHU-1 scenario”, the parameter list complementing processing unit 15 applies the correct parameter 1 by applying data of any combination to the plurality of parameters that are not set. , 2 and 3 must be searched, and the processing load increases. The same applies to the relationship between “3F system air conditioner scenario” and “13F system air conditioner scenario”.
  • the parameter list complement processing unit 15 applies the data extracted from the data storage unit 41 to the parameters 3 and 4 and calculates the degree of match according to the data characteristic rule.
  • the above-described data is sequentially read out from the parameter list in which the number of set parameters is more than half, and is set as a processing target for search processing applied to the data characteristic rule. This makes it possible to efficiently supplement the parameter list.
  • the parameter list complementing processing unit 15 recognizes that the data ID is not set for the parameter 2 therein.
  • the parameter list complement processing unit 15 extracts a rule including the parameter 2 from the data characteristic rules set in the data characteristic rule storage unit 24. In the setting example of the data characteristic rule illustrated in FIG. 11, rule 1 and rule 2 are extracted. Since this rule 1 includes parameters 1, 3, and 4, the parameter list complementation processing unit 15 sends data corresponding to the data ID set in the parameters 1, 3, and 4 from the data storage unit 41. read out.
  • the parameter list complement processing unit 15 reads one piece of data stored in the data storage unit 41 as described above, the data corresponding to the data ID set in the parameters 1, 3 and 4, and the read data Is applied to rule 1 to calculate the degree of match. Further, the parameter list complement processing unit 15 applies the read data to the rule 2 and calculates the degree of coincidence.
  • the degree of matching calculated for each rule may be averaged to calculate the degree of matching of the “3F system air conditioner scenario”.
  • the parameter list complementation processing unit 15 calculates the degree of coincidence for all the data included in the data storage unit 41
  • the parameter ID of “3F system air conditioner scenario” ⁇ is obtained from the upper predetermined number of data IDs of the degree of coincidence. It is displayed on the display 58 together with data related information set as parameters in the list. Thereby, the data ID to be set in the parameter 2 may be selected by the administrator or the like. In this way, the parameter list of “3F system air conditioner scenario” is completed. Specifically, a parameter list having the contents illustrated in FIG. 7 is generated.
  • the parameter list supplement processing unit 15 supplements the parameter list based on the data characteristic rule.
  • FIG. 12A, 12B, and 13 the setting contents of rule 2 and rule 3 of the data characteristic rule will be described with reference to FIGS. 12A, 12B, and 13.
  • FIG. 1 the horizontal axis indicates the time when the data was acquired, and the vertical axis indicates the output data values of all the sensors although the names are different.
  • the set temperature is data having a characteristic that does not move up and down frequently and a constant value continues as illustrated in FIG. 12A. is there.
  • the value changes instantaneously, and the amount of change is an integral multiple of a predetermined value (for example, 0.1 ° C.).
  • the measured value at room temperature is data having a characteristic that the constant value does not continue as illustrated in FIG. 12B and can move up and down unlike the set value.
  • the rule 2 of the data characteristic rule is that the value that the data of parameter 2 can take is less than 10 within a predetermined time, for example, within 1 hour, in other words, the data value does not change 10 times or more within 1 hour. It is a rule to show. That is, it is considered that parameter 2 should be set with data-related information corresponding to the set value. It should be noted that “10”, which means the threshold value between the set value and the measured value, may be set to an appropriate value according to the data characteristics.
  • the supply air temperature is data having a characteristic that the upper and lower limits are determined by the installation location of the device as illustrated in FIG. .
  • Rule 3 indicates that the data that can be taken by parameter 1 is greater than 1 and less than 10.
  • the upper limit value “10” and the lower limit value “1” may be set appropriately according to the data characteristics.
  • FIG. 14 is a diagram showing a data setting example of a part of the data related information included in the data related information group.
  • entity name and the property name are the same as in this example, two pieces of data related information corresponding to the parameter 1 of the “B1F system air conditioner scenario” exist.
  • one of these data-related information is erroneously written due to human error. Even in such a case, it is possible to specify correct data-related information by applying a rule such as rule 2 or rule 3, for example.
  • the parameter list generating unit 14 generates a parameter list with missing parameters. Become.
  • the parameter list supplement processing unit 15 supplements the parameter list.
  • the setting contents of the data related information storage unit 21 remain incorrect. Therefore, in the present embodiment, a correction / complementation processing unit 16 is provided so that incorrect entity names and property names can be corrected / complemented. That is, when it is detected that the parameters are complemented by the parameter list complement processing unit 15, or when correct data related information is selected from the duplicated data related information as illustrated in FIG. Then, the correction / complement processing unit 16 is activated.
  • the correction / complementation processing unit 16 When activated, the correction / complementation processing unit 16 displays the data related information of the scenario (entity name) corresponding to the parameter list completed by the parameter list supplementing processing unit 15 or a set of data related information on the display 58. Then, the administrator or the like is made to correct the entity name or property name of the data related information including the incorrect notation.
  • the data related information output unit 17 stores a plurality of data related information to be processed in the data related information storage.
  • the parameter list of one or a plurality of entities generated based on the data related information is read from the parameter list storage unit 23 from the unit 21, and data is extracted by combining the read data related information (group) and the parameter list.
  • the analysis device 7 performs analysis, diagnosis, and the like of the analysis target device.
  • HDD hard disk drive

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PCT/JP2015/085191 2014-12-19 2015-12-16 データ関連情報処理装置及びプログラム WO2016098805A1 (ja)

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CN110012070A (zh) * 2019-03-06 2019-07-12 中国南方电网有限责任公司 一种基于命名空间的智能录波器同源数据多域应用的方法
WO2020132903A1 (zh) * 2018-12-25 2020-07-02 深圳配天智能技术研究院有限公司 机器人程序指令编译方法、机器人控制系统及存储装置
US11726441B2 (en) 2021-03-17 2023-08-15 Kabushiki Kaisha Toshiba Information processing apparatus, information processing method, information processing system, and non-transitory computer readable medium

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JP2007171808A (ja) * 2005-12-26 2007-07-05 Canon Inc 情報処理装置
JP2014215902A (ja) * 2013-04-26 2014-11-17 三菱電機ビルテクノサービス株式会社 データ名称抽出装置及びプログラム

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Publication number Priority date Publication date Assignee Title
WO2020132903A1 (zh) * 2018-12-25 2020-07-02 深圳配天智能技术研究院有限公司 机器人程序指令编译方法、机器人控制系统及存储装置
CN110012070A (zh) * 2019-03-06 2019-07-12 中国南方电网有限责任公司 一种基于命名空间的智能录波器同源数据多域应用的方法
CN110012070B (zh) * 2019-03-06 2022-02-15 中国南方电网有限责任公司 一种基于命名空间的智能录波器同源数据多域应用的方法
US11726441B2 (en) 2021-03-17 2023-08-15 Kabushiki Kaisha Toshiba Information processing apparatus, information processing method, information processing system, and non-transitory computer readable medium

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